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Lean manufacturers transcendence to green manufacturing

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Title:
Lean manufacturers transcendence to green manufacturing correlating the diffusion of lean and green manufacturing systems
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Book
Language:
English
Creator:
Bergmiller, Gary G
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
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Subjects / Keywords:
Environmentally conscious manufacturing
Continuous improvement
Waste minimization
Sustainable development
Shingo Prize
Dissertations, Academic -- Industrial Engineering -- Doctoral -- USF
Genre:
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Scientific evidence of human impact on the natural environment, such as global warming, continues to mount. Green manufacturing systems that focus on minimizing environmental impact of manufacturing processes and products are ever more important to our sustainable future. Green manufacturing systems are slow to gain acceptance as manufacturers are focused on implementing Lean manufacturing systems, generally considered the most competitive manufacturing systems in the world.^ ^In recent years, researchers and the US Environmental Protection Agency (EPA) have sought to "build a bridge" between Lean and Green manufacturing systems, in hopes that the rapid expanse of Lean can serve as a catalyst to the implementation of Green manufacturing systems.This study contributes to this growing body of knowledge by determining if leading Lean manufacturers are transcending beyond the traditional limits of Lean and implementing Green manufacturing systems as part of their overallwaste reduction strategy. In this work Lean manufacturing plants that have been evaluated by a panel of experts from the Shingo Prize for Excellence in Manufacturing are surveyed on the diffusion of Green manufacturing system practices throughout their operation. A full system correlation analysis is performed utilizing forty-eight measures of Lean and Green manufacturing systems under the categories of management system, waste reducing techniques, and results.^ Data analysis indicates that known Lean manufacturers are significantly Greener than the general population of manufacturers in twenty-five of twenty-six measures of Green manufacturing. Lean manufacturers who implement Green manufacturing systems have the strongest results in both Lean and Green result areas, particularly cost reduction, indicating synergy between Lean and Green manufacturing systems. Manufacturing plants that choose to vertically integrate versus horizontally integrate their Lean systems transcend to Green manufacturing. Mexican plants in the study practice significantly higher levels of material resource efficiency and are more inclined to develop industrial partnerships to resolve environmental issues. The study also identifies a critical need for integrating Lean and Green management systems to drive synergistic waste reducing techniques throughout the operation.^ ^An integrated Lean and Green manufacturing system model, dubbed "Zero Waste Manufacturing", is proposed as a solution for economically and environmentally sustainable manufacturing.
Thesis:
Dissertation (Ph.D.)--University of South Florida, 2006.
Bibliography:
Includes bibliographical references.
System Details:
System requirements: World Wide Web browser and PDF reader.
System Details:
Mode of access: World Wide Web.
Statement of Responsibility:
by Gary G. Bergmiller.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 282 pages.
General Note:
Includes vita.

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University of South Florida Library
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University of South Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 001920446
oclc - 189837850
usfldc doi - E14-SFE0001847
usfldc handle - e14.1847
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SFS0026165:00001


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ABSTRACT: Scientific evidence of human impact on the natural environment, such as global warming, continues to mount. Green manufacturing systems that focus on minimizing environmental impact of manufacturing processes and products are ever more important to our sustainable future. Green manufacturing systems are slow to gain acceptance as manufacturers are focused on implementing Lean manufacturing systems, generally considered the most competitive manufacturing systems in the world.^ ^In recent years, researchers and the US Environmental Protection Agency (EPA) have sought to "build a bridge" between Lean and Green manufacturing systems, in hopes that the rapid expanse of Lean can serve as a catalyst to the implementation of Green manufacturing systems.This study contributes to this growing body of knowledge by determining if leading Lean manufacturers are transcending beyond the traditional limits of Lean and implementing Green manufacturing systems as part of their overallwaste reduction strategy. In this work Lean manufacturing plants that have been evaluated by a panel of experts from the Shingo Prize for Excellence in Manufacturing are surveyed on the diffusion of Green manufacturing system practices throughout their operation. A full system correlation analysis is performed utilizing forty-eight measures of Lean and Green manufacturing systems under the categories of management system, waste reducing techniques, and results.^ Data analysis indicates that known Lean manufacturers are significantly Greener than the general population of manufacturers in twenty-five of twenty-six measures of Green manufacturing. Lean manufacturers who implement Green manufacturing systems have the strongest results in both Lean and Green result areas, particularly cost reduction, indicating synergy between Lean and Green manufacturing systems. Manufacturing plants that choose to vertically integrate versus horizontally integrate their Lean systems transcend to Green manufacturing. Mexican plants in the study practice significantly higher levels of material resource efficiency and are more inclined to develop industrial partnerships to resolve environmental issues. The study also identifies a critical need for integrating Lean and Green management systems to drive synergistic waste reducing techniques throughout the operation.^ ^An integrated Lean and Green manufacturing system model, dubbed "Zero Waste Manufacturing", is proposed as a solution for economically and environmentally sustainable manufacturing.
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PAGE 1

Lean Manufacturers Transcendence to Green Manufacturing: Correlating the Diffusion of Lean and Green Manufact uring Systems by Gary G. Bergmiller A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Industrial and Management Systems Engine ering College of Engineering University of South Florida Co-Major Professor: Paul Mccright, Ph.D. Co-Major Professor: Ali Yalcin, Ph.D. Glenn Besterfield Ph.D. Michael Brannick Ph.D. Sheldon Busansky Ph.D. Date of Approval: October 9, 2006 Keywords: environmentally conscious manufacturing, continuo us improvement, waste minimization, sustainable development, Shingo Pr ize Copyright 2006, Gary G. Bergmiller

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Dedication To my loving wife Dianna and our wonderful children Brigit and Leo. Through this long journey your support was unwavering and I could not have accomplished it without you by my side

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Acknowledgements This dissertation is the culmination of years of effort a nd support by the wonderful group of friends I have gained along this awesome jou rney. A dissertation is like climbing a great mountain from whose summit you see so many other mountains, and you are equipped with the knowledge and confidenc e to climb them all. I was privileged to have such a supportive research commit tee: To Paul McCright who prepared and guided me from the very be ginning of this journey, offered encouragement at ever valley, celebrated ever y peak along the way, and personally assured the quality of this paper. To Ali Y alcin who stepped-up when a co-chair was needed and offered structure and expedie ncy to get me through this process most efficiently. To Sheldon Busansky who pl ayed a brilliant “devils advocate” to assure the study was strong and achievable. To Michael Brannick who guided me through the challenging terrain of sta tistical analysis by offering many hours of consultation. To Glenn Besterfield who always had thought provoking questions to make me think beyond the confinem ents of my study. To the late Richard Stessel who instilled in me the respon sibility and urgency to integrate environmental issues into Industrial Engineer ing research. To the Shingo Prize team at Utah State University wh o offered incredible support and access to their information and industrial partners. Their support assured a high level of strength and credibility, otherwise un achievable. I personally want to thank Ross Robson for his vision and commitment to fur ther Lean and Green manufacturing research.

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i Table of Contents List of Tables v List of Figures vi Abstract vii Chapter One Introduction 1 Background 1 Relevance of Topic 3 Purpose of Study 9 Organization of Research 11 Chapter Two Literature Review 13 Introduction 13 Background 13 Lean Manufacturing Literature Review 17 Background 17 Lean Manufacturing Wastes 21 Defects 22 Over-production 23 Transportation 26 Waiting 26 Inventory 26 Motion 27 Processing (excess) 28 Review of Lean Manufacturing System Models 29 The Womack Model 30 The Panizzolo Model 33 SAE J4000 Model 35 The Liker Model 40 The Shingo Prize Model 44 Green Manufacturing Literature Review 46 Background 46 Green Manufacturing Wastes 48 Green Manufacturing Models 50 Industrial Ecology 53 Green Management System Models 56 The Seven Quality Criteria Model 69 The Eleven Quality Criteria Model 70

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ii EPA Core Waste Minimization Elements 71 EPA Voluntary Environmental Programs 77 Source Reduction Review Project 77 Pollution Prevention in Enforcement Settlement Policy 78 Pollution Prevention Incentives for States 78 33/50 Program 78 Green Lights Program 78 Energy Star Computers 79 Design for the Environment 79 National Industrial Competitiveness through Efficiency 80 The Toxic Release Inventory 80 Pollution-Prevention Information Clearinghouse 80 Clean Technologies Program 80 Ciambrone Model 81 Dillon and Fischer Model 82 GEMI Model 83 Responsible Care Program 84 EPA Guide to Pollution Prevention 85 Design for the Environment 88 Total Cost Accounting 92 Scallon and Sten Model 95 Compliance Group 96 Alignment Group 97 Expansion Group 99 Integration Group 101 The Russo Model 104 Russo Methodology 105 Melnyk, Stroufe, Calantone Model 106 Melnyk Abstract 107 Melnyk Hypotheses 107 Melnyk Methodology 108 Melnyk Findings 109 Lean and Green Manufacturing Studies and Models 110 Introduction 110 The Florida Study 112 The Rothenberg Study 116 The King, Lenox Study 120 The EPA Study 126 Chapter Summary 128 Chapter Three Theoretical Constructs 129 Introduction 129 Theory 131

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iii Research Model Construction 135 Description of Research Model 141 Statement of Hypotheses 143 Chapter Summary 145 Chapter Four Methodology 146 Introduction 146 Definition of Variables 146 Lean Independent Variables 147 Green Dependent Variables 150 Control Variables 151 Survey Instrument 152 On-line Survey Development 154 Survey Testing 159 Survey Administration and Data Collection 161 Sample Size and Statistical Analysis 162 Chapter Summary 163 Chapter Five Data Analysis and Results 165 Introduction 165 Presentation of Data 166 Validation of Data 168 Hypothesis Testing 175 Full Correlation and Regressions Analysis 179 Full Correlation Analysis 179 Control Variables 181 Lean Management System Variables 182 Lean Waste Reducing Technique Variables 182 Lean Results Variables 183 Multi-variant Regression Analysis 185 Chapter Summary 190 Chapter Six Discussion of Results 191 Introduction 191 Validation of Data Discussion 192 Hypothesis Testing Discussion 193 Hypothesis I Findings 194 Hypothesis II – IV Findings 196 Full Correlation Analysis Discussion 198 Control Variable Findings 198 Quartile 198 Year 199 Country 201 Lean Management System Findings 205 Lean Waste Reducing Technique Findings 207 Vision and Strategy 207

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iv Innovation 208 Partnerships 210 Support Functions 213 Lean Results Discussion 217 Quality 218 Cost 220 Delivery 224 Customer Satisfaction and Profitability 225 Regression Discussion 229 Chapter Summary 230 Chapter Seven Conclusions and Recommendations 231 Review of Research 231 Conclusions 241 Implications for Practitioners 248 Implications for Academics 252 Limitations of Research Study 253 Opportunities for Future Research 255 Summary 258 References 259 Appendices 267 Appendix A: Expanded Literature Review 268 Shingo Prize Achievement Criteria 268 The Russo Model 278 About The Author End Page

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v List of Tables Table 1. Best Practices at European Lean Manufacturers 34 Table 2. SAE J4000 Criteria 37 Table 3. The Fourteen Toyota Way Principles 40 Table 4. Green Manufacturing Wastes 49 Table 5. Mechanistic versus Organic Cultures 68 Table 6. Melnyk et al Statistics 108 Table 7. Shingo Prize Scoring System Worksheet 149 Table 8. On-line Survey Instrument 156 Table 9. Simple Statistics for Data Set 166 Table 10. Cronbach Coefficient Alphas for Variables 1 69 Table 11. Correlation of Lean Main Variables 173 Table 12. Correlation of Green Main Variables 174 Table 13. T-Test Results for Hypothesis I 176 Table 14. Correlation Matrix for Hypotheses II – IV 178 Table 15: Full Lean and Green Correlation Matrix 180 Table 16. Multi-variant Regression Statistics 186 Table 17. Regression Results of LR with GWRT and LWRT P redictors 189 Table 18. Regression Results of LR with GWRT and LMS Pr edictors 190

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vi List of Figures Figure 1. Over-Production Generates All Other Lean Wa stes 25 Figure 2. The Analogy of Inventory to Water 27 Figure 3. The Shingo Prize Model 45 Figure 4. Industrial Ecology Model 55 Figure 5. EMS Continual Improvement Cycle 58 Figure 6. Interrelationship of ISO14000 Documents 61 Figure 7. Compliance Group 97 Figure 8. Alignment Group 99 Figure 9. Expansion Group 101 Figure 10. Integration Group 103 Figure 11. Evolution of Lean and Green Manufacturing Systems 133 Figure 12. Lean and Green Manufacturing System Model 137 Figure 13. Research Model 142 Figure 14. IRB Approval 160 Figure 15. Evolution of Lean and Green Manufacturing Systems 236

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vii Lean Manufacturers Transcendence to Green Manufacturing: Correlating the Diffusion of Lean and Green Manufact uring Systems Gary G. Bergmiller ABSTRACT Scientific evidence of human impact on the natural env ironment, such as global warming, continues to mount. Green manufacturing syste ms that focus on minimizing environmental impact of manufacturing pro cesses and products are ever more important to our sustainable future. Green manufacturing systems are slow to gain acceptance as manufacturers are focused on im plementing Lean manufacturing systems, generally considered the most comp etitive manufacturing systems in the world. In recent years, r esearchers and the US Environmental Protection Agency (EPA) have sought to “ build a bridge” between Lean and Green manufacturing systems, in hopes that the rapid expanse of Lean can serve as a catalyst to the implementation of Green m anufacturing systems. This study contributes to this growing body of knowledge by determining if leading Lean manufacturers are transcending beyond the traditional limits of Lean and implementing Green manufacturing systems as par t of their overall

PAGE 11

viii waste reduction strategy. In this work Lean manufacturi ng plants that have been evaluated by a panel of experts from the Shingo Priz e for Excellence in Manufacturing are surveyed on the diffusion of Green manufacturing system practices throughout their operation. A full system cor relation analysis is performed utilizing forty-eight measures of Lean and Green manufacturing systems under the categories of management system, waste re ducing techniques, and results. Data analysis indicates that known Lean manufacturers are significantly Greener than the general population of manufacturers in twent y-five of twenty-six measures of Green manufacturing. Lean manufacturers w ho implement Green manufacturing systems have the strongest results in both L ean and Green result areas, particularly cost reduction, indicating synergy be tween Lean and Green manufacturing systems. Manufacturing plants that choose t o vertically integrate versus horizontally integrate their Lean systems transcend to Green manufacturing. Mexican plants in the study practice sign ificantly higher levels of material resource efficiency and are more inclined to de velop industrial partnerships to resolve environmental issues. The study also identifies a critical need for integrating Lean and Green management system s to drive synergistic waste reducing techniques throughout the operation. A n integrated Lean and Green manufacturing system model, dubbed “Zero Waste M anufacturing”, is proposed as a solution for economically and environmen tally sustainable manufacturing.

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1 Chapter One Introduction “The idea that our natural resources were inexhaustible still obtained, and there was as yet no real knowledge of their extent and condition. The relation of the conservation of natural resources to t he problems of National welfare and National efficiency had not yet dawned on the public mind.” Theodore Roosevelt (1858–1919) Background During the end of the twentieth century and into the twenty-first century two types of manufacturing systems that emphasize waste minimizatio n have gained in popularity. They are “Lean” manufacturing systems tha t reduce waste defined as non-value added activity, and “Green” manufacturing systems that reduce waste defined as having adverse environmental impact. Gree n manufacturing is an essential part of sustainable development: Development balanced with the earth’s capacity to supply natural resources and process wa stes.

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2 However, the rate at which Green manufacturing systems are being implemented is not keeping pace with the rapid global expanse of t he manufacturing industry, and thus over time we are becoming less “sustainable”. Lean manufacturing is rapidly spreading around the world as the premier alt ernative to the outdated mass production model, for producing quality product, a t the lowest cost and shortest time. If Green manufacturing can be integrate d with Lean manufacturing, such that Lean serves as a catalyst to Gre en manufacturing implementation, economically and environmentally sustai nable manufacturing could be realized. Several research efforts summarized in the literature r eview indicate how Lean companies show significant environmental improvements by being more resource and energy efficient. Some of the studies also show how both systems share many of the same best practices to reduce their re spective wastes. Yet, the consensus view is that these two systems tend to oper ate independently, administered by distinctly different personnel, even w ithin the same manufacturing plant. The United States Environmenta l Protection Agency (EPA) very eloquently describes the division of environmental personnel focused on Green manufacturing system implementation and operati ons personnel focused on Lean manufacturing system implementation as “living in parallel universes of waste reduction”. (EPA, 2003) To date, there is little empirical evidence that Lean manufacturers transcend beyond the environmental bi-products of their Lean syst em and actually commit

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3 themselves to a comprehensive Green manufacturing system, which leads to continuous environmental improvement. If it is true t hat Lean manufacturing serves as a catalyst to Green manufacturing system impleme ntation, then this relationship could have a profound effect on the mean s by which Green manufacturing systems are promoted by agencies such as the EPA, which is currently supporting research on this topic. This research project intends to determine if Lean manufacturers transcend beyond the t raditional limits of their Lean manufacturing system to include Green manufacturing system components in their overall strategy to reduce waste. Relevance of Topic The twentieth century reminded us that the earth is fi nite in both its ability to produce raw material and safely process waste. Greater l egitimacy is given to global warming theories, emphasizing green house gas r eleases from industrial processes and their products as a major cause. The last decad e of the second millennium was the warmest decade ever recorded, and th e first decade of the new millennium is on track to also earn this dubious dist inction. Global warming causes drought and rising sea levels that in time will fl ood densely populated coastal areas, such as Florida. The past century also showed us how industrialization gon e unchecked can pollute water and airways making the very elements of life toxic. We also saw substantial damage to the ozone layer, the thin film that protects all fauna and flora from the Sun’s deadly ultraviolet radiation (N ational Geographic, 2004).

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4 Biodiversity, the delicate balance of all living thing s, is also threatened as an estimated 10 to 100 species become extinct every day, due mostly to tropical rain forest deforestation for industrial purposes and p opulation expansion. This species extinction rate was only matched by the end of th e Cretaceous age that eliminated the dinosaurs (Meadows et al, 2004). Fortu nately, the environmental legislation (i.e. Clean air and Clean water acts, and the global ban on CFCs) slowed the rate of environmental devastation. But it is a painful reminder of how mankind can, without even knowing it, cause major imbal ances to earth’s life sustaining systems. Global human population, which took 600,000 years, fro m the Stone Age to 1900, to reach 1.6 Billion, reached 6 Billion in the year 2000 (Meadows et al, 2004) (U.S. Census, 2003). At the same time, per cap ita consumption and pollution levels are increasing as developing countries strive for the same standard of living as developed countries. Human popu lation and the amount of waste humans generate are growing at unsustainable rat es: beyond the earth’s ability to support these activities. If something is not done to change the course of human development, the situation will only worsen. Although technology has greatly decreased the environmental impact of industry, the rate of consumption and production outpaces these innovations. All of these environmental indicators lead to several stark realities summarized in the 2004 release of thirty-year update to the famous book Limits to Growth (Meadows, et al 2004). For thirty years researchers at MIT have been refining an

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5 elaborate computer model of earth systems to monitor and predict when raw material “sources” and earth’s capacity for waste processing “sinks” are beyond the earth’s ability to replenish or sustain them. A br ief synopsis of their findings follows: The human economy is now using many critical resources a nd producing wastes at rates that are not sustainable. Sources are being d epleted. Sinks are filling up, in some cases, overflowing. Most throughput streams cannot be maintained over the long term even at their current flow rates, much less increased. We expect many of the will reach their peaks and then de cline in this century. These high rates of throughput are not necessary. Tech nical, distributional, and institutional changes could reduce them greatly while su staining and even improving the average quality of life of the world’ s people. The human burden on the natural environment is alre ady above sustainable levels, and it cannot be maintained for more than a g eneration or two. As a consequence, there are already apparent many negative impacts on human health and the economy. The true costs of materials are increasing. (Meadows et al, 2004) A global solution is required that allows for progress, while not degrading the overall quality of the environment. Many believe t hat ‘sustainable development’ is the only reasonable solution for humans to achieve ba lance with nature. The simplest definition of sustainable development is ‘…deve lopment that meets the needs of the present without compromising the ability for future generations to meet their own needs.’ (WCED, 1991) This does not impl y absolute limits to growth, rather, that consumption of natural resources an d the emission of wastes do not exceed the earth’s ability to support these acti vities. The following quote from Meadows captures the distinction between developmen t and growth: “… To ‘grow’ means to increase in size by the assimilatio n or accretion of materials. To ‘develop’ means to expand or realize t he potentials of; to bring to a fuller, greater, or better state. When something g rows it gets quantitatively

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6 bigger, when it develops it gets qualitatively bette r, or at least different. Quantitative growth and qualitative improvement fol low different laws. Our planet develops over time without growing. Our economy, a su bsystem of the finite and non-growing earth, must eventually adapt to a similar pattern of development.” (Meadows et. al., 2004) Sustainable development theorists break global environm ental problems into two major socio-economic categories, population growth and u nsustainable resource consumption. Population is growing exponentially, most ly as a result of developing nation’s birth rates. Industrial nation’s p er capita natural resource consumption is much greater than that of developing na tions. “Americans pollute 30 to 100 times more than the average third world cit izen”(Prokop, 1993). These combined behaviors of industrial and developing nation s are unsustainable. Some sociologists believe that families in developing na tions compensate for high infant and child mortality rates by having large families. Lack of birth control also increases unwanted pregnancies in developing nation s. There are other religious and social paradigms that lead to high birth rate. Regardless of the root cause, over-population causes people in developing nati ons to strip their natural landscapes so they can expand their villages, grow addit ional crops, and raise cattle (typically for export to industrial nations) to support their families. Deforestation causes precious topsoil to be washed into t he waterways making the land and water incapable of regeneration. (Mead ows et al, 2004) History shows that as a country becomes industrialized popu lation growth slows to zero. The sociological reasoning for this phenomenon is that industrialization improves the standard of living, which reduces infant mo rtality rates. Child health security leads families to limit their size, to a point where zero net population

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7 growth occurs. Zero population growth means that natur al habitats are not destroyed by human migration. Although industrial na tions experience little population growth, their per capita natural resource consumption is the greatest in the world. Manufacturing practices, waste disposal met hods, and consumer behavior together have caused industrial nations to con sume and degrade natural resources at an unsustainable rate. Here in l ies the paradox: If industrialization is the proven way to stem population growth, yet the source of most environmental waste, how can industrialization occur in a sustainable manner? One of the essential components of a sustainable society is Green manufacturing, manufacturing that assures sustainability in resource extraction, material processing, product use and disposal. Open-ended processes such as resource extraction and waste disposal are replaced with a “closed loop” industrial system that emphasizes waste reduction, reuse an d recycling. Green manufacturing could solve the unsustainable behaviors o f both developing and industrialized countries. Industrialized countries could maintain the same standard of living with less adverse impact on the envir onment. Developing countries could industrialize without devastating thei r natural resources. This would increase their economic and health security, even tually leading to zero population growth. Yet, given all of the importance of Green manufactu ring to the global environmental problem, many companies are still skeptica l about the business

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8 benefits of Green manufacturing. Even though many Gr een manufacturing success stories have proven this point, it seems most manufact uring managers still see environmental waste minimization not as a com petitive opportunity but as a necessary evil, simply to avoid EPA sanctions and fut ure liability. Burt Hamner, a major advocate of environmental waste minim ization, graphically depicted a sorry state of affairs by indicating how indu stry was littered with the bodies of unemployed pollution prevention experts wh o tried to sell waste minimization initiatives on environmental merits rath er than on the basis of resource efficiency and cost reduction. (Hamner, 2002). However, most companies readily see the business benefits of Lean manufacturing. Any efforts to link Green manufacturin g with Lean manufacturing can serve as a catalyst to promote Green manufacturing a nd the resulting environmentally sustainable benefits. If it is true th at Lean and Green systems are complementary and even synergistic, the debate over whether being Green is good for business or not could end. Clearly this subje ct is worthy of complete exploration. In recent years, the EPA has funded research that shows ho w manufacturers implementing Lean are having significant Green results (e.g. less energy, less scrap, less floor space per unit output). However, the EP A is quick to note that Lean strategies do not target environmental wastes, rat her the traditional 7 wastes associated with Lean (Defects, Over-production, Tra nsport, Waiting, Inventory, Motion, excess-Processing – DOTWIMP) They are eager to promote

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9 research to “build a bridge” between Lean and Green t o help integrate true Green waste reducing techniques. (EPA, 2003). One strong realization the EPA made in its recent study is that Lean companies develop a “waste reduction culture” that is essential to the company embracing Lean or Green manufacturing systems. They find that L ean companies have already built waste reducing infrastructure that puts t hem well on their way to building a Green manufacturing system. If Lean manufa cturing serves as a catalyst to Green manufacturing, then in addition to t he productivity, quality, and cycle time improvements realized by the manufacturer, so ciety benefits from its improved environmental performance: a win-win scenario (EPA, 2003). Purpose of Study This dissertation builds upon recent research regarding the relationship between Lean and Green manufacturing systems. An empirical study of North America’s leading Lean manufacturers is conducted to determine if there is in fact a direct correlation between the level of diffusion of the Le an manufacturing system and the level of diffusion of the Green manufacturing syste m. The study performed on a set of known Lean manufacturers, recognized by exp erts from the Shingo Prize for Excellence in Manufacturing. This dissertation will advance the Lean and Green manuf acturing body of knowledge by determining if Lean manufacturing plants have expanded their systemic approach to waste reduction to include Green waste reduction. In other

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10 words, do Lean manufacturers transcend beyond the enviro nmentally beneficial byproducts of their Lean implementation to embrace a systemic approach to environmental waste reduction, akin to their systemic app roach to reducing wastes associated with their Lean manufacturing system? Th e research question, put more succinctly is: Do Lean manufacturers transcend to Green manufacturing? The unique contribution this dissertation makes is that i t answers the research question from a full manufacturing systems perspective, o n a population of leading Lean manufacturers. For purposes of this dissert ation, a manufacturing system is defined as a collection of best practices that toge ther achieve the objectives of that manufacturing system, to include but n ot limited to, management systems (i.e. policies and procedures), waste re ducing techniques (i.e. actual process changes), and measurable results. For comparative purposes, this study classifies both Lean a nd Green manufacturing system components into the same three mai n categories: Management systems, Waste reducing techniques, and Results The management system defines the policies and procedures that create the environment/culture that commits the organization towa rd waste reduction, respective to each manufacturing system. Waste reducing t echniques are the specific process (both business and production process) practi ces associated with each manufacturing system that result in waste reduc tion, respective to each

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11 manufacturing system. Results are the measurable impro vements to the stated objectives of each manufacturing system. Comparative models developed in this study are based o n leading scholarly research of Lean and Green manufacturing systems. It is important to develop models for each system that are robust enough to capture the complexities of each system, yet general enough to allow for meaningfu l correlation analysis between major factors of the two systems on a “apples to apples” basis. Organization of Research Chapter 1 presents an introduction to the research to pic, its relevance, and purpose of this dissertation research. Chapter 2 reviews the academic literature that is relev ant to the topic of Lean and Green manufacturing systems. The first part of the Lit erature review offers a detailed review of Lean manufacturing system literatur e to provide in-depth understanding of Lean Philosophy and system components. This section is followed by analogous review of Green manufacturing system literature. The last section of the literature review is dedicated to previo us research on the relationships between Lean and Green manufacturing syste ms that preceded this dissertation study. Chapter 3 synthesizes previous Lean and Green manufactu ring studies to build a foundation of this dissertation study. An evolutionary theory of Lean and Green systems is described to identify the research gap this study intends to fill.

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12 Leading models of Lean and Green manufacturing systems a re reviewed for application in the study’s comparative research model. The chapter concludes with the statement of hypotheses this study sets out to pr ove. Chapter 4 describes the research methodology. This enta ils the description of the independent, dependent and control variables, de velopment and validation of research instruments, survey administration and data colle ction, and the selection of tools for statistical analysis. Chapter 5 presents the results of this study along with the statistical reasoning behind these outcomes. Lean and Green manufacturing models are held up for statistical verification, main hypotheses are tested, and results of a full correlation and multi-variant regression analysis are described in d etail. Chapter 6 contains a discussion and interpretation of the results presented in Chapter 5 to give meaning to the statistical findings. Chapter 7 presents the conclusions and contributions thi s study will make to both theory building and practice. It contains an overview, including the limitations of this study, directions for further research and a brief summary of what was learned from this study.

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13 Chapter Two Literature Review Introduction The literature review will begin with a historical ba ckground of Lean and Green manufacturing systems in order to bring the reader up to date as to how these systems, and related research, evolved over time. Follo wing the background section will be a section dedicated to the latest research on Lean manufacturing system models followed by a similar section for Green ma nufacturing systems. Both the Lean and Green sections will describe the waste s these individual systems target and the various system models used to reduce them. Finally, the literature review will summarize all of the studies fo und to date that explored Lean and Green system correlation. This will prepare t he reader for chapter three, where the literature review is synthesized to f orm the research model for this study. Background Early attempts to reduce the environmental impact of manufacturing processes had a negative relationship with productivity, and c ost. Christiansen and Haveman (1981), Barbera and McConnell (1990) found t hat pollution abatement increased operating cost and/or reduction in plant produ ctivity. The reason for

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14 this negative relationship is that pollution abatement was addressed at the endof-the-pipe. Environmental solutions were costly addons to existing processes and even restricted process output. Not only did these s olutions restrict the manufacturing process, they were also ineffective in e liminating the targeted pollutants. End-of-pipe solutions simply transfer the m edia of the pollutant: e.g., a scrubber transfers air pollution into solid/hazardous waste 1 In other words, end-of-pipe solutions are a lose-lose scenario. The 1980’s and 1990’s experienced a fundamental shift in how environmental issues were addressed. Rather than focus solely on end-o f-pipe solutions, manufacturers started to address environmental waste at the source. In the late 1980’s and early 1990’s a movement began to disprove t he adversarial relationship between environment and productivity an d instead claim that “pollution prevention pays”. The simple logic expressed in this movement is that pollution is essentially poorly used resources that cost m oney to dispose of and can lead to potential liability. In a study of compan ies in the Standard and Poor’s 500 index, Hart and Ahuja (1996) found that efforts to reduce emissions (as measured from the Toxic Release Inventory (TRI), repo rted to the EPA) were significantly related to operating and financial perfo rmance. Several studies evolved that looked at the relationship between env ironmental performance and manufacturing performance. Morris (1997) who looked a t the relationship between TRI emissions and Return on Assets (ROA) found th at environmental performance reduced operating costs. 1 It should be noted that transferring a waste from an airborn state to a solid waste may reduce the ne ar term environmental impact of the pollutant.

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15 One of the major proponents of this change in industri al thinking was the Office of Technology Assessment, who made it clear that polluti on prevention and minimization of environmental waste at the source were the way of the future. (Hirschorn and Oldenburg, 1988; Roy, 1988; Office of Policy Planning and Evaluation; 1991, Byers, 1992). International inter est in proactive environmental management systems that embody the principles of PP/WM l ed to the creation of ISO14000, an international Environmental Management System (EMS) standard, in the mid 1990’s. All of these approaches to improvin g the environmental performance of companies are categorized under the su bject of Green manufacturing, for purposes of this study. During this same period in the twentieth century, sever al advanced manufacturing strategies were beginning to transform traditional approaches to quality and productivity. One of these was Lean manufa cturing, a term coined by the MIT research team that studied the Japanese automot ive manufacturing industry and compared it to other country’s automotive manufacturing performance. The MIT study, embodied in the book, “The Machine that Changed the World” (Womack, 1990) proved that Lean manufacturers had sup erior productivity, quality, and responsiveness over tradition al (mass production) manufacturers. The term Lean reflected a philosophy that targeted wa ste in every facet of the manufacturing business, including suppliers and customers, design, human resources, management, etc. A survey by Osterman (1994) shows significant

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16 adoption of Lean manufacturing techniques amongst US m anufacturers. MacDuffie (1995) identified performance gains as a resu lt of implementing Lean manufacturing. Ichniowski (1993) found significant perf ormance gains from a bundle of innovative manufacturing and work organizat ion practices associated with the Lean system. Confronted with the undeniable benefits of Lean manufacturing, companies all over the world started ju mping on the Lean manufacturing bandwagon during the 1990’s and early 21 st century. Growing interest in both Lean and Green manufacturin g systems led to natural curiosity about their potential relationship. The fi ndings from an MIT research effort indicates a relationship between Lean manufactu ring and innovative environmental practices (Maxwell et al, 2001). Wallace (1995) indicated that both radical technology innovation and continuous impro vement (e.g. kaizen) created significant opportunities for pollution prevent ion. Researchers at the University of Michigan found that efforts to prevent p ollution and reduce emissions had a positive effect on industrial performanc e (Hart et al, 1996). Early studies on Lean and Green manufacturing systems and their potential relationship led to scholarly research and the creation of system models in the late 1990’s and this work continues today. These studies a re summarized in the literature review that follows. The literature revi ew will first explore literature specialized to either Lean or Green manufacturing system s in order to gain a strong understanding of the components that comprise thes e systems. Secondly, the literature review will explore all of the studies found focused on the

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17 Lean and Green relationship to understand the correlat ions found to date and the methodologies used to achieve these results. Synthesis of this literature review in Chapter three will identify the research gap and proposed actions to close that gap. The literature review is based on research through lea ding journals and books on Lean and/or Green manufacturing. Articles were found through searches on a variety of scholarly engineering, industry and business databases. Books were typically found through searches on trade organization websites, publishing houses specific to topical areas, and recommended through Lean and Environmental listserv communication. Lean Manufacturing Literature Review Background Manufacturers are rapidly transforming their manufact uring systems from traditional mass production to flexible lean systems. As early as 1994, Osterman found a significant rate of adoption of Lean manufactu ring systems across a wide sample of U.S. business establishments. A more recent stu dy found that 50% of US manufacturers are implementing Lean waste reducing t echniques, with 10% fully implementing the Lean manufacturing system (EPA, 2003). The flexibility and precision of these systems allows efficient production of small quantities of products at high levels of quality. In a modern worl d where product personalization is as much a requirement as quality and cost, Lean systems are

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18 essential. Even high volume/low mix companies without t he need for enhanced process flexibility, find that Lean systems are justified by the resource efficiency and quality benefits alone. Traditionally, manufacturers believed there was a trad e-off between cost and quality, cost and lot size. Essentially, building a lo t of the same product quickly, without regard to quality was the paradigm of tradit ional “mass production” manufacturing. It was the Japanese, in particular To yota, who pioneered Lean manufacturing that challenged both of these assumptions. In essence, they saw defects as waste and put in place methods to prevent def ects rather than inspection techniques to catch them at the end of the p rocess. Likewise, they viewed over-production as wasteful, and focused on reduci ng process set-up times, so that they could economically produce smaller q uantities of products efficiently that coincided with actual customer demand ( Hayes et al, 1984, Skinner, 1974). The success of Japanese manufacturing led many scholars to r esearch these methods in the 1980’s and 1990’s, (see for example Mon den, 1983, Schronberger, 1982, Ohno, 1988, Ishikawa, 1985, Juran e t al, 1988). Early articles and books on Lean manufacturing focused on Lean w aste reducing techniques and gave little attention to the managemen t system aspects of this system. For the early observers of Lean companies like T oyota in Japan, it was obvious to see the waste reducing techniques in practice out on the factory floor (i.e. kan ban systems, work cells). It was far less obvious t o observe the

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19 management system that led to the creative culture that developed and sustained these techniques. Part of the problem was that by the time American and European observers came to Japan to observe these Lean plants, the managem ent systems were so much a part of the culture that they did not stand ou t to the observers or even the host companies as worth mentioning (Womack, 1996). How ever it became clear after companies tried for decades to implement the wast e reducing techniques, that these solutions were not sustainable, and the com panies implementing them were not achieving the same Lean results as they saw in Ja pan. As a result, during the 1980s, interest in Lean waste reducing techni ques, often referred to as Just-in-time, began to wane. During this same period there was considerable research in to managerial philosophies (Chase, 1980, 1987, Amoake-Gyaampah, 198 9, Neely, 1993, Miller, 1981, Filippini, 1997). The Total Quality Manageme nt philosophy suggests that the quality of management was as important, if not mo re important, than the management of quality. Combining all of these appr oaches into a single manufacturing strategy led to the startling revelation that there was no longer a trade-off between quality, productivity and flexibil ity. Lean factories manufacture a wide range of models, while maintaining high level s of quality and productivity. (Panizzolo, 1998) (Krafcik, 1988). James Womack and Daniel Jones, who coined the term “Lean ”, were instrumental in explaining Ohno’s manufacturing system i n terms the western

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20 world could understand in their book Lean Thinking Womack describes Lean production as a system that uses less, in terms of all inpu ts, to create outputs similar to those of traditional mass production systems, wh ile offering increased choices for the final consumer (Womack, 1996). For examp le, they restated Ohno’s forms of waste as follows: mistakes/defects which req uire rectification, production of items that no one wants so that inventori es pile up, processing steps which aren’t actually needed, movement of employe es and transport of goods from one place to another without any purpose, groups of people in a downstream activity standing around waiting because an u pstream activity has not delivered on time, and goods and services which don ’t meet the needs of the customer. (Womack, 1996). Womack and Daniels advocated Ohno’s view of total waste e liminating by stating “Our earnest advice to lean firms today is simple. To h ell with your competitors; compete against perfection by identifying all activities that are muda (waste) and eliminating them. This is an absolute rather than a relative standard which can provide the essential North Star for any organization .” (Womack, 1996) In the early 1990’s with the coining of the term Lea n in the release of the in-depth studies of the automotive industry, James Womack promoted a more complete view of Lean manufacturing system, to include the manag ement system that led to a continuous waste reducing culture, which in turn de veloped and sustained the Lean waste reducing techniques. Interest in Lean m anufacturing systems

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21 was reborn, and since that time it is hard to find a b ook or article that does not talk about the management system and cultural aspects of Lean. The Womack study found Toyota as the model for Lean man ufacturing. As a matter of fact, the title ‘Toyota Production System’ w as commonly used to describe Lean manufacturing systems, before an MIT study c oined the term ‘Lean Manufacturing’, during an in-depth study of the automotive industry in the late 1980’s and early 1990’s. The MIT study, embodie d in the book ‘The Machine That Changed The World’ offered strong evidence that Lean manufacturers had better quality, cost and response tim e performance than traditional manufacturers. While the study provided e xamples of Lean manufacturing successes and a philosophical overview of Lean manufacturing, it doesn’t clearly spell out the specific best practices of the Lean manufacturing system. Nonetheless, the MIT studies were very popular a nd led to further research into the constructs of the Lean manufacturing syst em. In addition to Womack’s efforts, several recent scholarly efforts have done a worthy job of defining complete models of the Lean manufacturing syste m. They are described in detail after an overview of the seven wa stes that Lean manufacturing systems strive to eliminate. Lean Manufacturing Wastes In the Lean manufacturing vernacular, waste is defined as any human activity which absorbs resources but creates no value: mistakes/defects w hich require rectification, production of items that no one wants so that inventories pile up,

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22 processing steps which aren’t actually needed, movement of employees and transport of goods from one place to another without a ny purpose, groups of people in a downstream activity standing around waitin g because an upstream activity has not delivered on time, and goods and ser vices which don’t meet the needs of the customer. (LEI, 2003) In particular, Lean manufacturing focuses on the reducti on of seven wastes. They are: Defects, Over-production, Transport, Waiting, Inventory, Motion, and excess-Processing (D.O.T.W.I.M.P.). The unachievable obje ctive is to eliminate all of these wastes, so that nothing but value added ef fort exists in the manufacturing process. Reducing these wastes requires con siderable changes in the traditional manufacturing operation. Essentia lly the Lean manufacturing system is a never-ending commitment to reducing the seven wastes mentioned, through the application of best practices. The followin g is an in-depth definition of the seven Lean wastes. (LEI, 2003) Defects A defect occurs when a product or component no longer conf orms to the requirement of the customer. This customer can be inte rnal or external to the manufacturing operation. At a minimum, a defect req uires rework to resolve the problem. If the defect makes it to the customer, this w ill strain customer-supplier relations. Defects are wasteful because they are non-va lue added in nature, and require additional non-value added use of labor and materials to resolve them. In addition, defects create forms of wastes. (LEI, 2003)

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23 For example, defects cause excess processing that would not have been needed if the defect did not occur in the first place. Occurren ce of defects often slows or stops the progress of an assembly line causing other processe s to wait until the defect generating process is resolved. If a product make s it to a customer and must be returned, this leads to unnecessary transportation Transportation leads to emission of green house gases and use of energy If a product requires rework or in the worst case needs to be scrapped, then excess processing is required. Excess processing requires additional energy If the process uses hazardous materials and/or water in processing or cleaning the product, additional amounts of these resources are required. P roduct that is scrapped becomes solid waste which may also have hazardous waste characteristics. (LEI, 2003) Over-production Over-production occurs when production output exceeds actu al customer orders. Over-production is considered the greatest form of waste in the Lean manufacturing philosophy. The reason for this is becau se overproduction can lead to the generation of all other forms of Lean wa stes (figure 1). If production quantities exceed customer orders, the manufacturer incur s several risks. At a minimum, the manufacturer is exposed to possible custome r engineering changes that may require teardown, rework, and even scra pping the product. It is also quite possible, in this era of rapid change, tha t the product will become obsolete or unwanted while waiting for the next orde r and need to be severely

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24 discounted and even scrapped completely. As mentioned e arlier, scrap generates solid and possibly hazardous waste. (LEI, 2003 ) In addition, over-production generates excess inventory that must be stored until the customer needs it. This inventory must be transported to a safe storage location. Excess inventory in the form of work in process requires production operators to move this WIP either out of the way or t o the next process, leading to excessive motion Transportation and storage require energy usage, an d generation of green house gases. Generation of excess inv entory consumes capacity, which means other processes and other customer or ders must wait until processing is complete. (LEI, 2003)

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25 OverProduction Inventory Storage costs ties up resources handling damage production imbalance late supplier deliveries defects downtime long setups transport & handling long lead time wasted space hides problems Figure 1. Over-Production Generates All Other Lean Wa stes (LEI, 2002)

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26 Transportation Transportation is wasteful because it is non-value adde d. In the ideal Lean manufacturing process, all processes are next to each oth er. And, in the Lean model, manufacturing operations should be close to sup pliers and customers. Transportation leads to excess operator motion, which ca n lead to injury. If transportation requires a vehicle or conveyor, this prob ably leads to energy use, and green house gas emissions. In addition, excessive tran sportation implies that processes are far from each other. Distance impedes communication, critical for quality feedback that can prevent or at lea st minimize defects. Also, distance leads to inventory, due to the impractical nat ure of moving small amounts of parts or products over great distances. In fa ct, the greater the distance, the greater the inventory build-up prior t o transport. (LEI, 2003) Waiting Waiting occurs when processes are not balanced. If machines and operators are waiting either for a preceding process to deliver mate rial (starved) or for a proceeding operation to take material (blocking), then they are not producing value. Machines that are idling, waiting to produce, may still consume energy, consume water and generate hazardous and green house em issions. (LEI, 2003) Inventory An analogy is made in the Lean manufacturing philosop hy that compares inventory to water. The water/inventory hides, like rocks under the water,

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27 manufacturing problems such as machine breakdowns, absente eism, imbalance, defects, long set-up times, etc. Of course, hiding the problems does not keep them from causing trouble, it only makes it harder to find the root causes and fix them. Lowering the inventory steadily exposes the pro blems, and allows the company to deal with them once and for all. (LEI, 2 003) Figure 2. The Analogy of Inventory to Water (LEI, 2 003) Motion Motion in the Lean philosophy is any unnecessary human movement. Unnecessary motion is non-value added and consumes human energy that could be used more productively. Unnecessary motion can often lead to injury as well. At a minimum it leads to fatigue, which causes defects and all of the ills that go Raw Material Finished Product Sea of Inventory (WIP) Long Transportation Absenteeism Poor Scheduling Quality Problems Machine Breakdowns Line Imbalance Vendor Delivery Long Setup Times Communication Problems

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28 with defects. If excess motion is required to move produ ct from one operation to the next, either inventory will build or the operat or will spend a great deal of time moving individual units from one operation to the n ext. Ideally, Lean manufacturing work design minimizes unnecessary motion so that an operator can build a quality product with the least amount of e ffort. (LEI, 2003) Processing (excess) Too much of a good thing is not always a good thing. Sometimes an operator will strive to make a perfect part, surpassing the custo mer’s requirement. While their intentions are good, over-processing can lead to d efects. An example of this is applying too much heat to a solder joint to mak e it perfect, beyond customer requirements, and burning up the electronic com ponent in the process. In addition, excess processing takes time that could be spen t on value added processing. Slowing down a process causes proceeding process es to wait and preceding operations to either wait or build inventor y. It requires excess operator motion. If excess processing requires any machinery, it w astes energy and generates emissions. Excess processing also causes consumption o f water or hazardous materials as well. (LEI, 2003) As mentioned previously, the objective of the Lean m anufacturing system is to identify and reduce the aforementioned seven wastes. Since the mid-1940’s, when Toyota pioneered this new manufacturing system, m any innovative practices have been developed to realize this objective. Researchers and practitioners alike have tried to refine these practices i nto a set of “best” practices

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29 that are a together effectively identify and elimina te wastes and are generally applicable to most, if not all, manufacturing operatio ns. The next section attempts to define a working set of best practices for pu rposes of this doctoral study, based on preceding scholarly research. Review of Lean Manufacturing System Models In reviewing past and present Lean research, there app ears to be an evolution of research focus. Early studies focused on the characteristics o f production processes of Lean companies, such as production planning and process and equipment solutions. Research focus then began to look at the functions that support production operations, such as Human resources and Product design. More recently, research focused on the extended enterp rise, including customer relations and supplier relations in the Lean Enterpri se. (Sakakibara, Flynn, Schroeder, Morris, 1992, Panizzolo, 1998, Womack, 1996 ) The most recent research (SAE, 1999, Liker, 2004, Shing o, 2003, SME, 2006) emphasizes the necessity of management commitment and t rust in developing and sustaining a Lean culture. Each research area buil ds on the next, emphasizing the importance of developing all areas of the business to realize true Lean system potential. The literature review of Lean manufacturing best pra ctices focuses on several studies that define Lean manufacturing as a system of co mplementary best practices. Too many people have mistakenly characterized Lean manufacturing

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30 as a short list of best practices implemented on the facto ry floor. In reality, if all elements of the Lean system are not addressed, the fact ory floor best practices are at best short lived and the entire system is unsustai nable. This part of the literature review begins with the studies that promote d the system nature of Lean manufacturing and are also the studies that coined th e term “Lean”. These studies performed by an MIT research team led by James W omack are instrumental in defining the principles of the Lean m anufacturing system. The review of the Womack led studies is followed by more rece nt studies that actually do a far better job of specifying the specific componen ts/best practices of the Lean system. The Womack Model As mentioned in the introduction of this section, James P Womack led an M.I.T. study of the automotive industry that led to the creat ion of the term “Lean manufacturing”. The study, performed in the late 1 980’s and early 1990’s, compared the practices of Japanese automotive manufacture rs that pioneered the Lean manufacturing system against the practices of Am erican and European manufacturers (Womack, 1996). This research team then con ducted another study in the mid-1990’s that took a more global look at Lean manufacturers and attempted to capture their common best practices (Womack 1996). The Womack studies identified 5 core principles of Lean manuf acturing. They are specifying value, identifying the value stream, flow, pull, and perfection.

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31 Specify Value: Value is defined by the customer and is the goods and /or services that the customer pays for. Anything that does not dir ectly contribute to the creation of value is considered waste in the Lean philo sophy. This concept of value to the Lean manufacturing system is akin to quali ty in the Total Quality Management system whereby quality and value are ultim ately defined by the customer. Identify the Value Stream: The value stream is the set of all the specific action s required to bring products or services to the customer. Mapping the value stream helps companies identify value added steps versus st eps that are wasteful. Once wasteful steps are identified, they ar e targeted for reduction by applying a variety of Lean manufacturing best practice s. Typically, value stream steps are grouped in three categ ories: Value added (e.g. transformation of raw material into saleable product ), non-value added but necessary for the time being (e.g. quality inspection t hat is catching defects before going to the customer), and non-value added and immediately removable (e.g. excess travel distance between operations that can b e eliminated by simple improvements to plant layout). It should be noted that the Womack studies do not clear ly stipulate best practices used to reduce waste. Fortunately, other studi es in the literature review do a better job of detailing Lean manufacturing system best practices. (Womack, 1996)

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32 Flow: Once value added steps are identified in the val ue stream and wasteful steps are targeted for reduction, the next step is to ma ke product and information flow freely from value added step to value added ste p. The speed of this flow through the value stream, often termed cycle time, de fines the responsiveness to customer needs. The concept of flow challenges the concept of economic orde r quantity (EOQ). In the flow model, emphasis is place on only building exactly what the customer needs and moving that quantity of product or informat ion through the value added steps without delay. In the EOQ model, emphasis is place on building larger batches of products at each stage in the process in order to maximize machine utilization and minimize machine changeover. Unfortunately, larger batches lead to larger levels o f work in process (WIP) inventory that leads to longer cycle times. Shorter cycl e time relies on more frequent changeovers, so Lean manufacturing practices wer e developed to reduce changeover/set-up time. For example the Sing le Minute Exchange of Die (SMED) approach was developed at Toyota to reduce changeover times of all tooling to less than ten minutes. Pull: “Push” versus “pull” are simple concepts with profound e ffects on cycle time. From a enterprise perspective, “pull” means that a pro duct is only built when there is an actual customer order for that product. Pus h means that products are built in anticipation of product demand. The latter assumes significant delays in the supply chain and therefore is relegated to foreca sting and assumptions. The

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33 former assumes short cycle times and quick response to a custom er’s needs. From and internal factory perspective “push” is a term u sed to describe traditional batch manufacturing where batches of products are produc ed at each operation’s rate and then staged for the next operation for the next processing step. Pull systems internal to the factory control each stage of prod uction by only allowing preceding operations to produce when the next operatio n needs parts. This lowers WIP and shortens cycle time. The Panizzolo Model The Panizzolo study (1998) interviewed leading Europ ean Lean manufacturers to understand the diffusion process of Lean manufacturing b est practices. The Panizzolo study (1998) found that Lean manufacturing system deployment began in the core production functions (Production Control an d Process and equipment). Then, implementation moves upward into the manufacturing support functions (Product design, Human resources, Manage ment strategy), and then eventually outwards to the extended enterpr ise (supplier and customer relations). It should be noted that Panizzolo (1998) found that amongst recognized leaders in Lean manufacturing, most had fully implemented Lea n best practices in the core production functions. Diffusion of best practices in t he support functions was partial, and most companies had insignificant level s of diffusion of best practices in the extended enterprise. The Lean best pra ctices that Panizzolo studied in particular are organized categorically in th e following table.

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34 Table 1. Best Practices at European Lean Manufacturers Human Resources HR1 multifunction workers HR2 expansion of autonomy and responsibility HR3 few levels of management HR4 employee involvement in cont. improvement HR5 work time flexibility HR6 team decision making HR7 worker training HR8 Pay for performance, innovative appraisal Process and Equipment PE1 setup reduction PE2 flow lines PE3 cellular manufacturing PE4 rigorous preventative maintenance (TPM) PE5 “error proof” equipment (poka-yoke) PE6 progressive use of new process technologies PE7 process capability (6 sigma) PE8 order and cleanliness (5S) PE9 continuous reduction of cycle time (JIT) Production Planning PPC1 leveled production (JIT) and Control PPC2 synchronized scheduling (mix model) PPC3 mixed model scheduling PPC4 under-capacity scheduling PPC5 small lot sizing PPC6 visual control of shop floor (visual factory) PPC7 overlapped production PPC8 pull flow control Product Design PD1 parts standardization PD2 product modularization PD3 mushroom concept (?) PD4 design for manufacturing PD5 phase overlapping PD6 multifunctional design teams Supplier Relationships SR1 JIT deliveries SR2 open orders (blanket orders) SR3 quality at the source SR4 schedule/MRP sharing SR5 supplier involvement in quality improvement SR6 reduction in vendor base SR7 long-term contracts SR8 total cost supplier evaluation SR9 supplier involvement in product design Customer Relations CR1 reliable and prompt deliveries CR2 commercial actions to stabilize demand CR3 capability and competence of sales network CR4 early information on customer needs CR5 flexibility in meeting customer requirements CR6 serviced enhanced product CR7 customer involvement in product design CR8 customer involvement in quality programs

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35 SAE J4000 Model In 1999 the Society of Automotive Engineers (SAE) rel eased a Lean Operations Best Practices Specification titled the J4000. The J4000 specification includes the Lean best practice categories identified in the Pani zzolo study (i.e. production processes, support functions, extended enterprise). In add ition, the J4000 has a complete section devoted to Management Commitment. I n particular the J4000 indicates that leading Lean manufacturers exhibit the following management commitment best practices: Lean is considered a strategic tool essential to the compa ny’s competitiveness. Structured Lean policy statements are in place. Lean goals and objectives are defined. Lean philosophy is communicated to all, and employees a re vigorously trained on lean practices. Senior officials exhibit strong leadership of Lean de ployment. There are regular Lean progress reviews and managers are accountable for lean progress. Meaningful incentives are in place to reward Lean pro gress. A non-blaming, performance oriented, process-driven o rganizational atmosphere exists. No employee has reason to perceive his livelihood is in jeopardy by contributing to organizational Lean progress. Management has chosen to adhere to Lean principles in the face of short term operating objectives inconsistent with Lean progress. SAE developed the J4000 based on several years of resear ch assessing the best practices of recognized Lean manufacturers from a va riety of industry sectors. Each best practice was validated by identifying its existence in at least three of the leading Lean companies. The validation efforts were documented in

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36 SAE document RR3003, which I have reviewed for complet eness. The end result is a generalized set of best practices that all m anufacturers aspiring to become Lean should implement. The J4000 specification is structured as a survey companies can use to benchmark their performance against the best practices of industry’s Lean manufacturing leaders. SAE began the best-practices surv ey in 1998 and developed a comprehensive measurement template and m ethodology to evaluate companies that had been identified as model Lean companies. The companies were selected based on input from automaker ex ecutives, industry analysts, and academics, as well as independent research. ( SAE, 1999) It stands to reason that SAE would develop a Lean speci fication since the automotive industry has been under the greatest competi tive pressure to adopt Lean systems. The MIT study on the automotive industry in the early 1990s, which coined the term ‘Lean’, found that Lean manufac turing principles were the leading reason for Japanese dominance of the automoti ve industry during the 1980s. (Womack, 1996) Now most automotive manufacturers in the U.S. are transforming their traditional manufacturing systems t o Lean systems. (Rothenberg, 2001) Popularity of these studies and succ essful cases of Lean manufacturing systems has lead to broad based acceptance o f the Lean manufacturing system throughout all manufacturing secto rs. Both the research and application of best practices concisely culminate in th e J4000 Lean manufacturing system best practices specification, making i t an ideal tool

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37 assessing a company’s “Leanness”. The sections of the J400 s pecification dealing with Lean best practices are listed below for com pleteness. In parentheses are the weighting factors assigned by SAE t o the respective sections, indicating the relative importance of that sect ion to the overall effectiveness of the Lean system. (SAE,1999) Table 2. SAE J4000 Criteria 4) Management/Trust (25%) 4.1) Continuous Progress in Implementing Lean Operati ng Methods is the organization’s primary tool pursuing its strategic obj ectives. 4.2) Structured policy deployment techniques are used t o plan the organization’s Lean deployment. 4.3) Lean progress targets are defined and have been effectively communicated 4.4) Knowledge of the philosophy and mechanics of Lean operation has been obtained and effectively communicated. 4.5) The organization’s senior managers are actively l eading the deployment of Lean practices (senior managers of the site) 4.6) Lean progress is reviewed by senior management ag ainst planned targets on a regular basis. 4.7) Meaningful incentives that reward organizational Lean progress are in place 4.8) Individual managers’ performance is evaluated an d rewarded relative to Lean progress 4.9) A non-blaming, performance oriented, process-drive n organizational atmosphere exists 4.10) There is regular, direct personal involvement by senior management with operating workforce concerning Lean practices 4.11) Consistent policy for disposition of individuals ma de surplus by lean progress in place and followed 4.12) No employee has reason to perceive their liveli hood to be jeopardized by contributing to organizational lean progress 4.13) Management has chosen to adhere to Lean princip les in the face of short term operating objectives inconsistent with Lean progre ss

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38 Table 2. (Continued) 5. People (25%) 5.1) Adequate training resources are provided and pai d employees training time is made available. 5.2) The training syllabus includes training in the Lea n-specific tools and measurable suitable to the organization’s needs, at all level within the organization. 5.3) Training is conducted as scheduled, records are not k ept or are inadequate or no measure of training effectiveness exists. 5.4) Organization is structured to correspond to the str ucture and sequence of the value chain through the enterprise. 5.5) Each employee participates in the structure as corre sponds to his work role 5.6) Labor and employment policies and agreements are in place which allow Lean progress within the organization 5.7) Team authority level and accountability level is clearly defined. 5.8) Employee development through quality circles/Cont inuous Improvement (CI) teams is encouraged and supported at all levels. 5.9) Team is accountable for CI in its segment of the v alue chain 5.10) Team decision-making authority and authority to act corresponds to the level of team accountability 5.11) Management does not supersede team decisions and a ctions when within the teams authority 5.12) Management supports team decisions and actions with required resources, consistent with good business practices. 6. Information (Sections 6,7 & 8 together equal 25%) 6.1) Adequate and accurate operating information is a vailable to members of the organization as needed. 6.2) Knowledge is shared across the organization 6.3) Data collection and its use are the responsibility o f the individuals most closely associated with that part of the process 6.4) The operating financial system is structured to pre sent correctly the results of lean progress 7. Supplier/Organization/Customer Chain 7.1) Both suppliers and customers participate at the ea rliest possible stage in the organization’s undertaking of a product/process proj ect 7.2) Both suppliers and customers are appropriately re presented on the organization’s product/process/project teams. 7.3) Both suppliers and customers participate in regula r reviews of product/process/project progress.

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39 Table 2. (Continued) 7.4) Effective incentives for supplier, organization an d customer are in place that reward shared performance improvements or cost red uction 8. Product 8.1) Product and process design is conducted by fully int egrated teams with team representation by all stakeholders. 8.2) Cost, performance and attribute specifications for p roduct and process are unambiguous, measurable and agreed to by all stakehold ers 8.3) Product and process design is conducted from a lifecycle systems approach 8.4) Product design and process capability parameters a re set to be as robust as possible, consistent with good business practice. 8.5) Provision is made for continuity of team knowledg e for duration of product/process launch. 8.6) Lead times for product and process design are measur ed and being continually 9. Process/Flow (25%) 9.1) The work environment is clean, well organized an d audited regularly against standardized 5S practices. 9.2) An effective planned preventative maintenance sy stem is in place with the appropriate maintenance conducted at the prescribed freq uencies for all equipment 9.3) Bills of material are accurately catalogued and sta ndard operations are accurately routed, timed and have been value engineer ed. 9.4) Value stream is fully mapped and products are physi cally segregated into like-process streams. 9.5) Production sequence is Load-smoothed to customer P ull, and Demand is leveled over the manufactured planning period. 9.6) Process flow is controlled by visual means, internal to the process. 9.7) Process is in statistical control with capability requi rements being met and process variability continually reduced. 9.8) Preventative action, using disciplined problem-solv ing method, is taken and documented in each instance of product or process nonconform ance. 9.9) Production flow commences only upon receipt of shi pment order. Process flows at takt time rate, in single unit quantities, to point of customer receipt. 9.10) Procedures are in place and being followed that result in continually shorter changeover times and smaller lot sizes. 9.11) Factory layout requires continuously synchronous flo w of material and infactory product travel distance is continually reduced a s flow path is improved. (SAE,1999)

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40 The Liker Model Dr. Jeffery Liker has been studying the Toyota producti on system for twenty years and was granted full access to Toyota executives, em ployees, and factories, both in Japan and the United States to deve lop a book explicitly detailing the Toyota Production System which is synonymo us with Lean manufacturing. In his recent book ( The Toyota Way, 2004 ) Dr. Liker reveals the fourteen principles that comprise the Lean manufacturin g system. Dr. Liker’s description of the Lean system is similar to J ames Womack’s, but provides considerably more detail in all aspects of the manufacturing system. Dr. Liker’s books on the Toyota way are among the top sell ing books on the subject of Lean. This is a strong indication that practitioners and industry leaders are yearning for more systems based understanding of Lean ma nufacturing. For completeness, the following table summarizes Dr. Liker’s f ourteen principles that depict the Lean manufacturing system. Table 3. The Fourteen Toyota Way Principles The Fourteen Toyota Way Principles 1) Base your management decisions on a long-term philosop hy, even at the expense of short-term financial goals Have philosophical sense of the purpose that supersedes any short-term decision making. Generate value for the customer, society, and the econo my it is your starting point. Evaluate every function in the company in terms of it s ability to achieve this. Be responsible. Strive to decide your own fate. Act wi th self reliance and trust in your own abilities.

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41 Table 3. (Continued) 2) Create continuous process flow to bring problems to t he surface Redesign work processes to achieve high value-added, conti nuous flow. Strive to cut back the to zero the time that any work project is sitt ing idle or waiting for someone to work on it. Create flow to move material and information fast as well as to link processes and people together so that problems surface right away. Make flow evident throughout your organizational cul ture. 3) Use "pull" systems to avoid overproduction Provide your downstream customers in the production pro cess with what the want, when they want it and in the amount that they want. Minimize your work in process and warehousing of invent ory by stocking small amounts of each product and frequently restocking based on what the customer actually takes away. Be responsive to the day-by-day shifts in customer demand rather than relying on computer schedules and systems to track wasteful inventory. 4) Level out the workload Eliminating overburdened people and equipment and e liminating unevenness in the production schedule. Work to level out the workload of all manufacturing a nd service processes as an alternative to the stop/start approach of working on projects in batches that is typical. 5) Build a culture of stopping to fix problems, to get quality right the first time Quality for the customer drives your value proposition Use all the modern quality assurance methods available. Build into your equipment the capability of detectin g problems and stopping itself. Develop a visual system to alert team and team leads th at a machine or process needs assistance. Build into your organization support systems to quickly solve problems and put in place countermeasures. Build into your culture the philosophy of stopping or slowing down to get quality right the first time. 6) Standardize tasks are the foundation for continuous i mprovement and employee empowerment Use stable repeatable methods everywhere to maintain t he predictability, regular timing, and regular output of your process. Capture the accumulated learning about a process u p to a point in time by standardizing today's best practices. Allow creative and individual e xpression to improve upon the standard; then incorporate it into the new standard so that when a person moves on you can hand off the learning to the next person.

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42 Table 3. (Continued) 7) Use visual control so no problems are hidden Use simple visual indicators to help people determine im mediately whether they are in a standard condition or deviating from it. Avoid using a computer screen when it moves the worker's focus away from the workplace. Design simple visual systems at the place where the work is done, to support flow and pull. Reduce your reports to one piece of paper whenever po ssible, even for your most important financial decisions. 8) Use only reliable, thoroughly tested technology that serves your people and process Use technology to support people, not to replace people Often it is best to work out a process manually before adding technology to support th e process. New technology is often unreliable and difficult to sta ndardize and therefore endangers "flow". A proven process that works generally takes pr ecedence over new and untested technology. Conduct actual tests before adopting new technology in business processes, manufacturing systems, or products. Reject or modify technologies that conflict with your cu lture or that might disrupt stability, reliability and predictability. Nevertheless, encourage your people to consider new techn ologies when looking into new approaches to work. Quickly implement a thoroughly considered technology if it has been proven in trials and it can improve flow in your process. 9) Grow leaders who thoroughly understand the work, li ve the philosophy, and teach it to others Grow leaders from within, rather than buying them fr om outside the organization. Do not view the leader's job as simply accomplishing tas ks and having good people skills. Leaders must be role models of the company's phil osophy and way of doing business. A good leader must understand the daily work in grea t detail so he or she can be the best teacher of your company's philosophy. 10) Develop exceptional people who follow your company' s philosophy Create a strong, stable culture in which company valu es and beliefs are widely shared and lived out over a period of many years. Train exceptional individuals and teams to work within the corporate philosophy to achieve exceptional results. Use cross-functional teams to improve quality and produc tivity and enhance flow by solving difficult technical problems. Empowerment occurs wh en people use the company's tools to improve the company.

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43 Table 3. (Continued) Make an ongoing effort to teach individuals how to wo rk together as teams toward common goals. Teamwork is something that has to be learn ed. 11) Respect your extended network of partners and supplie rs by challenging them and helping them improve Have respect for your partners and suppliers and treat t hem as an extension of your business. Challenge your outside business partners to grow and de velop. Set challenging targets and assist your partners in achieving them. 12) Go and see for yourself to thoroughly understand th e situation Solve problems and improve processes by going to the sour ce and personally observing and verifying data rather than theorizing on the ba sis of what other people or the computer screen tell you. Think and speak based on personally verified data Even high-level managers and executives should go and se e things for themselves, so they will have more than a superficial understanding of the situation. 13)Make decisions slowly by consensus, thoroughly considering al l options; implement decisions rapidly Do not pick a single direction and go down that one pa th until you have thoroughly considered alternatives. Discuss problems and potential solutions with all of those affected, to collect their ideas and get agreement on a path forward. 14) Become a learning organization through relentless reflection and continuous improvement Once you have established a stable process, use continuou s improvement tools to determine the root cause of inefficiencies and apply eff ective countermeasures. Design processes that require almost no inventory. Expo se waste and have employees use a continuous improvement process to eliminate it. Protect the organization knowledge base by developin g stable personnel, slow promotion, and very careful succession systems. Use reflection at key milestones and after you finish a project to openly identify all the shortcomings of the project. Develop countermeasures to av oid the same mistakes again. Learn by standardizing the best practices, rather than reinventing the wheel with each new project and each new manager.

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44 The Shingo Prize Model The Shingo Prize for Excellence in Manufacturing is nam ed for Japanese industrial engineer Shigeo Shingo, who distinguished h imself as one of the world’s leading experts in improving manufacturing pro cesses. Dr. Shingo has been described as an “engineering genius” who helped cre ate and write about many aspects of the revolutionary manufacturing practices which comprise the renowned Toyota Production System. The Prize was established in 1988 to promote awareness of Lean manufacturing concepts and recognize companies in the United States, Can ada, and Mexico that achieve world-class manufacturing status. The Shing o Prize philosophy is that world-class business performance may be achieved thro ugh focused improvements in core manufacturing and business processes. The Shingo Prize recognizes organizations that use wor ld-class manufacturing strategies and practices to achieve world-class results. A pplicants are scored based on the point systems shown in figure 3, and appli cants with high scores receive a site visit from a team of five or more exper t examiners. All applicants who receive a site visit will be publicly recognized as F inalists. Recipients of the annual Shingo prize itself are selected from this prest igious group. The figure below depicts the Shingo Prize criteria in model form. The complete Shingo prize criteria is in appendix A. (Shingo, 2003 )

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45 Figure 3. The Shingo Prize Model The Shingo Prize achievement criteria provide a frame work for identifying and evaluating world-class manufacturing competence and perf ormance. The criteria comprise a business systems model for manufacturing excelle nce, organized into principle sections as pictured in figure 3. The world-class strategies and practices that are referred to in the criteria are presented in sections I through III of the guidelines. W orld-class results are discussed in sections IV and V. There are expected measurem ents for quality, cost, delivery and business results (See appendix A). (Sh ingo, 2003) ENABLERS Leadership Culture and Infrastructure A. Leadership 75 pts B. Empowerment 75 pts CORE OPERATIONS Manufacturing Strategies and System Integration A. Manufacturing Vision and Strategy 50Ppts B. Innovations in Market Service and Product 50pts C. Partnering with Suppliers & Customers 100pts D. World Class Manufacturing operations 250 pts Non-Manufacturing Support Functions 100 RESULTS Quality, Cost and Delivery A. Quality Improvement 75pts B. Cost and Productivity Improvement 75pts C. Delivery and Service Improvement 75pts D. Customer Satisfaction and Profitability 75pts

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46 The Shingo criteria are an excellent example of how t he understanding of the Lean manufacturing system has evolved from a collection of shop floor best practices to a robust Manufacturing system. However, wha t has not evolved during this same period is the definition of waste from a Lean perspective. Except for the studies mentioned in the beginning of the literature review, little attention has been given to the relationship of Lean system wastes and environmental waste. The next section of the literatu re review will attempt to define environmental wastes and the Green manufacturi ng system best practices used to reduce them. Green Manufacturing Literature Review Background Manufacturers are fortunate to live in a time when t hey can be part of the environmental solution rather than the environmental problem. Market conditions and regulatory pressure offer great incentives for Gre en manufacturing and great risks for those that continue polluting the environmen t. Cleaner processes, conservation of material and energy, and the eliminat ion of waste in general make good business sense. In other words, reducing enviro nmental wastes reduces costs and risks of doing business.(Montabon, 2001) The costs and liabilities associated with environmental w aste are not restricted to legal issues, although these can be substantial. Severa l other reasons exist for companies to consider going green. The cost to purchas e and dispose of

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47 hazardous materials continues to rise. Market resistance to environmentally harmful products continues to increase. Environmental co nsciousness of consumers continues to rise. Regulatory hostility increases for known polluters. The primary wastes targeted by a typical Green manufac turing system include hazardous materials, green house gases, solid wastes, wat er usage, and energy. Like Lean manufacturing there are a series of best practi ces used to reduce these wastes. Commitment to reducing environmental wast e through the implementation of best practices is the essential core of a Green manufacturing strategy. A fully implemented Green manufacturing system affects e very function of the manufacturing business. Marketing, accounting, human r esources, supplier and customer relations, design and production are all invol ved in a fully integrated Green manufacturing system. However, it is the rare c ompany that has taken its Green system to these limits. Most manufacturers begin in the manufacturing process and work their way upward and outward over time (Scallon, Sten, 1997) In order to assure general applicability of this study, emphasis will be placed on the core production operations and those that directly affect them. This will help to keep the study to a manageable scope. Unlike the Lean manufacturing system, which is based on th e Toyota Production System established in the 1950’s, the Green manufacturi ng system is in its infancy of development and standardization. Arguably it is not mature enough to be called a system at all. Thus, it is difficult to deve lop a comprehensive yet

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48 generally applicable model for Green manufacturing. However, several common themes and best practices do emerge in looking at leadin g studies on the subject and these will be explored shortly. To help define a Green manufacturing System, it is hel pful to understand its objective, which is to reduce environmental waste. In order to be more specific, several literature sources were tapped on environmental waste and waste metrics. A working definition of hazardous waste was dev eloped in 1985 under the United Nations Environment Program auspices. “… Sol ids, sludges, liquids and containerized gases, other than radioactive and in fectious wastes which, by reason of their chemical activity or toxic, explosive, co rrosive, or other characteristics, cause danger or likely will cause danger to health or the environment, whether alone or when coming into contac t with other waste … “Solid wastes comprise all the wastes arising from human a nd animal activities that are normally solid and are discarded as useless or u nwanted.” (Tchobanoglous, 1993). Additionally, green house gases are also important environmental wastes to consider in this day and age. Green Manufacturing Wastes There are many measures of environmental waste used by manufacturers today. EPA environmental regulations alone have created a n eed to assess companies’ environmental wastes objectively. The following tabl e provides a rather complete set of environmental wastes metrics used by manu facturing and

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49 regulatory agencies to objectively assess and ultimately r educe the environmental impact of manufacturing on the environm ent (NAE, 1997). Table 4. Green Manufacturing Wastes Metric What is measured Advantages Disadvantages Permit Compliance Compliance with applicable permits expressed as exceeding permit limits An essential measure-customers will look first to your compliance with permits Taken alone, a narrow measure indicating that you are doing only what is required. Toxic Release Inventory (TRI) Chemical Releases Over 300 chemicals subject to release annual reporting requirements under SARA Section 313. Information on release is widely available to the public; an effective way to communicate performance. Does not cover all important chemicals or industries; focuses on release volume without accounting for differences in toxicity. 33/50 Chemicals A subset of the TRI chemicals identified by the EPA as priority candidates for voluntary reductions in releases by industry. A more refined list of chemicals than TRI; companies participating in the 33/50 program and meeting goals will receive public credit. Leaves out many important chemicals; not clear that a company not participating Clean Air Act Toxics 189 chemicals listed in the Clean Air Act as air toxics subject to maximum achievable control technology (MACT) standards. MACT standards will be extremely costly to meet. By reducing or eliminating releases, you avoid very high future costs Taken alone, like TRI, not a full measure of environmental performance; focuses only on air, creates risk of shifting problem from air to other media Risk-Weighted Releases Toxic chemicals weighted by their relative toxicity. A more realistic depiction of health and environmental effects than unweighted releases. Toxicity data are frequently highly uncertain; risk-weighted approach has not been generally accepted by key customers-EPA, environmental groups. Waste per Unit of Production Percentage of production lost as waste; generally measured by weight. A very broadly applicable measure that incorporates efficiency in use of resources as well as containment releases to the environment. No priority established in terms of type of wastes; absent other measures, creates an incentive to focus on high-volume, low-toxicity wastes.

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50 Table 4. (Continued) Energy Use Total energy use by all aspects of corporate operations; can be expressed also as carbon dioxide. A comprehensive measure that focuses attention on efficiency in use of key resources; anticipates possible global warming concerns; readily communicated to customer. Energy efficiency is important, but not the only basis on which to evaluate environmental performance; other measures also needed. Solid Waste Generation Total solid waste going to landfills or other disposal facilities An important measure in the public mind because of publicity surrounding landfill capacity shortage; often reflects efficiency in resource use. A very narrow measure of environmental performance; often misinterpreted as the most important criterion to judge performance. Product Life Cycle The total impact of a product on the environment from raw materials sourcing through production use and ultimate disposal The most comprehensive measure of product level impact; a meaningful goal to strive for in resource use efficiency an pollution prevention. Extremely complex to implement; methodologies are not commonly accepted; claims based on product life cycle analysis are frequently treated with skepticism; difficult to apply at a corporate or unit level. Green Manufacturing Models So what does it mean to be a Green manufacturer anywa y? Essentially it means that reducing environmental waste is as important as oth er traditional operational measures such as cost, quality and responsiveness. It impl ies that the organization embraces continuous environmental improv ement in all business functions. It also implies that pollution prevention is regarded as the only reasonable approach to reducing environmental impact, a s opposed to ‘end-ofpipe’ waste containment or transformation. End-of-pipe strategies may let companies get past regula tory emission hurdles, but this approach is a costly alternative to waste minim ization, and does nothing

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51 to reduce the waste of the product after it leaves the factory. Remediation and compliance approaches only apply if a waste can be contain ed once emitted. Major environmental problems such as ozone depletion, green house gases and loss of arable soil cannot be remediated and must be pr evented. The only logical approach to reduce environmental impact is to adopt a c ontinuous process of waste minimization. Companies ignoring environmenta l issues are in danger of losing market penetration and being viewed as part of the problem and not part of the solution. There are several additional incentives for managemen t to commit to a Green manufacturing strategy: A company can reduce exposure to regulatory pressure and the related fines and criminal charges. Green manufacturing solutions improve resource efficien cy, lowering the costs of material, energy, water, waste management and disposal Companies that operate in the global economy will be nefit from global acceptance of environmentally conscious behavior, thereby reducing trade barriers. Consumer pressure for environmentally conscious products is ever increasing. And of course, common sense an ounce of prevention is wo rth a pound of cure. (EPA, 2001) How does a Manufacturer become Green? This is a question of considerable debate. Topics in this area of research are still being defined and new topics are arriving on the scene. In an attempt to define what Green manufacturing actually is, several subjects have been identified that together make up a holistic approach to reducing environmental waste of manufactur ing operations: Green manufacturing. These subjects are summarized below in t he following Green manufacturing literature review.

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52 Starting at the top of the organization, a Green ma nufacturing system should include an Environmental Management System (EMS). Th e EMS defines the corporate environmental policies and procedures that assur e good environmental performance. In particular, ISO14001 is the internat ionally supported model for an EMS. An EMS is very high-level strategic model an d does not necessarily directly reduce waste, rather it creates the environment or culture that leads to waste reducing techniques. When it comes to specific techniques for reducing environ mental waste, this is where pollution prevention and waste minimization pro grams are effective. These tactical programs focused mainly on the operationa l aspects of the manufacturing firm, help companies create continuous en vironmental improvement programs with elements such as improvement team structures, tools for identifying and reducing wastes, etc. In addition there is a specific body of literature on environmentally conscious product and process design, known as Design for the Enviro nment (DfE). This discipline focuses on the engineering side of Green manu facturing. Also, there is a Green accounting discipline, for which one name is Tot al Cost Accounting. Finally, the newest subject relating to Green manufact uring and without question the most broad based, is Industrial Ecology. So broad is this subject, that by all rights, Green manufacturing is simply a part of it. It also makes for a good topic to discuss first to frame the rest of the Green manufactu ring discussion.

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53 Industrial Ecology The philosophy of Industrial Ecology is so profound tha t it warrants mention in this literature review in order to provide a broad p hilosophical framework for the ultimate Green manufacturing system. Industrial ecolog y attempts to look at industrial systems as ecosystems, whereby the waste of one pr ocess becomes the raw material of another: closing the loop of a no rmally open ended industrial system. As if that was not enough of a challenge, indus trial ecology also seeks to find harmony between natural ecosystems and these ne w industrial ecosystems, creating a sustainable future for mankind. Rei d Liefset, of Yale University and editor and chief of the Journal of Industrial Ecology firmly states that Industrial Ecology is still very much in the conceptu al stages, and thus has limited application in this doctoral study. (Liefset, 2000) But, philosophically it offers some of the most powerful rationale for accelera ting the deployment of Green manufacturing systems. Industrial ecology is the means by which humanity can d eliberately and rationally approach, and maintain a desirable carrying capacity, gi ven continued economic, cultural, and technology evolution. The concept requ ires that an industrial system be viewed not in isolation from its surrounding systems but in concert with them. It is a systems view in which one seeks to opt imize the total materials cycle from virgin material to finished material, compo nent, to product, to obsolete product, and to ultimate disposal. Factors to be optimi zed include resources, energy, and capital. (Liefset, 2000)

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54 Industrial ecology differs from traditional waste mini mization and pollution prevention strategies. A single company can make great str ides in waste minimization all by itself and perhaps its suppliers, l ike 3M’s pollution prevention pays (3P) program that reduced air pollution by 120,0 00 tons. Industrial ecology builds on this concept to an industrial ecosystem where the waste byproducts of one manufacture become the inputs to other manufactur e, and products and packaging are returned back into the industrial ecosystem when their useful life is over, rather than in a landfill. The concept of managing materials from raw materials to finished products is common among Lean manufacturers and often referred to as supply chain management. But, supply chain management ends when t he product reaches the consumer. Industrial ecology closed the industrial l oop and considers additionally how the product makes its way back from the consumer to various stages of the industrial ecosystem. The following figur e shows the five life-cycle stages in a typical manufactured product.

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55 Figure 4. Industrial Ecology Model Activities in the five life-cycle stages of a product man ufactured for customer use In an environmentally responsible product, the environ mental impacts are minimized in each stage, not only stage 2. The longterm goal is to reintroduce all material in discarded products into the resource str eams that flow into new products. (Liefset, 2000) Stage 1:Pre-manufacture, is performed by suppliers. Ge nerally drawing virgin resources and producing materials and components Stage 2:Manufacturing Stage 3:Packaging and Transport Component Manufacture Materials Processing Module Assembly Product Assembly Package Ship Customer Use Refurbish Component Recovery Materials Recovery Virgin Materials Extraction 1 Materials Preparation 2 3 4 5

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56 Stage 4:Customer use stage, is influenced by both the u ser and the degree of continuing manufacturing interaction. Stage 5: End of useful life, a product is no longer satisfactory because of obsolescence, component degradation, or changed business o r personal decisions. At this point, it is either refurbished or d iscarded. Eventually, all five phases will become, in some part, the responsibility of the manufacturer. The emerging vision is that the product s minimize their environmental impact throughout all five life cycle st ages, from cradle to reincarnation. Ideally, there is no longer a grave co mmonly known as a landfill. To fulfill the objectives of industrial ecology, manuf acturers have to change their thinking from providing a product to providing a prod uct of service. That is to say providing the service a product provides rather than t he product itself. In this model manufacturers are responsible for the entire life cycle of the product and thus more encouraged to make products that last longer a nd are easily remanufactured. (Liefset, 2000) Consumers are becoming more receptive to the concept of “borrowing” or leasing a product rather than owning it. Automobile leasing is popular and more recently computer leasing is growing. Designers have traditionall y considered only the cost to manufacture and the final performance of their designs. The new concern with the environmental approach to the entire produc t life cycle requires that all life stages be addressed in a structured way. Green Management System Models Management Systems became popular in recent decades wit h the development of international standards for both Quality Managemen t Systems (ISO9000) and

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57 more recently Environmental Management Systems (ISO14 001). ISO refers to the International Standards Organization in Geneva, Switzerland. Manufacturing plants are certified to one of these International stan dards by independent registrars, upon meeting the requirements stated in th e ISO Management system standard. (Russo, 2001) Implementing an environmental management system (EMS) is a process by which an organization’s management identifies regulate d and unregulated environmental aspects and impacts of its operations, assesse s current performance, and develops targets and plans to achieve both significant and incremental environmental improvements. Environmental aspects are human or industrial activities, products, or services that can inter act with the environment. Environmental aspects are evaluated as to whether the y can cause significant environmental impacts or changes. An EMS integrates environmental management into the organization’s overall management system by identifying the policies, environm ental targets, measurements, authority structures and resources necessary t o produce both regulatory compliance as well as environmental perform ance "beyond compliance." A continual improvement cycle is established t hrough this process. (ISO, 2002)

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58 Figure 5. EMS Continual Improvement Cycle ISO 14001 has been gaining in popularity as the model for Environmental Management System since it was finalized in 1996. It is an ideal measure of an environmental management system in that it is general enough to apply to any business environment, yet specific enough to assure that t he right set of policies and procedures are in place to drive Green waste reducin g activity. As with any company wide improvement program, environ mental management must begin at the top. Management commitment and a comprehensive management system that establishes the proper structure fo r Green manufacturing are the essential first steps to becoming a Green manufacturer. This is similar to establishing a Total Quality Manageme nt program (TQM). The ISO9000 series Quality Management System (QMS) specifica tion, offers

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59 companies a model for establishing a company wide TQM p rogram. ISO14000 provides a similar blue print for companies attempting to become Green. (ISO, 2002) The ISO 14001 sanctioned EMS provides the necessary struct ure for sustainable environmental improvement. The ISO 14001 standard f ocuses on process not performance standards. The EMS defines the corporate e nvironmental policies and procedures that assure good environmental performa nce. Documenting the environmental policies and procedures, and identifying those responsible for enacting them, clearly defines everyone’s role in the o rganizations toward improving environmental performance. (ISO, 2002) It is difficult, given the broad scope of industry, to set international standards for environmental performance. This is the job of regulat ory agencies. The role of ISO 14000 is to standardize the system a company has in p lace for environmental management. It can be considered a proa ctive approach if it can be inferred that a well developed and managed envir onmental management system leads to good environmental performance. ISO 1 4000 attempts to lay a foundation for good environmental performance, and a lso attempts to help level the playing field for environmental performance glob ally. (ISO, 2002). A specific example of how ISO 14000 drives management commitmen t to Green manufacturing is illustrated in the following environ mental policy requirement. Top management shall define the organization’s enviro nmental policy and ensure that it is appropriate to the nature, scale and envir onmental impacts of its activities, products or services. It includes a commitment to continua l improvement and prevention of pollution. It includes a commitment to comply with relevant

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60 environmental legislation and regulations, and with o ther requirements to which the organization subscribes. It provides the framework for se tting and reviewing environmental objectives and targets. The policy is docu mented, implemented, maintained and communicated to all employees, and is av ailable to the public (ISO, 2002) The reason for an international standard is because the re has been growing interest in comprehensive environmental programs and a proliferation of national EMS standards in recent years. Most notably are the EM AS and BS7750 standards that ISO 14000 is based upon. A single intern ational standard will simplify international trade issues. Eventually, havin g a certified EMS will be the requirement for doing business, as in the case of ISO 9 000 – Quality Management System standard. Standardizing this process will eliminate the need for a company to have its EMS registered in every country where it does business. The European Union (EU) is imposing stronger environme ntal requirements on companies that conduct trade with EU nations and requir e certain environmental conditions are met before products can be shipped into the EU, such as led free solder in electronics and provisions for recycling of produ cts shipped into the EU. (ROHS, 2006). Perhaps one day in the very near futu re companies conducting business with the EU will also need to be ISO14001 cer tified. The following diagram shows the interrelationship between ISO 14000 documents (Goetsch, 2001):

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61 Figure 6. Interrelationship of ISO14000 Documents Similar to the Quality Management System (QMS) imple mented for ISO 9001, the ISO14001 requires implementation of an Environm ental Management System (EMS) in accordance with defined international ly recognized standards (as set forth in the ISO14001 specification). The ISO140 01 standard specifies requirements for establishing an environmental policy determining environmental aspects & impacts of products/activities/services, planning e nvironmental objectives and measurable targets, implementation & op eration of programs to meet objectives & targets, checking & corrective action, and management review. Implementation of an ISO 14000 Environmental Management System Conformance verification of the Environmental System ISO 14004 Guidance Advice, etc. ISO 14001 EMS Specification Environmental Management System Development & Implementation Conforming Environmental Management System EMS Auditing/ EMS Conformance Verification ISO 14010 General Principles of Environmental Audi ting ISO 14011 Guidance for EMS Auditing ISO 14012 Guidance on EMS Auditor Qualification

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62 As with ISO9001, the key to a successful ISO14001 EMS i s having documented procedures that are implemented and maintained in such a way that successful achievement of environmental goals commensurate with th e nature and scale of our activities is promoted. In addition, the EMS must i nclude appropriate monitoring and review to ensure effective functioning of the EMS and to identify and implement corrective measures in a timely manner. (ISO, 2002) ISO14001 standards include the need for sites to document and make available to the public an Environmental Policy. In addition, p rocedures must be established for ongoing review of the environmental as pects and impacts of products, activities, and services. Based on these environm ental aspects and impacts, environmental goals and objectives must be esta blished that are consistent with the environmental policy. Programs must t hen be set in place to implement these activities. As with the QMS, internal A udits of the EMS must be conducted routinely to ensure that non-conformances to t he system are identified and addressed. In addition, the management review pro cess must ensure top management involvement in the assessment of the EMS, a nd as necessary, addressing need for changes. The Environmental Management System (EMS) document is the central document that describes the interaction of the core eleme nts of the system, and provides a third-party auditor with the key informati on necessary to understand the environmental management systems in-place at the co mpany. Consistent with the principles of ISO14001, the Environmental Po licy and Environmental

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63 Aspects/impacts analysis, including legal and other require ments, shape the program by influencing the selection of specific measurab le environmental goals, objectives, and targets. Specific programs and/or projects must then be developed to achieve these environmental goals, objectives, and targets (in ISO140 01 terms, this would be referred to as "Implementation and Operation"). The checking and corrective action elements of the system help ensure continuous impr ovement by addressing root causes on non-conformances. The ongoing man agement review of the EMS and its elements helps to ensure continuing su itability, adequacy, and effectiveness of the program. (ISO, 2002) For many companies, conformance to ISO 14001 may become a contractual requirement of customers in both the U.S. and the Eur opean Community (EC). Also, because ISO 14000 is a continuation of the ISO 90 00 Product Quality standards, it is expected that ISO 14001 will eventuall y become a requirement for attaining ISO 9001 re-certification. Thus, many compan ies are setting goals to establish environmental management systems that conform to ISO 14001 guidelines in order to remain competitive in the glob al marketplace. For those companies who have already obtained ISO 9001 registra tion and/or follow Total Quality Management (TQM) system principles, the ISO 140 01 registration is a logical next step because it is very similar to ISO 9001 and the principles of TQM. ISO 14001 is an internationally recognized standard fo r environmental management systems. Conformance to the standard can help companies remain

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64 competitive in the marketplace. For many companies, bot h their competitors are seeking registration and their customers are beginning to demand conformance to ISO14001 guidelines. As with the ISO9001 standard, the continuous improvement requirements of the standards lead to regi stered companies eventually needing to require that their suppliers al so comply with the ISO14001 standards. In addition, by establishing and maintaining an Environmental Management System that meets the standards established by ISO14001, companies will be implementing a strong and effective environmental management program. Some of the benefits of implementing an Environmenta l Management System (EMS) in accordance with the ISO14000 standards, include : identifying areas for reduction in energy and other resource consumption, redu cing environmental liability and risk, helping to maintain consistent compli ance with legislative and regulatory requirements, benefiting from regulatory incentives that reward companies showing environmental leadership through cer tified compliance with an internationally recognized EMS standard, preventin g pollution and reducing waste, responding to pressure from customers and sharehold ers, improving community goodwill, profiting in the market for "gree n" products, responding to insurance company pressure for proof of good management before pollutionincident coverage is issued, and demonstrating commitment to high-quality. (ISO, 2002)(Montabon et al, 2001) In addition to the prod uct marketing benefits of obtaining ISO 14001 registration, the U.S. Environme ntal Protection Agency

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65 (EPA) is currently considering regulatory incentives und er its Common Sense Initiative (CSI) program to benefit companies certifie d to ISO 14001. (ISO, 2002) The EPA is very supportive of ISO14001 stating, “the n ew global Environmental Management System standard is proving to be an effecti ve tool in improving industrial environmental performance. The intent of t he standard is to establish and maintain a systematic management plan designed to co ntinually identify and reduce the environmental impacts resulting from the or ganization’s activities, products, and services.” (EPA, 2001) Yet the EPA do es not intend to make ISO14000 a regulatory requirement, rather officials w ill consider a company’s efforts toward ISO14000 when imposing fines if a viola tion is found, likewise with related sentencing imposed by the Justice Department. Other benefits the EPA sees as a result of a company achieving ISO14001 compli ance include public recognition, fewer scheduled inspections and audits in ex change for ISO compliance, faster permitting, adoption in place of com pliance penalties, streamlined reporting paperwork. It may become a requ irement for government suppliers/ vendors. (EPA, 2001) A study of over 1,500 varied manufacturers found many interesting observations about the perceived impact and effectiveness of ISO14001 certification. It should be noted that only 2.5% of the respondents have actua lly achieved ISO14001 certification, although 20% of respondents partake in v oluntary industrial or voluntary EPA environmental programs. The respondent s in this study came from a variety of industries and were in a variety of managerial positions. They

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66 had been involved in a variety of improvement progr ams. Generally speaking respondents perceived ISO14001 as having negative impa cts on core operational metrics (i.e. lead time, cost and quality) They also do not see that ISO14001 will improve their companies’ market place p osition of ability to sell products internationally. The study found that the cl oser a company is to ISO14001 certification the more favorable their opini on of the related benefits to the company. (Russo, 2001) Companies that have attained ISO14001 certification a re more likely to be large, foreign owned, ISO9000 or QS9000 certified, successfull y implemented a TQM program, and effectively utilize cross-functional teams. Compared with other voluntary-based programs aimed at improving environme ntal performance, the evidence indicates that the ISO 14000 certification p rocess is more effective and efficient when viewed in terms of its impact on perform ance. (Montabon, 2001) The study found that for 10 of the 14 dimensions of pe rformance, ISO 14000 is more effective than either Voluntary EPA Programs or Industrial Voluntary Environmental Programs. For 13 of the 14 dimensions, I SO 14000 is more effective than OSHA's Voluntary Prevention Program. W hat these results suggest is that plants actively pursuing ISO 14000 certif ication seem to do better on the various dimensions of performance. The reason fo r this improved performance is to be determined. However, two possible explanations can be identified. T he first is that ISO 14000 is process-oriented rather than output-based. As a result when pursuing this

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67 form of certification, firms are more likely to change the underlying processes. These changes result in more efficient processes, less waste and less pollution. An alternative explanation lies in the requirements f ound in ISO 14000 for outside certification. Plants pursuing this form of certification must demonstrate to a third party that they have met the various requirements of ISO 14000. As a result, these plants are more likely to take this approach more s eriously. Another explanation is that ISO14001 is systemic in nature, touc hing on all aspects of the business. This may serve to create a ‘Green culture’ tha t leads people to thinking Green in all that they do. (Montabon, 2001) One study explored the cultural and organizational im plications of ISO14001 and the results were rather surprising. The Moxen and Stra chan (1998) study finds that ISO14001 implies a rigid top down bureaucratic ap proach to deploying the environmental management system. Specifically, Moxen and Strachan indicate that most of the requirements of ISO14001 are for ma nagement to establish a system of top down policies, measurements and controls, and there is little mention of other employee involvement in the progra m. Furthermore, the authors caution that for environment al innovation to occur an organization must be less mechanistic and role based, an d more flexible and task oriented. In other words, for true environmental innovation to occur, it is critical to improve the innovative environment of the company’s culture. This logic supports the notion that Lean companies may tend m ore toward environmental innovation and improvement than their less lean counterparts. A

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68 key feature of Lean companies is innovation, experiment ation and continuous improvement. While the claims of Moxen and Strachan c oncerning the implied rigidity of ISO14001 may be exaggerated, their poin t that true innovation requires a supporting culture and structure is an important one. The specific difference between what they refer to as a “mechanistic role bas ed structure” versus an “organic task based structure” is summarized in the follo wing table. These characteristics serve as good tools for assessing “organizatio nal readiness” toward implementing Lean or Green manufacturing syste ms. Table 5. Mechanistic versus Organic Cultures Organizational/Cultural Element Mechanistic Management System and Role Culture Organic Management System and Task Culture Management of People Favors extrinsic motivators Employees largely excluded from policy and management issues Favors intrinsic motivators Extensive use of employee involvement schemes Job Design Principles Fixed and narrowly defined Fl exible, role definitions contingent on changing circumstances Organizational Structure and Decision-making Hierarchical, centralized decision-making Co-ordination and control rely on highly formalized and documented rules and procedures Flat, dispersed decision-making Coordination and control based more on shared values and norms Attitudes and Behavior Tradition and precedent exercise powerful influence Rigid work practices, supports status quo or incremental change Challenging and experimenting Adaptable, supports radical and fundamental change Organizational Learning Slow Rapid

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69 The EPA realizes that these tools, core values and prog ram elements are really just parts of a complete management system for minimizin g environmental waste. They also recognize that successful models already exist that can be applied to environmental improvements. They promot e the use of ISO14001 as a premier model for a holistic environmental manageme nt system. But, they also recognize other existing models, based on successful qual ity system models that companies are happily using and may choose to use instead of the ISO14001 model. The following is a summary of these two qualit y based models recommended by the EPA. They are, the 7quality mo del criteria approach, and the 11quality model criteria approach. The Seven Quality Criteria Model The “seven quality criteria model” is based on the nati onal Malcolm Baldridge Award model. Emphasis is on “ how ” you are working to integrate waste minimization into your organization versus “ what ” you are doing specifically. It is believed that the “how” emphasizes a sustainable process of improvement versus specific projects that may be short term in nature. The criteria are: Leadership: Top down direction is critical to any level of success, an d particularly important when looking to integrate P2 across the company. In particular, there are two criteria that measure leader ship. Strategic Planning: Leadership most often uses some fo rm of strategic planning to guide the organization’s course. The P2 program mu st be important in the eyes of senior management and be so represented in the strategic planning process. Interested Party Involvement: No organization operates in isolation. Interested parties include the stakeholders in your P2 program. T hey include customers,

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70 suppliers, regulatory agencies, non-government organiza tions, environmental groups, community groups, and the public at large. Employee Involvement: Employee involvement looks at the bottom up portion of the P2 program that is every bit as important as the top-down portion. Employees are a very important part of the P2 progra m, they are experts in their work areas, and are therefore best at finding P2 solu tions. Process Management: Related to the ISO14001 EMS appr oach, process management focuses on how all work process are managed to facilitate the P2 program. Information Analysis: Information and the analysis of this information is th e fuel for the P2 program. Paying attention to this criteri on is the only way that clear results can be determined. Results: This is the most important criterion in the q uality model. It moves the P2 model from anecdotal information and success stories t o something that will drive all the other criteria. It is not critical that a company do well in all 7 crit eria areas. It is more important that the program addresses all 7 criteria: Breadth is mo re important than depth. (EPA, 2001) The Eleven Quality Criteria Model The 11 Point quality model approach is very similar to the seven point quality model approach except that it adds 4 more points. The total set of elements is listed below: (EPA, 2001) Interested party driven pollution prevention Leadership Continual improvement and learning Valuing employees Fast response Efficient product, service, and process design Long-range view of the future Management by fact Partnership development

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71 Public responsibility and citizenship Results focus EPA Core Waste Minimization Elements Synthesizing these different models, the EPA developed a core list of elements that should be included in any comprehensive Green manu facturing system. Regardless of the approach a company decides to take in mi nimizing environmental waste, ‘all of these elements should be included in their program to assure success’. (EPA, 2001) The common elements are l isted below followed by a brief description of each element: Planning Leadership Metrics and Goals Focus on results Information and analysis Process management Employee involvement (participation) Focus on interested parties The EPA provides excellent planning guidelines for designing a multi-media (air, water, soil) pollution prevention program. Some EPA sources include: the pollution prevention opportunity assessment manual, th e office of research and development, state and technical assistance, pollution p revention clearing house, and benchmarking studies. All pollution prevention pr ograms should emphasize the EPA hierarchy pollution prevention, environmen tally sound recycling,

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72 environmentally sound treatment, environmentally soun d disposal. There are at least three levels of planning involved in a comprehen sive Green manufacturing (waste minimization) program. They are strategic plan ning, formal action planning, integration and implementation planning. Management through leadership must make pollution prevention part of the organization’s policy and set explicit goals for reducing the volume and toxicity of waste streams. Managers must show commitment by impleme nting recommendations identified through assessments, evaluatio ns and pollution prevention teams and designate a pollution prevention coordinator who is responsible for facilitating effective implementation m onitoring and the evaluation of the program (i.e. facilitating self-managing poll ution prevention teams). Other ways that management can motivate pollution preventio n is to publicize success stories, recognize individual and collective accomplishme nts and train employees on waste generating impacts of their process. Further, management must lead improvement efforts both internally and externally to their organization. There is some argument as to the preferred order of ev ents during the goal setting process. The EMS approach states that Goals and objecti ves are established as soon as there is enough of an understandin g of the systems environmental aspects to set realistic goals for improve ment. Action plans are then formed to reach these goals. Under the quality m odel approach, goals are not set until after action plans are established. These goals are focused to each action plan and short term in nature. Short term foc used goals are considered by

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73 some to be the essence of continual improvement, as pr omoted by Dr. Edward Deming. (Deming, 1986) Others believe that stretch goals such as zero waste are st rong indications of the organization’s never-ending commitment to continuous e nvironmental improvement. Perhaps both schools of thought are correct After all, the process is iterative. Clearly there is a need for different levels of goals. Long term or even unachievable goals such as zero waste, establish a str ategic direction for the entire organization to rally around: A lighthou se in the distance guiding the organization through stormy seas. But, individual te ams need specific near term goals to focus their action plans around. This repetitio n of goals setting and action plans is the process of continuous improvement. I t takes an infinite number of iterations over time to reach zero waste. A s to which comes first, the action plan or the goals, it’s like the chicken and the eg g. It’s one thing to set goals, it’s quite another to make sure goals are being met by focusing on results Management must stay engaged and let everyone know that these goals are important to the organization by regu larly reviewing action plan status and achievement of goals. Management must also re alize that improvement teams often need help from management in achieving their goals. They must be open minded and supportive of improvemen t efforts if goals are to be met. Regular reviews are essential as a forum for all of these points. Ideally, management will include environmental improvement sta tus in their regular monthly operational reviews. This is a clear sign that these efforts are part of the

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74 normal mode of business and helps to institutionalize G reen thinking throughout the organization. The types of results that should be considered in a Gr een manufacturing program are not just the environmental ones. There s hould be financial improvements as well. “All environmental results can b e translated into financial results” (EPA, 2001). Money is the universal language of business, so if a company wants the support of upper management, financia l savings are critical. Pollution prevention opportunities should be based on true costs of waste management and clean-up. Determining true cost requir es a waste accounting system that tracks the types and amounts of waste. True cos ts include compliance, paperwork, reporting requirements, loss of pr oduction potential, cost of material found in the waste stream (i.e. purchase ma terial scrap), transportation, treatment, disposal, employee exposure risk, etc. Each organization should find the best way to account fo r true costs of impacting the environment. True costs of waste management should be allocated to the activities responsible for generating the waste in the f irst place, rather than to an amalgamated overhead. Without allocating costs, pollu tion prevention opportunities can be obscured by accounting practices that do not clearly identify the true cause. Additionally, companies should express the overall envir onmental health and safety improvement to and from employees, customers and suppliers as important results of their Green manufacturing effor ts. It is important that

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75 everyone involved in the pollution prevention progr am understand the benefits of the program. This will help motivate people to get involved. Some of the obvious benefits include reducing compliance costs, reducing worker exposure, and reducing inventories of hazardous materials that reduce risk of spill/releases. Less obvious, but very important is how pollution preve ntion can possibly decrease future Superfund and RCRA liabilities and fu ture tort liabilities, improving facility efficiency and product yields, enhanci ng organizational reputation and image. In terms of future considerati ons for companies, numerous states have enacted pollution prevention laws and more laws are on the drawing board. Wise companies will proactively star t to budget and implement pollution prevention strategies before state s edict such changes. Proper gathering of information and accurate analysis is essential in guiding the organization to solving the root causes of environment al problems. The old saying “if you don’t know where you are going, any p ath will get your there” is an illustration of this fact. All too often companies try to implement solutions without truly understanding the problems. More time should be spent gathering relevant data and analyzing this data to understand problems be fore they are solved. The term process management has a dual meaning regarding waste minimization. First it is important to properly man age the physical processes that generate waste. Secondly, the administrative processes that make up an environmental management system are also critical to sust ained waste minimization. The EMS approach to waste minimization strongly emphasizes

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76 that certain administrative processes are in place for en vironmental improvement to occur. All of the elements listed in this section, s uch as Goal Setting, and Employee involvement are all made up of processes and a re all part of the many processes essential to waste minimization. Higher levels of employee involvement translate directly to higher levels of waste reduction activity. There are opportunities in every function to prevent pollution before it occurs. Engineering can design products and pr ocesses that prevent pollution, purchasing can select materials that are less h azardous, production can improve handling and use of chemicals to prevent sp ills and accidents. Since few if any individuals in a manufacturing company have environmental knowledge, technical process knowledge and hands on experie nce of the process, the best approach is to have a cross-functional tea m working together toward pollution prevention. A challenge for the pol lution prevention manager is to get these different groups communicating in the same language and working together, given their busy schedules. Traditionally waste minimization programs focused inwa rd within the manufacturing company, but focusing on all interested parties can yield much greater results. The EMS and quality based approaches to waste minimization particularly emphasize the importance of collaborative relationships with customers, suppliers, regulatory agencies, and other stake holder. In recent years greater emphasis has been placed on minimizing th e “life-cycle” impacts of products. During this same time, manufacturing has beco me more global and

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77 horizontally integrated: Products are made of parts a nd sub-assemblies from all over the world. Reducing the life-cycle impacts of prod ucts requires strong collaborative relationships with all part in the exten ded supply/demand chain, and other stakeholders as well. EPA Voluntary Environmental Programs The leading environmental organization in the Unite d States is the US EPA. Often labeled an enemy of industry only concerned wit h “command and control” approach to waste management, the EPA is actually very progressive in developing and supporting environmental programs that simultaneously reduce waste and operating costs. The EPA is convinced that po llution prevention is the answer to present and future environmental problems. The agency has developed several voluntary programs meant to stimulat e the creative engine of industry towards devising innovative pollution prevent ion solutions. The following is a summary of the EPA’s existing programs that promote Green manufacturing in innovative ways. (EPA, 2001) Source Reduction Review Project As a short term goal, the Source Reduction Review Proje ct SRRP ensures that source reduction measures and multi-media issues are conside red as air, water, and hazardous waste standards affecting 17 industrial cat egories are developed. For the long term, the project tests different approac hes to provide a model for the regulatory development process throughout EPA.

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78 Pollution Prevention in Enforcement Settlement Policy EPA negotiators are strongly encouraged to incorporate pollution prevention conditions into settlements-both criminal and civil-invol ving private entities, federal facilities, and municipalities. Pollution Prevention Incentives for States Under the state prevention grant program, EPA has aw arded more than $25 million through fiscal year 1993. These grants help st ates to enhance innovative and results-oriented programs, implementing multimedi a prevention approaches and targeted high-risk high-priority areas. For exa mple, Tennessee was awarded $300,000 for its Waste Reduction Assistance Prog ram (WRAP). 33/50 Program This is a voluntary initiative to reduce toxic-waste gen eration from industrial sources. EPA targeted 17 chemicals for reduction of 33 pe rcent by the end of 1992 and 50 percent by the end of 1995. To date, mo re than 1,150 companies have signed up to participate, committing to more than 354 million pounds of reductions in toxic chemical emissions. Green Lights Program The first of EPA's market-driven, non-regulatory "gre en" programs, Green Lights encourages voluntary reductions in energy use through m ore efficient lighting technologies. More than 700 participants have agreed t o survey their facilities

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79 and, where possible, upgrade lighting efficiency in 90 percent of their square footage, within five years, Green Lights participants are saving more than 35,000 kilowatts annually, or $6.9 million, in electricity costs. Energy Star Computers Energy Star is a voluntary partnership between EPA an d the manufacturers that sell 60 percent of all desktop computers and 80 to 90 per cent of all laser printers in the United States. These companies are now introduci ng products that automatically "power down" to save energy when not in use. Consumers will easily recognize the more efficient systems, because they will be labeled with the EPA Energy Star logo. Design for the Environment (DfE) DfE is a cooperative effort between EPA and industry t o promote consideration of environmental impacts at the earliest stages of product design. Initial projects include designing a more environmentally conscious compute r workstation and funding research into alternative synthesis of importan t industrial chemical pathways. A new focus of the DfE program is a joint ef fort with the accounting and insurance professions to integrate environmental co nsiderations not capital budgeting and cost accounting systems.

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80 National Industrial Competitiveness through Efficiency National Industrial Competitiveness through Efficiency (Energy, Environment, Economics) (NICE 3 ) is administered jointly by EPA and the US Departme nt of Energy with matching state and industrial funds, the NI CE 3 grant program was provided $4.4 million through fiscal year 1993 to sup port new processes and equipment that reduce high-volume wastes in industry, conserve energy and energy-intensive feed stocks, and improve industrial cost-co mpetitiveness. The Toxic Release Inventory The Toxic Release Inventory (TRI) is EPA's compilation and public dissemination of the type and quantities of toxic chemicals companies are releasing to the environment, data that the companies must report annu ally. Pollution-Prevention Information Clearinghouse Pollution-Prevention Information Clearinghouse (PPIC ) makes information resources available to the public and to industry to fa cilitate the adoption of methods, processes, and technologies for pollution preve ntion. Clean Technologies Program The Clean Technologies program (Clean-Tech) is a broadbased, applied research program focused on improving US and world-wide environmental quality, efficiency, and economic competitiveness through the development and application of innovative pollution prevention method s and clean technologies.

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81 Under this program the EPA's Office of Research and Dev elopment creates and disseminates a wide variety of technical documents on pol lution prevention. The EPA works in partnership with other agencies, universit ies, and industry groups to develop and evaluate cleaner technologies and proce sses; and provides technical assistance to various industries, particularly tho se composed mostly of small businesses. Ciambrone Model Ciambrone (1996) identified ten essential elements of a successful waste minimization program. He indicated that there had t o be genuine documented management commitment for all to see. Employee’s ide as must receive consideration and hopefully implementation. There had to be long-term continuity of waste minimization strategy, or as Deming said ‘consta ncy of purpose’.(Deming, 1986) The waste minimization progr am has to be clear and simple. Careful initial preparation is required to a ssure successful implementation. The waste minimization program has t o be viewed as job enhancing and not job threatening. Leadership of pro gram implementation and maintenance has to come from line managers and not sim ply from the environmental group. Office personnel, factory empl oyees and design engineers must all be involved in program design and i mplementation. The waste minimization program must be seen as a new way o f doing business versus a fad. There must be regular and purposeful sessio ns, where progress is reviewed and ideas are exchanged (brainstorming).

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82 Ciambrone (1996) offers the following best practices for reducing environmental waste. Interestingly, included in this list are distinct ly Lean best practices: Reducing solid (non-hazardous) waste by x%/year Reducing hazardous waste Reducing the generation of priority wastes (TRI 300 ch emicals) Reducing production scrap/rework Increasing the use of flexible tooling Reducing set-up time Use of environmental check list in product design Use of Green index rating system on materials and proces ses for product design and purchasing Dillon and Fischer Model A field research study of U.S. chemical companies conclu ded that higherperforming environmental companies tended to have ex plicit objectives, longrange planning, performance-based evaluations, proact ive corporate cultures, formalized control, measurement, and reward programs. The President’s Council on Environmental Quality created a framework f or pollution prevention. Progress along these steps can be used as a tool to measu re the success of an environmental management program. Categories of best practices for this framework include: Management commitment Quality action teams Training Determining environmental impact Selecting environmental projects Implementing improvement projects

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83 Measuring results Standardize the improvements GEMI Model The Global Environmental Management Initiative (GEM I) established and environmental self-assessment program based on the 16 pr inciples from the Charter for Sustainable Development. The GEMI princi ples are more specific and action oriented than the original 16 principles fr om the Charter for Sustainable Development. These environmental best pr actices include: (GEMI, 2000) Recognize environmental management as a top corporat e priority Integrate environmental programs into each business Continually improve environmental programs Educate employees Assess environmental impacts before starting projects Minimize the impact of products and services Advise customers in the safe handling of products Operate facilities with minimal impact Research the environmental impacts of operations and w ays to reduce these impacts Change processes to prevent serious environmental harm Promote improved environmental activities of contract ors Prepare for emergencies Transfer environmentally sound technologies Contribute to public education and policy developmen t Foster openness with employees and the public Measure and report environmental performance

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84 Responsible Care Program Members of the Chemical Manufacturers Association (CMA ) are evaluated by the Responsible Care program. The members of the CMA acc ount for more than ninety percent of the basic industrial chemicals produced in the US. The Responsible Care program developed six codes of environm ental management best practices on the following topics; Pollution prevent ion, Community awareness and emergency response, Distribution, Process saf ety, Employee health and safety, Product stewardship. Within the Pol lution Prevention code, CMA has identified the following best practices that Gre en manufacturers should implement: Commit the organization Inventory wastes and releases Evaluate potential impacts Educate and listen to employees and the public Establish a reduction plan, goals and priorities Measure progress Communicate progress Integrate reduction concepts While the Environmental Management System is an essent ial aspect of a company wide Green manufacturing program, it was desig ned for general application to all industries. As a result it cannot pr escribe specific practices known to reduce environmental waste in manufacturing o perations. Criticism of ISO14001 is similar to the criticism surrounding ISO9001 in that they both lack the “teeth” to truly drive improvement.

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85 However, they create a framework of management commit ment, policies and procedures that foster the implementation of best practi ces that do actually reduce waste, or improve quality in the case of ISO9000 So, in addition to the management system level of Green manufacturing strateg y, there should be best practices that truly reduce environmental waste in the m anufacturing process. Once again, manufacturers interested in these best pra ctices have to look no further than the U.S. EPA for guidance. EPA Guide to Pollution Prevention In the EPA Guide to Pollution Prevention (EPA, 2001 ), several models of Green manufacturing best practices are offered. Companies who implement a pollution prevention (P2) program see the following improvemen ts: Reduced operating costs Improved worker safety Reduced compliance costs Increased productivity Increased environmental protection Reduced exposure to future liability costs Continual environmental improvement Resource conservation (EPA, 2001) Generally speaking, the EPA P2 guide recommends some pr eliminary work to set the stage for the pollution prevention program. The guide indicates the importance of a management system to drive waste reducti on activity to include the establishment of a vision statement, a mission statem ent, metrics and goals,

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86 and the use of environmental indicators. A vision state ment represents what the organization expects or the desired outcome of the pol lution prevention program. A mission statement identifies what the organization ne eds to accomplish in the key areas that affect pollution prevention. Metrics and goals are used to set the direction of improvement and measure progress. Indicato rs measure progress along the way. Another important element of a pollution prevention program is to establish a set of core values that are used as guiding principles of co nduct during the implementation of the Green manufacturing system. Th e core set of values is specific to each company, based on the company beliefs and ethical constructs. Some examples of core values appropriate to a Green ma nufacturing system are as follows. (EPA, 2001) Interested party-driven approach: Understanding who environmental stakeholders are and what they expect from the Green manufacturing system. Leadership: Everyone in authority must set an example and conduct themselves and their business dealings in an environmentally conscio us manner. Continuous improvement : The Green manufacturing syst em is a living system that will die without continued involvement toward t he unachievable goal of zero waste. Valuing employees: The most important resource to any company in meeting its objectives is its people. This is no different for impr oving environmental quality. Design environmental waste reduction into products and processes: An ounce of prevention is worth a pound of cure. Maintain a long-range outlook: Green manufacturing t akes a long term commitment. The program should not be abandoned if i mmediate results are not attained. Management by fact: Measure things accurately and let t he facts guide behavior. Partnership development: Developing partnerships betw een different functional departments within the corporation and with externa l stakeholders is essential to efficient and continual environmental improvement.

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87 Corporate responsibility and citizenship: A green manu facturer is a good corporate citizen always concerned with business ethics and the protection of public health, safety and the environment. Fast response: Green manufacturers must always keep abrea st of environmental opportunities and challenges, such as changing regulati ons. The ability to respond quickly to these changes keeps the company one step ahead of the competition. (EPA, 2001) The EPA also offers suggestion on specific tools for waste minimization. Coincidentally, the tools they recommend are often use d in TQM and Lean manufacturing programs. These tools are examples of ho w a Lean or Green company can apply its waste minimization tools toward re ducing all forms of waste. Specifically, the EPA recommends the following: Provide top management support: Without management support there can be no waste minimization program. Management must set clear objectives and provide resources and active leadership. Process Mapping: The process map identifies in a flow cha rt form the stages of the process. Included in these can be inputs to the proce ss at each stage (material, energy, hazardous solvents, etc.) and process outputs (products, and wasteful by-products). Determining costs of loss: It is essential to quantify t he cost of waste in order to justify expenditures to minimize the waste. Several costs that should be considered include the raw material that is wasted, tre atment costs, disposal costs, clean-up costs, and when possible potential liabil ity costs. Selecting waste minimization opportunities: This is a p rocess of prioritization, focusing on opportunities with the greatest opportuni ty for improvement. Apply the Pareto (80:20) rule. Encourage technology transfer: Learn from the experi ences of others. Take advantage of partnerships, other facilities within the company and trade organizations to obtain new ideas for waste minimizati on. Perform periodic waste minimization assessments : Make sur e that solutions are still in effect and that process changes are accounted for. Conduct program evaluations: Keep the Green manufactu ring program alive by conducting regular reviews and refocusing the program as it evolves. (EPA, 2001)

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88 Design for the Environment In addition to the waste minimization/pollution prev ention models summarized above, there is a distinct body of research on the subje ct of environmentally conscious design, known as Design for the Environment (DF E). The premise of Design for the Environment is to design a product with minimum impact on the environment. It is during the design phase that almost all potential environmental effects of the product are determined. For example, the raw material the product requires for its manufacture is determined at this stage. The product design dictates how the product is manufactured and even the n eed for hazardous materials in the manufacturing process. The recyclability of the product is also determined at this stage. Product reliability that is designed into the product also determines product longevity. The functionality of th e product, which determines the product’s impact on the environment during its usef ul life is also determined at the design stage. The following Design for Environ ment best practices help to minimize a product’s environmental impact during the d esign phase. (EPA, 2001) It is important when designing a product to assure that the product is modular, meaning that it can be easily disassembled for recycling. Modularity also means that subassemblies are shared with different product, so that subassemblies can be refurbished and used in other products. Modularity also means that rather than fully replacing an item when it becomes obsolete, it is possible to simple upgrade a few of the subassemblies and keep the rest of the unit. Computers and peripherals offer great opportunities for modular design. (EPA, 2001)

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89 Minimize the different number of materials (e.g. simi lar grade plastics). Specify recycled, rather than virgin materials or at least a bl end. Specify materials that can be recycled. Minimize toxicity of materials, no sign ificant toxicity should be allowed. This should include both direct (product) and indirect (process) materials. This implies both product and process design changes to include these materials. All plastic part should be marked with ISO identifying marks, size, geometry and function permitting. This helps in the sorting and recycling of these materials. (EPA, 2001) Product should be easy to assemble and disassemble. This p romotes efficient re-manufacturing and separation of materials for recycli ng. Any surface treatment required should be compatible to the recyclin g of the base product. Labeling, such as UL should be molded-in rather than u sing stickers, as not to degrade recycling. (EPA, 2001) Subassemblies should be modular, making separation from the main unit easy, for repair and recycling. Parts prone to failure shoul d be placed in accessible locations on the subassembly to facilitate repair. Sho uld facilitate product upgrades in a modular manner rather than replacing en tire unit. For example, replacing the CPU module of a computer rather than th e entire mother-board or entire PC, just because a new microprocessor makes the ol d one obsolete. (EPA, 2001)

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90 Progressive companies include the following tactics in thei r DfE programs: Eliminate CFC cleaning in favor of aqueous or no clea n solutions Hazardous chemicals are replaced with more benign chemica ls Material reduction, reuse, and recycling are all consid ered in the design phase Products are designed for ease of disassembly or remanufa cturing Generic parts are designed that are easily removed an d can be reused in a variety of products (modularity) Improve handling and containment of chemicals to preve nt evaporation or spills/leaks in production operations (EPA, 2001) One of the major aspects of a successful DfE program is th e organization assigned to this effort. No single engineering disciplin e contains the knowledge to achieve true Green Manufacturing, which requires e valuating the environmental impact of the entire product life cycle. This group would possess the knowledge necessary to fully account for the enviro nmental impact of product and process in terms of present and future environmental regulations. Environmental engineers are trained to manage waste st reams. They lack knowledge of process and product design. Likewise product and process design engineers lack knowledge on environmental regulations a nd impact. If these engineers are teamed together, they can design products that minimize waste and cost simultaneously. Environmental engineers ca n specify environmentally benign or recycled materials that desi gn engineers can use in the product and process development; thereby preventi ng waste, and the associated waste management costs, from ever occurring. If done properly, management should see a direct pay back to this “concurr ent engineering”

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91 approach to Green Manufacturing. Several Green manu facturing leaders include the following aspects in their DFE programs: (EPA, 2001 ) AT&T maintains a highly visible yet straightforward me thodology for DfE avoiding complicated LCA analysis. They integrate EH&S into all major business considerations. Management believes that DfE provides a good cost benefit ration and is a competitive tool. Accounting practices a llocate costs properly to the activity generating the waste, rather than genera l overhead. They use DfE to assess suppliers and alliance partners and make trade-offs as opposed to mandates to suppliers regarding green products. They bl end together environmental protection and business growth. IBM views DfE as a highly competitive tool when successf ully integrated into engineering and operations. They Create DfE concept and general guidance documents at corporate level. Business units and operati ons are responsible for DFE deployment and impact assessment. IBM views DfE a boundary condition to product development. Xerox’s ARM (Asset Recycling Management) organization is credited with saving more than $50 million in materials and logistics in 12 months. Thirty people are responsible for deploying ARM within design groups. AR M is a profit and loss organization. Embedding DfE activities in operations r esolved conflicts between divisions and the EH&S organization.

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92 Total Cost Accounting One of the reasons manufacturers have been slow to ado pt Green manufacturing systems is because waste management costs are often not dire ctly associated with the cost to manufacture a product. Waste manageme nt costs are hidden in the overhead structure, making it difficult to justify savings to a specific manufacturing process by investing in clean technology. An approach known as Total Cost Accounting (TCA) is being implemented in pro gressive companies that directly ties waste management costs to the costs of the process and/or product producing the waste. This fundamental change in accounting calculations is the n ecessary stimulus for management to recognize the costs of wasteful processes a nd the benefits of clean technology investment. Business decisions will revol ve around a central goal of "zero waste" as an ideal philosophy for busine ss, much like zero defects is the appropriate goal for quality. Total Cost Accoun ting (TCA) encompasses four elements: cost inventory, cost allocation, time hori zon, and financial indicators.(EPA, 2001) In evaluating the profitability of prevention invest ments, forms often exclude costs that rightfully belong in the analysis. Cost inventory is a method to resolve this problem. Accurate costing for prevention has obvious b enefits for sound business management, but in practice it is often more c omplicated than it first appears. Depending on where the usage is measured the results will very. For example, is the amount based on what was purchased? Is measured on how

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93 many products were produced multiplied by the quantit y per unit, plus a waste factor? The answer is using both techniques to get a fu ll picture of how much of the purchased material was used. Closely coupled with "how much" is the question, "by wh at". In other words, which processes or products are responsible for hazardous m aterials used and wastes generated. Cost allocation is a method to answer which processes generate the wastes. To answer this, the firm must assign figures to specific processes or products. Doing so requires a precise picture of how materials flow into, through, and out of the manufacturing process. This tracking is often refereed to as "mass balance". When business looks at a potential prevention investment, it must ask the question: How long will it take to show profitability ? Proper use of time horizons can answer this question. Prevention investments often t ake time to show profits, particularly when profitability is based on suc h items as future liability avoidance, recurrent savings due to waste avoidance, an d revenue growth owing to market development of environmentally sound product s. A TCA approach takes future benefits into account by considering at lea st a five-year time horizon, whenever feasible. Financial indicators for pollution prevention projects should capture all the elements discussed above. Net Present Value (NPV) meets this criteria and Internal Rate of Return (IRR). One measure that doe s not, though it still may be used as a project screening tool, is simple payback.

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94 TCA helps justify pollution prevention alternatives. The EPA’s Guide to Pollution Prevention and Waste Minimization (2001) helps compan ies identify the full cost of hazardous materials and hazardous waste management. It provides NPV, IRR, and annualized cost savings calculations for polluti on prevention projects. The manual identifies four levels of cost types: Usual costs equipment, materials, labor Hidden costs monitoring paper work, permit requirem ents Liability costs future liabilities, penalties and fin es Less tangible costs corporate image, community relation s, consumer response Some interesting discovers occur when Total Cost Accounting is applied. National Association of Plastic Container Recovery concl uded that after analysis from raw material extraction through recycling to disposal PET plastics was more energy efficient than glass or aluminum contain ers. Another study indicated that plastic bags were far superior to paper b ags. ECO balance sheet: Return on environmental investment. The eco-balance sheet is a way to integrate environmental concerns into daily decision maki ng, transitioning from cost avoidance to environmental profitability. Better understanding total costs and taking active steps t o eliminate present and future costs of waste will help a company’s competitiven ess now and in the future. Progressive companies see the benefits of factor ing in present and downstream environmental costs into their cost accounting systems, incentives for this approach include:

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95 Traditional, environmental costs had been assigned to general overhead, since they were relatively low and the cost of tracking re latively high. These allocation methods are becoming inappropriate due to decreased re porting and compliance costs and soaring environmental compliance regulations. Adopting proper environmental compliance practices can d ecrease pollutant levels and save money. Penalties and law suits can be m ore costly for those not complying with federal and state regulations. Correctly tracing and allocating environmental costs in volves properly identifying cost drivers, which imply cause-and-effect relationships bet ween assigned costs and allocation bases, and identifying nonlinear cost re lationships to avoid distorted cost estimates. Strategies for managing environmental costs involve giving mangers appropriate incentives for environmental compliance costs, because successfu l financing, sound investment decisions, and competitive advantage pri marily rely on the accuracy of data supplied by management. (EPA, 2001) Scallon and Sten Model Now that an overview of Green manufacturing model co mponents is complete, it is important to understand the process of Green manufac turing system diffusion and the correlation between system components. Lean man ufacturing studies indicated that companies implement Lean best practices st arting with management commitment, production operations, support functions and then outward to the extended supply chain. Is this true wit h Green manufacturing best practice deployment as well? The following study sheds light on the process of Green best practice deployment for a small group of kno wn Green companies in the pacific northwest of the USA. The two studies that follow focus more on the interrelationship of Green manufacturing system compo nents. A study performed by Scallon and Sten (1997) looked at the environmental behavior of 36 companies in the Pacific Northwest of th e United States. The companies were selected based on their involvement in v oluntary environmental

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96 programs, and reputation as environmental leaders in their industry. Information was gathered by five people (2+ person teams) doing fa ce to face interviews, 45 min. + each, with at least one person from the company. Information is of a qualitative nature. Companies were grouped by size: L arge companies had over $1 billion in sales. Medium sized companies had sales gre ater than $75 million. Small companies had less than $75million in sales or less than 1,000 employees. Companies were grouped into four categories of enviro nmental behavior (Compliance, Alignment Expansion, and Integration ) and are described below. Compliance Group The Compliance group, consisting of six companies, focuse d on maintaining a strong compliance record. They try to keep up and comp ly with regulations. They are primarily reactive, either to regulations or to specific customer requirements. They participate in environmental act ivities that are either required by law or are least-cost alternatives. They have the primary motivation to avoid problems, stay out of trouble, or stay in business. Atti tudes reflective of this group are: “Any other way would have required more changes; Our recycling program grew out of a disposal problem, We are expecti ng a wake-up call, a big law suit.” (Scallon and Sten, 1997)

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97 Figure 7. Compliance Group Environmental activity is confined to the manufacturin g process and regulations that influence them. Recycling programs are the primar y facilities-related activities, and perhaps a carpool or similar employee pr ogram is in place. The only customer specific areas addressed are those dictated by the customer. (Scallon and Sten, 1997) Alignment Group The Alignment group, consisting of 10 companies, recogni zes that environmental issues and trends can open up new cost savings areas and ma rket opportunities. These companies are beginning to align their business ob jectives with their environmental objectives. The idea that being enviro nmentally responsible is the right thing to do also comes to light in Group II. However, behavior in relation to environmental issues is still driven more from a desire t o minimize risks and avoid compliance problems. By setting their own target s, these companies see Regulatory Agency Customers Employees Facilities Manufacturing Process

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98 that they can minimize planning risk and their vulnera bility to changing regulations within their planning horizon. These comp anies: Try to keep ahead of regulations though early compli ance and often participate in voluntary compliance programs. Primarily address environmental issues that relate to o r that are extensions of compliance issues, business survival issues or changing market co nditions. Recognize that addressing environmental issues can be pr ofitable, yet are generally unwilling to make significant investments in non-mandatory environmental activities that do not have expected mea surable returns. Have motivations that include a desire to be ahead of compliance issues, potential economic benefits, and being responsive to chan ges in market demand. (Scallon and Sten, 1997) Attitudes reflective of this group are: Compliance is th e focus unless savings are involved. Most environmental activities are performe d because they are driven by compliance forces. They recognize the value added co mponent of environmental improvement, but compliance has been th e main thing. These companies are sensitive to the people who work here an d related environmental health and safety concerns, so they try to go beyond com pliance. (Scallon and Sten, 1997)

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99 Figure 8. Alignment Group Companies in this group recognize changing customer deman d and the related potential opportunities, and new or redesigned produ cts and services are being developed. Some community-related activities such as hig hway clean-up programs may be in place, and new cost effective recyclin g service suppliers may be identified to replace costly hazardous materia l disposal. (Scallon and Sten, 1997) Expansion Group The Expansion group, consisting of 14 companies, is proact ive in nature, and search for opportunities to improve environmental impr ovement. In other words, an environmental ethic takes precedent over compliance c oncerns. Companies Facilities Regulatory Agencies Customers Employees Manufacturing Process Community Suppliers

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100 in this group see environment and even regulations as opportunities. Doing the right thing environmentally is expected behavior. Se eking opportunities for environmentally conscious behavior is performed througho ut the organization and enterprise (outside the company). Environmental issues take a higher priority and are addressed at a hire level in the or ganization. These companies involve many key stakeholders in their environmental s trategy. In general these companies: Work to influence regulations in a positive way Are characterized by the development and implementat ion of programs that go beyond areas of compliance, survival and market changes. Have a wider range of environmental activities, which include programs that involve customers, suppliers, and the community Address facilities-related environmental issues in addit ion to manufacturing process issues. Often have comprehensive waste minimization or pollut ion prevention programs Have elements of an environmental management system, and a willingness to experiment continually (a.k.a. continuous improvement) (Scallon and Sten, 1997)

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101 Figure 9. Expansion Group A greater emphasis is put on employee and supplier ori ented initiatives, including the use of employee ‘green teams’ to address e nvironmental problems and the creation of supplier programs to re-evaluate p roduct inputs and reduce or redesign packaging. Product take-back programs are a g ood example. Community involvement initiatives and facilities-relat ed energy-efficiency programs are also significant and well established compon ents of the environmental efforts of this group. Elements of an e nvironmental management system are in place. (Scallon and Sten, 1997) Integration Group Companies in the Integration group have developed an organization culture and internalized the perception that environmental issues p rovide opportunities. Facilities Regulatory Agencies Customers Employees Manufacturing Process Community Suppliers

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102 Some companies in this category developed due to a stro ng environmental ethic. Others have developed environmental programs d ue to a respect to changing political, market and economic concerns about th e environment. Either way, decisions are based on environmental opport unities and upholding an environmental ethic. This group has begun to insti tutionalize its expanded definition of the role of environmental issues in the organization. These companies: See the value of actively addressing environmental i ssues as an integral part of the operation of their business Approach environmental issues strategically Have a structure in place to generate new project ide as, address different area of concern, and look at issues of interest to a wide range of relevant constituencies Recognize the role of employee involvement and corpo rate culture in being an environmentally-responsive company Recognize the benefits of environmental activities, b ut do not require individual environmental initiatives to provide a return or bre ak even (Scallon and Sten, 1997) Attitudes reflective of this group are: The nature of our business instills in us the need to protect the environment. It is up to us to u se rigor and common sense to measure what is really at stake. Environment is integ ral to our business and our environmental activities emanate from our value system We are working to incorporate an environmental ethic into all decision-ma king and new products and product lines. (Scallon and Sten, 1997)

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103 Figure 10. Integration Group These companies take their programs a step further by addressing the concerns of shareholders, which often involves the publication of environmental progress reports. They institute systems and strategies that ensur e environmental concerns are integrated into all aspects of the company’s b usiness. (Scallon and Sten, 1997) The Scallon and Sten study shows that as a company evolv es from Compliance to Integration the scope of environmental activities ex pands to reach a broader group of stakeholders. Similar results were found in th e Panizzolo (1998) study of Lean manufacturers whereby companies typically began Lean implementation on the factory floor and then expanded outward to su pport functions and ultimately to customers and suppliers. Therefore, resear ch indicates that, as companies’ appetites for reducing waste increases, they see k out untapped Facilities Regulatory Agencies Customers Employees Manufacturing Process Community Suppliers Shareholders

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104 opportunities both internally and externally. Thi s logic supports the hypothesis submitted in this study that as a company becomes Leaner it will seek out new opportunities to reduce waste, which should lead it to implementing Green best practices. And, as a company becomes Greener it will a lso seek out new opportunities to reduce waste, which will lead them t o implementing Lean best practices. Thus, we should see a correlation between the extent to which a company implements Lean and Green manufacturing best p ractices. (Scallon and Sten, 1997) The Russo Model Michael Russo from The University of Oregon observed a rapid increase in annual ISO14001 registrations over the past several ye ars. Curious as to what this might mean in terms of improved environmental pe rformance, he conducted a literature review. He realized that there had be en no thorough analysis of the environmental impact of ISO14001 on emissions. He then posed the research question: Does ISO14001 certification actually lead to environmental improvements? He determined that this was a very impo rtant question given the recent acceleration in ISO14001 certification worldwide. If ISO14001 has a positive impact on environmental performance, then t his would be magnified by the number of firms becoming registered.

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105 The main hypothesis for the Russo study was: Facilities tha t receive ISO 14001 registration will experience environmental performance improvements (as measured by the EPA’s Toxic Release Inventory (TRI) da ta). The findings for the Russo study include: For the entire sample, the presence of an EMS (ISO140 01 or otherwise) was a significant predictor of improved toxic emissions perform ance. Within the sample of facilities with emissions above TRI reporting thresholds, ISO 14001 registration significantly reduced subsequent toxic emissions. The Russo study provides strong evidence that there is a co rrelation between a Green Management System and Green results. It indicat es when management formally commits itself and the organization to reduce environmental waste, it happens. If it can be shown that as a manufacturing pl ant’s level Leanness correlates positively to its certification to ISO14001, then it can be logically inferred from Russo’s study that the plant is also exper iencing reduced TRI emissions. The studies methodology is summarized below a nd a more complete description is in Appendix A. Russo Methodology Sample: The study explored the adoption and impact of ISO 140 01 within a sample of electronics plants, broadly defined. The plant, or faci lity, was chosen as the unit of analysis for two reasons. First, it is facilities—not firm s—that are registered under ISO 14001. The ISO 14001 registration process was desig ned specifically to operate at this level, as it was patterned after the ISO 9000 quality standards (Tabor, Stanwick, and Uzumeri, 1996). Second, data wi thin the Toxic Release Inventory is organized at the plant level, and aggre gation beyond that level creates imprecision. In order to balance the need for a viabl e sample size with comparable industry environments, six segments of the electronics in dustry were selected for analysis: SIC 3571 (Electronic computers), SIC 3651 (Hou sehold audio and video

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106 equipment), SIC 3661 (Telephone and telegraph equip ment, SIC 3671 (Electronic tubes), SIC 3672 (Printed circuit boards), and SIC 367 4 (Semiconductors and related devices). Thus, there is a high degree of commo nality to the sample, responding to criticism of studies with samples that are too dispersed (Griffin and Mahon, 1997). The numbers of observations for the two studies are shown in Table 1. I used as the population all facilities in these seg ments where manufacturing took place and which employed at least 100 persons. Data fur nished by Dun and Bradstreet listed 1104 such establishments. A university survey research center randomly selected and contacted facilities from the set of 1104 facilities in early 2000. A tota l sample of 316 facilities provided interview data. Given that 95 of the original 1104 sites were not actually manufacturing sites or were used for other lines of bu siness, the interviewed sample consisted of 31.3% of the population. All facilities we re contacted multiple times, and the main reason for non-response was inability to g et to the respondent either due to absence or having an answering machine respond to all interview attempts. Refusals by respondents were a relatively minor occurren ce, at roughly 5% of nonrespondents. When contacting firms, in order to avoid biases, interviewers did not leave phone messages, as this might have affected the ch ance of a return phone call. The level of success we enjoyed might be due to t he relative lack of knowledge about ISO 14001, the desire of environmental manager s to receive copies of the results of this study, or a desire to improve the netwo rk among environmental professionals. In early 2001, a second wave of surveys w as sent to firms that had not yet registered to ISO 14001 to ascertain whether o r not they had done so. Of the 316 facilities that were contacted, a number wa s dropped from each analysis because the interviewee did not provide inform ation on all variables that were used in analyses. In addition, for the study of toxic releases, an additional 196 facilities had to be handled differently because they d id not produce enough toxic emissions for any effluent to report to the Environmen tal Protection Agency (This raises the issue of selection bias, with which is explicitly a ddressed below). Table 1 provides a summary of the available facilities and obser vations for the adoption study and emissions study, organized by Standard Indust rial Classification area. Study Period. I used the years 1996 through 2000 for the study of ISO 14001 adoptions. Although the ISO 14001 standards were fin alized in late 1996, their general nature was well known prior to that point, a nd in fact several respondents claimed to have “registered” earlier in 1996. This i s feasible, since the drafts of ISO 14001 were available by 1995 (Epstein, 1995). For the emissions study, as toxic emissions data is only available through 1999, that yea r is the last one used in that analysis. Melnyk, Stroufe, Calantone Model A study conducted by Melnyk, Stoufe and Calantone, in 2 002 explored the effect Environmental Management Systems (especially ISO14001 EMS standard) have

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107 on the implementation of “environmental options” (a. k.a. Green Waste Reducing Techniques) and, interestingly enough, the effect of a formal EMS on “Operations performance” described as Lead time, Quality, and Cost (a.k.a. Lean Results). This is an interesting study in that it looks directly at two of the main correlations is the research model, the correlation between GMS an d GWRT, and GMS and LR. The methodology developed for this study is very applicable to our research model as well. For completeness, relevant excerpts from the Melnyk et. al. study are included below: Melnyk Abstract There has been an increase in interest towards corporat e activities aimed at reducing or eliminating the waste created during the p roduction, use and/or disposal of the firm’s products. Prior research has focused on t he need for such activities, while current research tries to identify those component s that encourage or discourage such activities. As a result of the introductio n of ISO 14001, attention has turned to corporate environmental management system s (EMS). The underlying assumption is that such as system is critical t o a firm’s ability to reduce waste and pollution while simultaneously improving ove rall performance. This study evaluates this assumption. Drawing on data provided by survey of North American managers, their attitudes toward EMS and ISO 14001, this study assesses the relative effects of having a formal but uncertified E MS perceive impacts well beyond pollution abatement and see a critical positive impact on many dimensions of operations performance. The results also show that firm s having gone through EMS certification experience greater impact on performance t hat do firms that have not certified their EMS Additionally, experience with these systems overtime ha s a greater impact on the selection and use of environmenta l options. These results demonstrate the need for further investigation into E MS, the environmental options a firm chooses, and the direct and indirect relationships between these systems and performance. (Melnyk et. al., 2003) Melnyk Hypotheses Hypothesis 1: Performance is lowest when EMS is not prese nt, intermediate when EMS is present but not ISO14001 certified, highest when EMS is present and ISO 14001 certified.

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108 Hypothesis 2: Use of environmental options are lowest when a formal EMS is not present, intermediate when a formal EMS is present bu t not ISO 14001 certified, and highest when a formal EMS is present and ISO 14001 cert ified. Melnyk Methodology A survey was used to collect data for this study. The surv ey gathered data on the environmental activities, the state of the firms EMS, and the effects on environmental and corporate performance. Mailing list s of 5000 names each were obtained from the National Association of Purchasing Ma nagement, American Production and Inventory Society, and one anonymous gr oup, with duplications eliminated. The organizations were asked to specifical ly provide names of managers who worked in manufacturing (SIC code range 20-39). The usable responses totaled 1510, for response rate of 10.35%. Independent variables: EMS: State of the EMS SALES: To determine resources available to the firm to eith er help implement a formal EMS and/or to help implement Environmental o ptions. YEARS: Captures the age of the EMS PUBLIC: Company is either public traded or privately owned Controls: SIC Codes: To ensure that respondents were manufacturing firms. Table 6. Melnyk et al Statistics INDEPENDENT VARIABLE LEVEL MEANING NUMBER PERCENTAGE EMS 1 No formal EMS 591 50.9 EMS 2 Formal EMS 475 40.9 EMS 3 ISO 14001 Certified 96 8.3 SALES 1 First Quartile Sales 335 30.9 SALES 2 Second Quartile Sales 256 23.6 SALES 3 Third Quartile Sales 254 23.4 SALES 4 Forth Quartile Sales 240 22.1 PUBLIC 0 Privately held 628 51.4 PUBLIC 1 Publicly held 594 48.6 YEARS Continuous 1055 100

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109 Table 6. (Continued) DEPENDNENT VARIABLE LABEL N MEAN S.D. Environmental activities within your plant have: Significantly reduced overall costs ACTCOST 1142 3.35 2.57 Significantly reduced lead times ACTLT 1143 2.71 2.28 Significantly improved product quality ACTQUAL 114 4 3.24 2.53 Significantly improved its position in the marketp lace ACTPOS 1140 3.48 2.70 Helped enhance reputation of company ACTREP 1144 4.85 3.09 Helped company design/develop better products ACTP RODS 1144 3.60 2.77 Significantly reduced waste within production proc ess ACTWPROD 1144 4.73 2.99 Significantly reduced waste in equipment selection ACTWEQIP 1133 4.02 2.79 Had benefits that outweighed any cost incurred ACT BENE 1138 4.21 2.83 Improved sales opportunities internationally ACTIN TER 1133 3.73 2.89 To what extent are the following environmental options considered in your plant: Product redesign OPTPROD 1163 4.99 3.07 Process redesign OPTPROC 1166 5.95 2.91 Disassembly OPTDIS 1155 4.03 3.02 Substitution OPTSUB 1163 6.02 3.05 Reduce OPTREDUC 1160 5.82 3.03 Recycle OPTRECYC 1165 5.48 3.19 Rebuild OPTREBLD 1153 4.80 3.21 Remanufacture OPTREMAN 1148 4.16 3.12 Consume Internally OPTCONSM 1163 3.66 2.99 Prolong Use OPTPROLN 1154 5.01 3.98 Returnable Packaging OPTREPCK 1162 5.81 3.23 Spread risks OPTSPRED 1153 4.44 2.89 Create a market for waste products OPTCREAT 1156 4.24 3.07 Waste segregation OPTSEG 1161 5.83 3.05 Relocation OPTRELOC 1153 3.30 2.85 Alliances OPTALL 1154 4.96 3.05 Melnyk Findings Regarding hypothesis I, the study indicates that corpor ate performance is strongly affected by the presence of a formal EMS and s trongly influenced by a formal ISO14001 certified EMS. The significant variab les include ACTCOST, ACTLT, ACPOS, ACTREP, ACTPRODS, ACTBENE, and ACTINT ER. One explanation of these findings supported by (Russo and F outs, 1997) is that the EMS provides firms with specialized information of cri tical functions. These systems and functions are necessary for personnel to reduce pollution and improve overall performance. Without an EMS the fir m may have no other method of obtaining this information, and therefore is oblivious to the opportunities to reduce environmental waste. Also, th e EMS helps to publicize throughout the company efforts to reduce pollution an d the effects on operating performance, through its formal review process. In thi s way an EMS serves as a “clearinghouse” of environmental waste reducing efforts of the firm, promoting awareness of environmental activities.

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110 Regarding hypothesis II, For the option variables, the overall model was significant for every environmentally dependent varia ble. Furthermore, EMS2 and EMS3 were again found to have positive effect and significant on the use of all 16 options. Additionally, the differences between the two stages of a formal EMS (EMS2 – EMS3) was significant in the use of only 6 of the 16 options. (Melnyk et. al., 2003) Lean and Green Manufacturing Studies and Models Introduction A small number of scholarly studies have investigated th e relationship between Lean and Green manufacturing systems (Florida, 1996; Ro thenberg, 2001; King, Lenox, 2001; EPA, 2003). These studies show a positiv e relationship between Lean and Green. The Rothenberg study shows that Lean companies have better environmental performance and embrace environmental waste minimization more so than non-lean companies. The Florida study id entified some common best practices between Lean and Green management systems (e.g. management commitment, teams, new process technology, in novative product design, and supply chain management). The King, Lenox study finds that companies with low inventories of hazardous materials an d who are ISO9001 certified have lower toxic emissions than companies with higher inventories and are not ISO9001 certified. Each of these studies shows correlation between some elements of a Green manufacturing system and some asp ects of a Lean manufacturing system. The Florida study (1996) found that progressive companies applied a dvanced management practices (e.g. management commitment, team s, new process technology, innovative product design, supply chain mana gement) toward

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111 minimizing environmental waste. Dr. Florida indicate d that these techniques are associated with both Lean and Green manufacturing systems. “Advanced manufacturing facilities, such as those organized under the principles of lean production, draw on the same underlying principles – a dedication to productivity improvement, quality, cost reduction, and continuous im provement, and technology innovation – that underlie environmental innovation.” (Florida, 1996) The Rothenberg study (2001) focused on the automotive industry, known for its leadership in Lean manufacturing implementation. Th e study shows that Lean manufacturers are more energy efficient than non-lean manufacturers. The study did not show significant reductions in emissions in Lean companies, which may in part be due to the fact that Lean companies te nd to focus on source reduction rather than end-of-pipe environmental solut ions. This approach is consistent with the Lean philosophy of eliminating non -value added activities and stopping problems at the source. The King and Lenox study (2001) finds that ISO 9000 ( International certification for Total Quality Management Systems) certified manuf acturers with low inventories of hazardous materials have lower emissions of toxic chemicals. It should be noted that ISO 9000 is not generally consider ed a Lean manufacturing best practice, although there is a great deal of synergy between Total Quality Management (TQM) and Lean manufacturing. The EPA study (2003) showed how Lean has direct Green b enefits as a biproduct of efficiency gains. But the study fell short o f showing that Lean led to

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112 commitment to a Green manufacturing system that leads to sustained and broad based environmental improvement. Russo (2001) showed t hat committing to ISO14001 had a strong relationship to environmental i mprovement (TRI emissions). The Florida Study A study conducted by Dr. Richard Florida of Carnegie Me llon University explored the relationship between advanced manufacturing practi ces (e.g. Lean manufacturing) and environmental performance. The r esearch effort included a combination of survey research, phone interviews, and fi eld research consisting of factory visits and on-site personal interviews. The hypothesis this study set out to prove was “that firms that are innovative and adopt advanced manufacturing practices can simultaneously realize improv ements in productivity and environmental performance. In other words, envir onmental improvements to some extent flow from broader corporate efforts to inn ovate and implement new and more efficient manufacturing systems and practices.” This is similar to the findings of Rothenberg who showed that Lean companies e re more resource and energy efficient. The Dr. Florida study defined the elements of Lean m anufacturing as a blend of technology and organizational changes: specifically, self -directed work teams, worker rotation, continuous process improvement, supply cha in management – close relations across the production chain. (Womack, 1996) The study explored the application of teams, continuous improve ment, supply chain

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113 management, management commitment and investment to i mproving environmental performance. Essentially the study showe d that best practices commonly used in Lean manufacturing strategies are also u sed in Green manufacturing strategies, suggesting synergy between stra tegies. Specifically, the following questions were asked of respondents. How important is pollution prevention is to overall corporate performance? Are you pursuing zero emissions manufacturing? What percent of capital expenditures are devoted to p ollution prevention? What are the main components of your pollution preve ntion strategy? What production process improvements were made to imp rove environmental performance? What emission level reduction resulted from waste minim ization efforts? Rank the effect certain factors have on your corporate environmental strategies on a scale 1-4. Who is most important in pollution prevention? The Florida study shows a combination of organizationa l practices and advanced technology into a system of waste minimization is more e ffective than a singular approach. The cluster analysis included key measures from the survey as well as data on firm size, sales, age, and industry obtained f rom Dun and Bradstreet. Four distinct clusters of advanced-environmental practices were established that are described as follows: Cluster 1 companies: Rate pollution performance as very important to corp orate performance Represent the largest sample of companies from the stu dy n=61 or 35% Are relatively large 48% over $2 Billion, only 15% under $500k in sales Exhibit high rates of adoption of technical and organ izational solutions (i.e. source reduction, recycling, process technology, TQEM) Integrate their pollution prevention initiatives acr oss the entire industrial chain. Rate productivity and technology as key drivers of th eir environmental strategy.

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114 Devote a relatively high level of capital expenditu res to pollution prevention. Significantly reduce emissions. Cluster 2 companies: Rate pollution prevention as relatively important Devote a relatively high level of capital expenditu res to pollution prevention Report a high level of emission reduction Low adoption rate of pollution prevention technolog y Less likely than cluster one companies to adopt organiz ational approaches to pollution prevention such as TQEM – EI Low integration rate of pollution prevention effor ts across the supply chain Cluster 3 companies: Consider pollution prevention as of moderate importa nce to corporate performance Readily adopt new production process technology, recyclin g and source reduction Moderately adopt organizational innovations such as T QEM, and worker involvement Moderately adopt supply chain best practices Do not rate productivity improvement or technology a s major drivers of their pollution prevention programs Dedicate moderate levels of capital expenditures to p ollution prevention resulting in slow rates of emission reduction Cluster 4 companies: Rate pollution prevention as relatively unimportant to corporate performance Exhibit low levels of organizational and technologica l efforts for pollution prevention Are mostly smaller firms Dedicate moderate level of capital expenditures to po llution prevention resulting in slow rates of emission reduction Exhibit little adoption of technology or organizati onal approaches directed toward pollution prevention. The Florida study found that dependent relationships between manufacturers and suppliers leads to transferring best practices betwee n supply chain partners, including environmentally conscious practices. Traditional ly manufacturers used their supply chains as a means of outsourcing hazardous operations to make their own environmental performance at the cost of th e suppliers. More recently collaborative efforts seek to improve environmental per formance throughout the

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115 supply chain. Some operational improvements in this ar ea also have environmental benefits. Just-in-time deliveries reduce both inventory and waste. Pressure to continuously improve quality and cost perfor mance provides incentive to reduce waste. Co-involvement in product design provides opportunities to design products and processes that are more efficient and environmentally benign. The Florida study found the following specific example s of supplier involvement in improving environmental performance. Motorola proactively drives pollution prevention effo rts with its suppliers. IBM worked with suppliers to transfer CFC based cleani ng of circuit cards to aqueous based cleaning. Scott Paper and Safety Kleen worked with suppliers to eliminate toxic chemicals through recycling and process changes. Amko Plastics developed task teams with suppliers to de velop water based inks or printing plastic films (24). Rayovac established an environmental audit and rankin g system for its suppliers and worked with first tier suppliers to diffuse polluti on prevention techniques throughout the supply chain. As part of Sony’s efforts to reduce cost and waste, the co mpany worked with suppliers to completely recycle all scraps thereby reducing environmental waste. The efforts to redesign packaging to lower cost led to u sing less material and lowered solid waste levels. Sony also reduced paint costs by going to water based pa ints, and lowered hazardous materials usage as well. Dr. Florida found that progressive companies used advance d techniques to reduce environmental wastes. These techniques include th e use of teams, technology investment, process improvement, involvement of suppliers and customers, pursuit of zero waste, or at least aggressive g oals for waste minimization, involvement of all types of employees ( i.e. executives, engineers,

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116 workers, consultants, suppliers, and customers). These best practices are important elements of both Lean and Green manufactur ing strategies. The study does not indicate if these best practices are a lso applied to Lean manufacturing wastes. What we don’t know is if the comp anies apply these best practices to reducing Lean wastes or simply began a Green manufacturing program for other reasons. In other words, did these progressive best practices originate as part of a Lean manufacturing program? O r, have these best practices grown out of a Green manufacturing program an d spread over to addressing Lean wastes? This study only asks if these best practices are applied to reducing environmental wastes. The Rothenberg Study This study looked at the effect of Lean practices (indepe ndent variables) on three environmental metrics/performance measures (Dependent variables) in the automotive industry. Sandra Rothenberg performed a quantitative analysis of data from a Green and a Lean survey, the Environment al Practice Survey (EPS) and the Work Practice Survey (WPS), respectively. The E PS is an instrument to attain a variety of quantitative measures of plant en vironmental performance and management. From this survey, three environmental p erformance measures were used in the Rothenberg study as dependent variabl es. Air pollution was measured by plant level emissions of volatile organic co mpounds (VOCs) in kg/vehicle. Resource efficiency was measured by water use per vehicle

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117 (m 3 /vehicle) and energy use per vehicle (MMBTU/vehicle). The metrics were averaged over two years. The Work Practice Survey (WPS) provided two Lean inde pendent variables: plant productivity and Lean management index. Plant productivity was measured as labor hours per car, lower labor hours per vehicle t ranslates to higher productivity. The Lean index is comprised of three bun dle variables, the use of buffers, work systems, and human resource management polici es. The ‘use of buffers’ variable measures the degree to which producti on operations are buffered against potential disruption. It is a combin ation of repair area size, inventory policy (days of parts and frequency of delive ry) and the size of the paint-assembly buffer. The ‘Work systems’ variable meas ures the work structures and policies that govern production activity on the shop floor and influence the skill acquisition and development of prod uction workers. It is a combination of percent of workforce in teams, percent of work force in employee involvement groups, number of employee suggestions, am ount of job rotation, and decentralization of quality responsibility. ‘Hum an resource management practices’ measures organization-wide policies that gover n the relationship between management and employees. It is the combinati on of recruitment selectivity, training for experienced employees, conting ent compensation, and status differentiation. Both surveys, the WPS and the EPS, were conducted on the same 32 automobile assembly plants (7 in Japan, 25 in North Am erica). One plant was

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118 ruled out due to a unique painting process. The Roth enberg study found that Lean companies use less water and energy than their less L ean counter parts. Energy reduction was more pronounced due to the fact t hat energy is readily perceived as costly and may be less capital intensive to reduce than water usage. However, Lean plants tend to have slightly hig her emissions of VOCs. This results from the fact that Lean companies try to ex clusively use source reduction to minimize environmental waste. Whereby, traditional manufacturers use end-of-pipe containment devices such as scrubbers. Whi le end-of-pipe solutions may reduce the amount of waste emitted at th e point source, they do not reduce the amount of waste itself, rather they simp ly transfer it to a different media (i.e. scrubbers transfer air-born VOC waste into hazardous solid waste). In addition to performing quantitative analysis of sur vey data, the Rothenberg study also performed several case studies on particular au tomotive manufacturers. The case studies suggested two primary w ays in which Lean production benefits Green production. Lean plants have a ‘waste reduction ethic’ and are better organized to identify waste in the pr ocess. For example, Rothenberg found that Lean plants had a high level o f employee participation in energy reduction activity. Here the Lean best practice of employee involvement is applied to the Green objective of lowering energy consumption. The study also found since operators were trained in charting, gra phing and statistical analysis of production data, they were better able to identify and implement environmental improvements. Third, in a Lean manufa cturing environment,

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119 employees are continually challenged to innovate and experiment with process improvement ideas. There are several examples in the automotive case studies from Rothenberg where the experimentation afforded to engineers in l ean plants, even if it meant halting production, was critical to innovative solutions that improved environmental performance. In contrast, engineers in t raditional mass production automotive plants were frustrated because they were ne ver given time to experiment for fear it would slow down production. It seems from this anecdotal information gathered in the case studies that the qua ntitative analysis would show a striking difference in the environmental perform ance between Lean and non-lean plants. However, Rothenberg found marginal improvements in the areas of water and energy use amongst Lean plants and a ctually higher VOC emissions by Lean plants. Rothenberg admits that the small sample size may have so mething to do with this, and the fact that Lean plants are probably relu ctant to implement end-ofpipe solutions, which would account for higher VOC emi ssions. In one of the case studies, an environmental manager from a Japanese au tomotive transplant in North America stated, “instead of asking ‘how much en d-of-pipe technology should we add?’ [we] put those resources into increasing efficiency and wait until regulation forces the add on controls.” Although Lean companies primarily target the seven lL ean wastes (defects, overproduction, transport, waiting, inventory, motion and excess-processing), waste

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120 is waste. The waste identification and elimination met hods used on these seven wastes may spill over to environmental wastes. Lean man ufacturing strives to eliminate all non-value added activities; environmen tal waste and the efforts to manage it certainly fit these criteria. However, this theory was not validated in the Rothenberg study. Rothenberg (2001) showed that Lean companies tended to have improved environmental performance, but did not indicate whether that was because Lean manufacturers are simply more resource e fficient or if they actually implement Green manufacturing best practices. The King, Lenox Study King and Lenox believe that Lean and Green are compl ementary. For example, ‘good housekeeping’ or 5S practices associated with Lean manufacturing have led to the reduction of spills and other forms of envir onmental waste (Florida 1996, Hart 1997, King, Lenox 2001). They attempted to prove this by showing empirically that Lean leads to pollution prevention, reduces barriers to implementing environmental waste minimization solutio ns, and helps to identify the costs of environmental waste reduction opportunitie s. Thus, Lean manufacturing reduces the marginal costs of Green man ufacturing due to shared practices and complementary attributes. The empirical study combined several large databases of U.S. manufacturers totaling 17,499. The study focused on readily availab le information on manufacturers such as ISO 9000 certification and publicl y available emissions information reported to the EPA. Essentially this stu dy looked at the correlation

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121 of ISO 9000 certification, inventory levels of TRI li sted hazardous materials, and TRI data. While this allowed for broad coverage and empirical data, these are insufficient measures of Leanness and Greenness. Unlike the automotive study performed by Rothenberg, the King, Lenox study, finds a strong relationship between Lean manufacturing and toxic chemical reduction. They found that Lean facilities reduce emissi ons through pollution prevention rather than end-of-pipe solutions. This f inding is consistent with Rothenberg. Also, King and Lenox found that firms ar e more likely to implement the ISO 14000 International Environmental Managem ent System Standard if they are already ISO 9000 certified. They also fou nd that companies that implement Lean systems reduce emissions. “Studies cannot ru le out the fact that Lean and Green may simply be by-products of a firm’s innovative nature. (King, Lenox 2001)” However, there is a problem with the King, Lenox stud y. Given that they were trying to perform a broad study based on generally av ailable data, their definition of Lean manufacturing is questionable. Essentially, thi s study measures “Leanness” based on ISO9000 certification and the level of hazardous material inventories. The study finds that companies with low in ventories of hazardous materials and who are ISO9001 certified, have lower toxic emissions than companies with higher inventories and that are not IS O9001 certified. It could be that the reason they have lower inventories of hazard ous materials is because their manufacturing processes are more benign and, there fore generate less

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122 toxic emissions. Also, the study finds that manufacturers that adopt ISO9000 are more likely to adopt ISO14000. It has been shown tha t ISO9000 certification provides an excellent foundation for ISO14000 impleme ntation. Perhaps ISO9000 serves as a catalyst to ISO14000. Proponents of the Lean and Green relationship obser ve that “zero waste” is the mantra of Lean manufacturing and suggest that pollutio n prevention will inevitably follow from this philosophy (Florida 1996, Hart, 1997). Lean manufacturing develops process improvement capabilities t argeted toward reducing waste (Womack and Jones,1990). Lean manufacturin g requires workers to develop skills needed to reduce wastes, targete d by the Lean manufacturing doctrine (defects, over-production, tran sport, waiting, inventory, motion and excess processing) (MacDuffie, 1995). Once oper ators develop these skills, teaching them related skills that target env ironmental wastes may require less investment. Thus, Lean manufacturing indirectly improves environme ntal performance by lowering the cost of waste reduction and by developing continuous improvement skills that are shared by both Lean and Green manufactur ing programs. (King, Lenox 2001). Lean production may also reduce the cost of pollution prevention by lowering the cost of discovering pollution preventio n opportunities. Lean production helps identify non-value added activities an d the costs associated with them. Use of activity based cost systems are common among Lean practitioners. Such cost targeting techniques may provi de managers with new

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123 expectations of the potential costs and benefits of pol lution reduction activities. Essentially, by developing tools to identify and reduce operational waste, Lean manufacturing ‘greases the skids’ for reducing environmen tal waste. Theory suggests that a priori expectations and search cost s can inhibit managers from uncovering existing opportunities for profit (Ar row 1974;Jensen 1982). If managers expect pollution-reduction to be costly, and it is difficult to do the measurement and analysis to test this expectation, manage rs may never investigate the real value of pollution reduction (Jensen1982). A s a result, opportunities for profitable pollution reduction may go unexploited. (King, Lenox 2001) This study hypothesizes that Lean manufacturers are more likely to use source reduction rather than end-of-pipe treatment. The lo gic here is sound, in that Lean manufacturing focuses on eliminating waste at the s ource versus at the end of the process. Examples of this include the use of poke -yoke (mistake-proofing) and sequential inspection versus end of line inspection t o reduce defects. Rothenberg determined that Lean manufacturers relied almost exclusively on waste minimization versus end-of-pipe containment to re duce environmental waste emissions. (Rothenberg, 2001). The Lean philosop hy views any nonvalue added process as wasteful and espouses stopping prob lems at the source. The King, Lenox study suggests that Lean firms will have lower emissions than non-lean firms. This hypothesis is based on the fact th at Lean companies already exploit waste reduction activities and this ble eds over to environmental waste reduction. Secondly, King and Lenox believe tha t Lean manufacturing serves as a catalyst to adopting environmental managemen t systems, such as ISO14000. This is probably based on the fact that Kin g and Lenox heavily weight the adoption of ISO9000 as a prime measure of Lean manufacturing.

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124 Lean manufacturing has been found to directly improve environmental performance by reducing energy requirements for produ ction (Rothenberg, 2001). However, Rothenberg found that Lean manufact urers actually have slightly elevated VOC/TRI emissions, because they do not use end-of-pipe containment systems. However, the overall waste generat ed is lower than companies that rely on end-of-pipe systems. End-of-pip e solutions simply change the medium of waste instead of eliminating it f rom occurring in the first place. The sample for the King, Lenox study was based on manuf acturers that reported their Toxic Release Inventory (TRI) to the EPA during the years of 1991 – 1996. By law, companies that manufacture more than 25,000 po unds or use more than 10,000 pounds of any of the listed chemicals, and employ at least 10 people throughout the year, must complete TRI reporting. Th e result was a sample of 17,499 facilities over a five year period, equaling 8 8,531 facility year observations. The ISO14001 standard is the most prominent environmen tal management system in the United States. The standard was established in 1996, by the International Organization for Standardization. ISO 14001 requires a facility to develop an environmental policy, set objectives, deline ate organizational responsibilities, provide training and documentation, a nd monitor and correct deficiencies (ISO, 2002). It is the environmental ana logue to the ISO9001 quality management standard. ISO14001 Adoption is coded simpl y as a dummy where

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125 "I" indicates that a facility became ISO14001 certified sometime during the period 1996-1999. Certification data were gathered from t he GlobeNet database of ISO14001certified firms (GlobeNet, 2000). This study used a variety of measures for environmental performance. They include; Toxic Release Inventory (TRI) Emissions, as repor ted to the EPA; Waste generation; On-site treatment; The adoption of the I SO14001 EMS standard. Since the data used for the study predates ISO14000 ce rtifications in the use, ISO14000 certification is used as a dummy variable that post dates survey data. Given that the study focused exclusively on manufacturer s that are large enough to require TRI reporting, they did a good job of ass essing Greenness. Unfortunately, the King, Lenox study implies that ‘Le anness’ can be measured by inventory levels of hazardous materials and ISO9000 ce rtification. Inventory is in fact one of the seven wastes targeted by Lean manufact uring. Typically this applies to direct materials at various stages of product ion. Hazardous materials are often considered indirect materials, used for cleani ng and processing. At least this is the case for discrete product manufacturing. So, this does not serve as a good measure of Leanness, when Lean systems focus most ly on the flow of products from the raw material stage to customer accepta nce. Secondly, they chose to simply use ISO9000 certification to cover all ot her aspects of Lean manufacturing (i.e. work systems management). While IS O9000 leads to process standardization essential for Lean production, it is not a strong depiction

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126 of Lean manufacturing. ISO9000 is a standard for qua lity systems, not Lean systems. Many companies that are ISO9000 certified are n ot Lean at all. Finally, our findings further support the idea that potential complementarities exist among operational practices, and that firms should conseq uently consider adopting these practices in bundles (MacDuffie 1995; Milgrom and Roberts 1995). MacDuffie (1995) argues that when firms move to lean productio n, they should adopt a bundle of new inventory, technology, and work practices. Our research suggests that managers should consider including green practices in thi s bundle.' (King and Lenox, 2001) The EPA Study The EPA (2003) in collaboration with Ross & Associates, an environmental research and consulting firm in Seattle, WA conducted a study of Boeing Corporation to determine if Boeing’s Lean manufactur ing program generated environmental improvements. The study showed that Boei ng’s Lean manufacturing program reduced environmental waste as a byproduct of process efficiency and quality improvements associated with “Lean ing” the manufacturing process. Secondly, they observed that the “waste reducin g culture” associated with Boeing’s Lean manufacturing program is exactly th e type of culture the EPA has deemed essential for sustained environmental improv ement. They also observed that Lean manufacturing programs/systems at Bo eing and in general do not specifically address environmental waste reduction as a core objective of the program and considerable research opportunities ex ist to “build a bridge” between Lean and Green manufacturing systems. This stud y closely relates to the topic of this present study and for purposes of comple teness excerpts from

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127 the EPA/Ross & associates study of Boeing are included be low. In particular, the study produced the following conclusions: Lean produces an operational and cultural environment that is highly conducive to waste minimization and pollution prevention (P2). Lean methods focus on continually improving the resource productivity and pr oduction efficiency, which frequently translates into less material, less capital, less energy waste per unit of production. In addition, lean fosters a systematic, em ployee-involved, continual improvement culture that is similar to that encouraged by the public agencies’ existing voluntary programs and initiatives, such as those focused on environmental management systems (EMS), waste minimization, pollutio n prevention, and Design for Environment, among others. There is strong evidence that lean produces environment al performance improvements that would have had very limited finan cial or organizational attractiveness if the business case had rested primarily on conventional P2 return on investment factors associated with the projects. Conv entional P2 return on investment factors include reductions in liability, comp liance management costs, waste management cost, material input costs, as well as a voided pollution control costs. This research indicates that the lean drivers for cu lture change-substantial improvements in profitability and competitiveness by d riving down he capital and time intensity of production and service processes-are consi stently much stronger than the drivers that come through the “green door,” such as savings from pollution prevention activities and reductions in compliance risk and liability. This research found that lean implementation efforts cr eate powerful coattails for environmental improvement. To the extent that impr oved environmental outcomes can ride the coattails of lean culture change, there is a win for business and a win for environmental improvement. Pollution preventio n may “pay”, but when associated with lean implementation efforts, the likel ihood that pollution prevention will compete rises substantially. Lean can be leveraged to produce environmental improveme nt, filling key “blind spots” that can arise during lean implementation Although lean currently produces environmental benefits and establishes a systematic, contin ual improvement-based waste elimination culture, lean methods do not explicit ly incorporate environmental performance considerations, leaving environmental impro vement opportunities on the table. In many cases, lean methods have “blind spo ts” with respect to environmental risk and life-cycle impacts. The research identified three gaps associated with these blind spots, that, if filled, could further enhance the environmental improvements resulting. First, lean methods do not explicitly identify pollution preventi on and environmental risk as “wastes” to target for elimination. Second, in many o rganizations, environmental personnel are not well integrated into operations-ba sed lean implementation efforts, often leading environmental management activities to operate in a “parallel universe” to lean implementation efforts. Third, the wealth of information and expertise related to waste minimization and pollution prevention that environmental

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128 management agencies have assembled over the past two deca des is not routinely making it into the hands of lean practitioners. Despite these gaps, there is evidence that lean provide s an excellent platform for incorporating environmental management tools such as li fe-cycle assessment, design for environment, and other tools used to reduce environmental risks and lifecycle environmental impacts. Environmental Agencies have a window of opportunity to e nhance the environmental benefits associated with lean There is strong and growing network of companies implementing, and promoting, lean across t he U.S. For those companies transitioning into a lean production environm ent, EPA has a key opportunity to influence their lean investments and im plementation strategies by helping to explicitly establish with lean methods envi ronmental performance considerations and opportunities. Similar, EPA can bu ild on the educational base of lean support organizations – non-profits, publishers, a nd consulting firms – ensure they incorporate environmental considerations into the ir efforts. EPA (2003) Chapter Summary This concludes the literature review section of this disser tation. Based on the detailed description of Lean and Green systems and previ ous studies regarding the relationship between them, it is clear that these two systems share a great deal in common and there is great potential for transce ndence from Lean manufacturing to Green manufacturing. Following thi s section is chapter three that summarizes the literature review and identifies a research gap and describes how this dissertation study will fill that gap. Chapte r three also describes the construction of a comparative model for Lean and Green manufacturing systems that forms the basis for the dissertation’s quantitative analysis.

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129 Chapter Three Theoretical Constructs Introduction The literature review of chapter two summarizes previou s research that describes Lean and Green manufacturing systems and the rel ationship between them. These studies showed evidence of shared best pra ctices and environmentally beneficial byproducts resulting from L ean manufacturing implementation. However, these studies fell short of indicating whether Lean manufacturers transcend beyond the traditional boundar ies of their Lean systems to embrace the broader Green manufacturing system that drives continuous environmental waste reduction. If so, then Lean manu facturing could be used as a catalyst to industrial sustainability: Industry in bala nce with Earth’s capacity to generate natural resources and process industrial waste. Summarizing the findings of the most recent Lean and Green manufacturing research yields the following conclusions. First, both Lean and Green bodies of literature indi cate that a systems approach is needed to create and sustain a culture for continuous w aste reduction. The main high-level components common to both Lean and Gr een manufacturing systems can be categorized into three components. The management system

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130 establishes formal management commitment to create the environment/culture conducive to waste reduction, the implementation of waste reducing techniques to physically transform products and processes to reduce wa ste, and measurable results to indicate to all stakeholders the benefits of the system Second, successful implementation of either Lean or Gre en manufacturing systems results in improvements that go beyond the tradi tional objectives of the respective system and have byproduct benefits that help t o fulfill the objectives of the other system. Third, Lean and Green systems share many best practices, th at once implemented for one system can easily be utilized for the other system, assuming management chooses to commit the organization to implementation of the other manufacturing system. Fourth, manufacturers are under competitive pressure to reduce operational waste (e.g. inefficiencies and quality defects) associated with Lean manufacturing. Manufacturers are also under growing p ublic and regulatory pressure to reduce environmental waste, which if done pr operly lowers operating costs, improves public image, and reduces risks of liability Thus, there is great motivation on the part of manufacturers to reduce waste associated with both systems, and to do this in the most efficient manner. T his could lead to efforts to integrate Lean and Green systems.

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131 Synthesizing these conclusions suggests that manufacturers, t o use a legal analogy, have the motive, means and opportunity to t ranscend to Green manufacturing. The question is: Are they doing it? Specifically, to restate the research question: Are Lean manufacturers transcending to Green manufacturing? To answer this question adequately ma nufacturing plants must be assessed from a full manufacturing systems perspective. This requires instruments to measure a manufacturing plant’s level of diffusion of Lean and Green manufacturing system components (a.k.a. best practice s). The literature review explored the latest research on Lean and Green manufacturing systems to define the generally accepted components/best practice s which comprise these two systems. These best practices provide the raw mat erials to develop a comparative research model. The purpose of this chapter is to build a comparative model for Lean and Green manufacturing syst ems, at a full system level. This model is utilized to conduct an empirical st udy to correlate the diffusion of Lean and Green manufacturing systems best p ractices. Theory Synthesizing the body of Lean and Green literature p ainted an evolving relationship between these two systems that leads to a th eoretical interpolation into the future. Philosophically speaking, Lean and Gr een manufacturing systems may start off targeting seemingly different type s of waste, but eventually all manufacturing wastes affect the objectives of either system. Ultimately, the pursuit to become truly Green will require reducing ope rational wastes that

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132 typically generate environmental waste as a result of p rocess inefficiency. Likewise, to become truly Lean, one must address environ mental wastes, which are almost always non-value added. So in the end, wh at begins as a pursuit to become Lean leads to becoming Green, and what begins as a pursuit to become Green leads to becoming Lean. This abstract reasoning leads to several interesting rese arch questions. If Lean companies are constantly looking for opportunities to r educe waste, and have developed skills and tools toward this end, do they natu rally become Greener as they become Leaner? The exact same argument could be made if a company started down the Green path first. Do companies become Leaner as they become Greener? Would Green companies ultimately emb race Lean manufacturing best practices because a more efficient pla nt, which uses less energy and resources, is a more environmentally friendl y plant? To borrow a phrase, is waste by any other name still waste? It is helpful to describe this plausible evolution betwe en Lean and Green systems into a series of Venn diagrams. These diagrams will serv e to frame the discussion of what aspect of this evolution has been studie d in previous research and what is yet to be studied. This will help shape t he specific research model for this study, which contribute to moving the body of Lean and Green research to the next level.

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133 UNIVERSE OF MANUFACTURING WASTES Lean Manufacturing System Green Manufacturing System UNIVERSE OF MANUFACTURING WASTES Green Manufacturing System Lean Manufacturing System PARALLELISM: The traditional view whereby Lean and Green best practices are considered distinct sets of solutions targeting different forms of wastes. Some consider these efforts as co nflicting. Best practices are administered by separate organization s operating in “parallel universes” of waste reduction. CONVERGENCE: The modern view, whereby Lean and Green best practices are considered complementary. Best practices from one discipline are successfully applied to reduce the o ther discipline’s wastes. Continuous improvement teams are starting to look at solutions that are both Lean and Green. Figure 11. Evolution of Lean and Green Manufacturing Systems

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134 UNIVERSE OF MANUFACTURING WASTES Green Manufacturing System Lean Manufacturing System SYNERGY: The Future, whereby distinctions between L ean and Green systems ends, and Zero Waste Manufacturing is the new holistic manufacturing system. Elimination of all forms of waste is the new corporate mantra. Synergy is realized as aggressiv e efforts to reduce waste results in continuous efficiency, quality service and environmental improvements. New best practices evolve as new form s of waste are identified, beyond the present boundaries of Lean o r Green wastes. The Earth itself serves as the model for manufacturing perfection and the TRANSCENDENCE: The view suggested in this study. Companies that are actively implementing Lean or Green manufacturing systems not only fully explore the common solutions (intersection of Lean and Green best practices) but also start down the path of implemen ting the other manufacturing system. Lean and Green manufacturing systems serve as a dualcatalyst to each other. Employees throughout the c ompany implement a broad set of best practice targeting th e full spectrum of wastes associated with both Lean and Green manufact uring systems. UNIVERSE OF MANUFACTURNG WASTES Zero Waste Manufacturing System Figure 11. (Continued)

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135 Research Model Construction In order to determine if transcendence and/or synergy e xists, comparative models of these two manufacturing systems that are consisten t with scholarly research of the two systems are needed. This required th e development of models for each system that were robust enough to captur e the complexities of each system, yet simple enough to allow for meaningful correlation analysis between major factors of the two systems on an “apples to apples” basis. Fundamentally, both Lean and Green manufacturing syste ms have three major factors: Management Systems, Waste Reducing Techniques, and Results. The management system defines the policies and procedures that create the environment/culture that commits the organization towa rd waste reduction, respective to each manufacturing system. Waste reducing t echniques are the specific process (both business and production process) change s associated with each manufacturing system that result in waste reduc tion, respective to each manufacturing system. Results are the measurable impro vements to the stated objectives of each manufacturing system. For example, th e objective of Lean manufacturing systems is to lower operating costs, improve quality, and reduce cycle-time. The objective of Green manufacturing syste ms is to lower costs of environmental compliance and waste management, while r educing environmental impact. Research on these two manufacturing systems typically looks for correlation between some combinations of these factors. A considerab le amount of

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136 research has been done to support the strong correlation s between the factors within either Lean or Green manufacturing systems over the past fifteen to twenty years. Only recently (the past five to ten years) has m eaningful research been done to explore the correlations between Lean and Gre en manufacturing systems. Already these studies are indicating statistically that there is correlation between the two manufacturing systems. Yet, there remai ns considerable research opportunity to complete the picture of full cor relation between these two manufacturing systems, leading perhaps to a holistic waste reducing manufacturing system. The following model diagram describes both Lean and Gr een manufacturing systems in their major components (management systems, waste reducing techniques, and results). Each block represents a set of cr iteria based on industry best practices. The arrows indicate the “indepen dent to dependent” relationship supported by literature. The citations in dicated in the model diagram support either the best practices associated with that par t of the model and/or correlation analysis between sets of best practice criteria Clearly there is a research gap at the “Front end” of the model in terms of the correlation among the level of Leanness in general and the level of Green management systems. There is also only anecdotal evidence regarding correlation between waste reducing techniques between sy stems. That is to say that the Florida study (1996) indicated that Lean too ls are being applied to the reduction of environmental waste, but not necessarily b y Lean companies.

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137 LEAN AND GREEN MANUFACTURING SYSTEM MODELS --------------------------------Melnyk, Stroufe, Ca lantone (2002) ----------------------------------------------------------------------------------------R usso (2001) ----------------------------------------------------------------------EPA 2000---------------------------PP/WM Studies (1992 – 2002) -------Green Management System (GMS) Green Waste Reduction Techniques (GWRT) Green Results (GR) LEGEND: Solid arrows indicate correlation between f actors (Independent Dependent variables) Dashed lines mean complementary use of technique s, but not necessarily correlation Citations near each arrow relate to specific stu dies supporting the correlation between the two factors connected by the arrow. Citations above the Lean system components and below the Green system components have arrows indicating t he breadth of coverage of the studies cited. Panizzolo Melnyk, Stroufe, Calantone (2003) ----------------Panizzolo (1998) --------------------------------SAE J4001 (2002) ---------------------------------------------------------------------Liker (2004)-------------------------------------------------------------------------------------------------Womack (1996) ---------------------------------------EPA (2003) Rothenburg (2002) Lean Results (LR) Lean Management System (LMS) Lean Waste Reduction Techniques (LWRT) Florida (1996) Figure 12. Lean and Green Manufacturing System Model

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138 The diagram shows that previous studies have not addressed if the level of Lean system diffusion correlates to the level of diffusion of Green management system or Green waste reducing techniques. Rather, previous stu dies focus more on the results part of the model between Lean and Green system s. To determine if transcendence from Lean to Green manufacturing system d iffusion exists, an empirical study can measure correlation between Lean and Green manufacturing systems components. To do this, valid measures of each syst em must be defined and instruments developed to measure the diff usion levels of Lean and Green manufacturing system components. An empirical ap proach of this nature requires cooperation from actual manufacturers, and was d one through survey instruments, as opposed to on-site case studies, in order to stay within the resource constraints of the study. With these considerations in mind, the leading models o f Lean manufacturing in the literature were reviewed for their application i n this dissertation study. The Toyota (4P) model described by Dr. Jeffery Liker (2004 ); the Society of Automotive Engineers (SAE) J4001 model (1999); and th e Shingo Prize for Excellence in Manufacturing (2003) are all comprehensiv e models of the Lean manufacturing system. The J4001 and the Shingo model s are already structured into assessment instruments, making them very practical for this type of research study. The Shingo criteria are unique in that a pane l of five experts has been assessing Lean manufacturing plants according to the Shing o Prize model since 1988. In 2006 the Shingo Prize criteria became the basis for the new national Lean certificate program sponsored by the Society of Man ufacturing Engineers

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139 (SME) and the Association for Manufacturing Excellence (A ME), working in collaboration with the Shingo Prize team. This is val idation that the Shingo criteria are viewed as the gold standard for Lean, as c onfirmed by two leading manufacturing associations. The instrument used by the Shingo Prize examiners is ca lled the Shingo Prize scoring system. A team of five expert examiners collabor ate to score a manufacturing plant’s “Leanness”, in eleven sub-categor ies that roll-up to three main categories (enablers, core operations, and results). These three categories are analogous to the three general categories described in the research model (i.e. management system, waste reducing techniques, and r esults). Shingo Prize scoring system data collected by the examiners is stored in a database and utilized to determine if a plant is a Shingo Prize re cipient, finalist, or simply an applicant. In the fall of 2004, Dr. Ross Robson (Executive Director of the Shingo Prize) indicated that he had recently become aware of the int erest in Lean and Green manufacturing systems by being contacted by Ross and Associa tes, who were conducting a case study on the environmental benefits of Boeing’s Lean program. This study is discussed in detail in the litera ture review. Dr. Robson was willing to support a study to survey the environmen tal practices of Shingo companies that had received site visits from examiners. This meant that an externally validated data set was available to serve a s the measure for the Lean

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140 manufacturing system. This meant that an equivalent m easure for the Green manufacturing system was required to perform correlatio n analysis. The selection criteria that were used to choose the Shin go criteria were applied to the selection of the Green manufacturing system instr ument, with one twist. The Green manufacturing instrument would ultimately b ecome a survey administered to the Shingo Prize manufacturing plants, which is a relatively small population (n<200). This meant the survey had to be very user friendly, to assure a high response rate. Yet, it still had to ade quately measure the broader Green manufacturing system. It also had to be general enough to be applied to the diverse set of discrete manufacturers that make up th e Shingo plant population. In reviewing the Green manufacturing literature, it was readily apparent that the survey instrument utilized by Melnyk et al (2003), struck a nice balance between breadth and brevity. It categorically covered the thr ee main sections of the manufacturing system research model (management system, w aste reducing techniques, and results). The Melnyk survey utilized the gold standard for environmental management systems (ISO14001), which is ob jectively measured through an independent annual audit of the manufact uring plant. The fourteen Green waste reducing techniques were all consistent with t he EPA’s guide for pollution prevention and waste minimization, considere d the gold standard for industry. The ten results factors in the Melnyk survey we re a robust balance of process and business metrics.

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141 The survey instrument was already validated by the Mel nyk team, and successfully applied to approximately eleven hundred di screte manufacturing plants. The statistics that came from the original Meln yk study could also serve as an interesting basis for comparison of the known Lean plants associated with the Shingo prize. The Melnyk study made a point of i ssuing their survey to a broad distribution of fifteen thousand discrete manufac turing plants listed in standard manufacturing databases. Description of Research Model The selection of Lean and Green manufacturing criteria was instrumental in shaping the hypotheses for this study. The committee agreed that “Gold Standard” Shingo criteria made for a strong independe nt measure of Lean. The Melnyk survey provides the complementary set of dependen t variables for the study. Survey data from the original Melnyk et al study of t he general manufacturing population, and data from the Shingo plants were bo th utilized in the hypotheses. The Melnyk survey is also distributed to the Shingo plan ts so that comparison can be made to the general population and within the Shingo population iutilizing the same set of Green variables. This assures an “apples to apples” comparison. This led to the research model and hypothese s stated below.

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142 The arrows in the diagram reflect the probable corre lations between the variable “LEAN” overall Shingo prize score, and the three variables Gr een management system (GMS), Green waste reducing techniques (GWRT), an d Green results (GR). The model suggests that the level of Lean manuf acturing system diffusion directly correlates to the levels of diffusion of the th ree environmental variables (GMS, GWRT, and GR). Lean and Green System Correlation Research Model Overall Lean Score (LEAN) = Lean Management System (LMS) + Le an Waste Reduction Techniques (LWRT) + Lean Results (LR) Measured by Shingo Scoring System criteria Green Management System (GMS) Measured by level of ISO14001 implementation via survey Green Waste Reduction Techniques (GWRT) Survey Green Results (GR) Survey Figure 13. Research Model

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143 Statement of Hypotheses The research model led to the development of hypothese s to answer this research question empirically. The availability of the Shingo prize plants whose level of Leanness was measured by a panel of experts ma de for the ideal set of independent variables to determine if levels of diffu sion of Lean manufacturing system components correlated to levels of diffusion of Gre en manufacturing system components. The set of three Green manufacturing system variables {Green management system (GMS), Green waste reducing t echniques (GWRT), Green results (GR)} serve as the set of dependent varia bles for the stated hypotheses. Hypothesis I is unique in that it compares the environme ntal performance of the set of Shingo plants with the set of general manufactur ers surveyed originally in the Melnyk study a few years earlier. The intent of t his hypothesis is to show that known Lean manufacturers are exhibiting significantly higher levels of environmental practices and results than the general ma nufacturing population. This would show evidence of Lean manufacturers transcendence to Green manufacturing. Hypotheses II through IV are internally focused within the Shingo plants that responded to the survey. Respectively, these hypotheses relate to correlation between a plant’s level of “Leanness” (LEAN) and its l evel of “Greenness” measured from the perspectives of the management system (GMS), waste reducing techniques (GWRT), and results (GR). The ind ependent LEAN variable

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144 is the total score from the Shingo Prize Scoring system. The Green dependent variables are taken from the three sections of the su rvey, each being the average score for that section. For ease of reference the hypot heses are listed below followed by a description of how the hypotheses were te sted and the results of these tests. Hypothesis I: Lean manufacturers, as recognized by the S hingo Prize team of examiners, are significantly Greener (as measured by G MS, GWRT, and GR variables) than the general population of manufacture rs, identified in the original Melnyk study. Hypothesis II: The overall Lean score (LEAN), as measur ed by the Shingo Prize examiners, positively correlates to the Green Manageme nt System score (GMS), as measured by the on-line Green survey. Hypothesis III: The overall Lean score (LEAN), as measur ed by the Shingo Prize examiners, positively correlates to the Green Waste Re ducing Techniques score (GWRT), as measured by the on-line Green survey. Hypothesis IV: The overall Lean score (LEAN), as measured by the Shin go Prize examiners, positively correlates to the Green Res ults score (GR), as measured by the on-line Green survey.

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145 Chapter Summary This chapter synthesized leading research on Lean and G reen manufacturing models, and previous research regarding their correlatio n. It then described a research gap to be filled and a practical means by which to fill the gap. The description of the research model and hypotheses for this dissertation study concludes chapter three. Chapter four will describe the specific research methodology used to test the hypotheses and perform fu ll system correlation analysis.

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146 Chapter Four Methodology Introduction This chapter describes the methodology utilized to test the hypotheses described at the end of Chapter three and conduct full system co rrelation analysis. This entails the definition of variables associated with the research model, the development and testing of an on-line Green manufact uring system survey, survey administration, data collection, and statistical a nalysis utilized to test the hypotheses and perform full system correlation analysis. Definition of Variables While this study sought to understand all possible correl ations between the components of both Lean and Green manufacturing systems, there was a decision to state hypotheses utilizing Lean variables as t he independent variables and Green variables as the dependent variab les. This was a logical choice, given that the Lean variables were known entiti es from the Shingo Prize database, validated by a panel of experts and the gre en variables were the unknown entity obtained by a survey administered to th ese Shingo companies. Control variables were also added to control external effects and minimize noise in the data.

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147 Lean Independent Variables The main lean independent variable LEAN is the total score from the Shingo prize scoring system database. It is the measure of an i ndividual manufacturing plant that received a site visit from a team of five S hingo prize examiners. The team collaborated to create a single set of scores for the eleven sub-elements of the Shingo prize criteria. Each of the sub-elements h as a range of potential points to earn, adding up to a total potential score of one thousand. Thus, LEAN is a continuous variable on a scale from zero to a thou sand. The Shingo prize scoring system worksheet used by examiners indicates the poi nt score for each of the eleven sub-elements and is shown in (table 7) The sub-elements for the Shingo prize scoring system, comp rise the Lean subvariables of this study, and are grouped into three ca tegories, associated with the research model (Lean management system (LMS), Lean waste reducing techniques (LWRT), and Lean results (LR)). The Lean ind ependent variables are listed below, with their labels in parentheses. Detai led descriptions of each of the variables listed below can be found in the literature review, Chapter 2, and will also be referenced in detail in chapters five and six. Lean Management system (LMS) = IA + IB Leadership (IA) Empowerment (IB) Lean Waste Reducing Techniques (LWRT) = IIA+IIB+IIC+ IID+III Vision/Strategy (IIA) Innovation (IIB) Partnerships (IIC)

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148 Operations (IID) Support Functions (III) Lean Results (LR) = IVA+IVB+IVC+V Quality (IVA) Cost (IVB) Delivery (IVC) Customer Satisfaction & Profitability (V) Total Lean score (LEAN) = LMS + LWRT + LR

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Company Name: City, State: Examiner Name: Points Possible Percentage Awarded Points Awarded Subtotal I.Leadership Culture & Infrastructure 150 0 A.Leadership 75 0 B. Empowerment 75 0 II.Manufacturing Strategy & Systems Integration 450 0 A.Manufacturing Vision & Strategy 50 0 B. Innovations in Market Service & Product 50 0 C.Partnering With Suppliers/Customers & Environment al Practices100 0 D.World Class Manufacturing Operations & Processes2 50 0 III.Non-Manufacturing Support Functions 100 00 IV.Quality, Cost & Delivery 225 0 A.Quality & Quality Improvement 75 0 B. Cost & Productivity Improvement 75 0 C.Delivery & Service Improvement 75 0 V.Business Results 75 00 Customer Satisfaction and Profitability TOTAL POINTS 1000 0 Would you recommend this company receive a Shingo P rize? Strongly Recommend RecommendNot RecommendStrongly Not Recommend Signature:Shingo Prize for Excellence in ManufacturingSite Visit Evaluation Form 11/2/2006 Table 7. Shingo Prize Scoring System Worksheet 149

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150 Green Dependent Variables In chapter three, the argument was made to leverage t he successful survey developed Melnyk et al in 2002. The Green dependent variables for this dissertation study will be taken directly from the Surve y. Two variables that seemed redundant were not utilized from the original Melnyk survey. New labels, shown in parentheses for each variable were developed for this study to coincide with the three Green management system model component s described in Chapter three (Green management system, Green waste re ducing techniques, Green results). Green Management System (GMS) Environmental management system/ISO14001 (GMS1) Years ISO14001 certified (GMS2) Green Waste Reducing Techniques (GWRT) Process redesign (GWRT1) Product redesign (GWRT2) Disassembly (GWRT3) Substitution (GWRT4) Reduce (GWRT5) Recycling (GWRT6) Remanufacturing (GWRT7) Consume internally (GWRT8) Prolong use (GWRT9) Returnable packaging (GWRT10) Spreading risks (GWRT11) Creating markets (GWRT12) Waste segregation (GWRT13) Alliances (GWRT14)

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151 Green Results (GR) Reduced costs (GR1) Reduced lead-times (GR2) Improved product quality (GR3) Improved market position (GR4) Enhanced reputation (GR5) Improved product design (GR6) Reduced process waste (GR7) Improved equipment selection (GR8) Benefits outweigh costs (GR9) Improved international sales (GR10) Total Green Score (GREEN) = normalized sum {GMS, GWRT GR} Control Variables Control variables were included to understand external influences on the variables under study. Based on discussions with the Shing o team and committee members, three control variables were chosen; quartile of lean scores, country of plant location, and year of Shingo site visit and assessment. This data resided in the Shingo prize scoring system data base and made available by the Shingo team. Quartile was chosen as a control variable, because it was thought that blocking the Shingo respondents into groups may provide a more discrete view of whether higher levels of greenness were associated with the highe st scoring Lean plants versus the lowest scoring lean plants. A simple point val ue was assigned to the four quartiles of respondents based on the total Lean score from the Shingo prize scoring system database. The definition of each quartile is below with the actual point value assigned in parentheses.

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152 Quartile 1: Lowest fourth of LEAN scores (1) Quartile 2: Second lowest fourth of LEAN scores (2) Quartile 3: Second highest fourth of LEAN scores (3) Quartile 4: Highest fourth of Lean scores (4) Country was chosen as a control variable because the three North American countries that are part of the Shingo database each h ave unique environmental regulations. It is believed that this could influence t he environmental behaviors of the plants in the study. The definition for each cou ntry is below with the actual point value assigned in parentheses. United states: Plant located in the United States of America (1) Mexico: Plant located in the country of Mexico (2) Canada: Plant located in the country of Canada (3) Year was chosen as a control variable because changes in both L ean and Green behavior could have occurred since the year the plant re ceived its Shingo site visit. Additionally, the data set was limited to five -years back so that the lag between Lean and Green assessment would not be too gre at. The value assigned to the variable year is the actual year the sig ht assessment was performed ranging from 2000 to 2005. Survey Instrument Consistent with the three main manufacturing system compo nents the survey has three sections (Management system, waste reducing tech niques, and results). Survey section one, Green management system, h as two questions that address the status and maturity of the plants envi ronmental management

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153 system implementation. Survey section two, Green waste reducing techniques, is comprised of fourteen questions regarding specific pract ices the plant undertakes to reduce environmental waste. Survey section three, results, is comprised of ten questions that address the process and busi ness results of Green manufacturing efforts in the plant. The survey questions align directly with the aforementioned Green dependent variables. Regarding survey scales, for section one, Green manageme nt system, the original seven-point scale from Melnyk was utilized. T his was because the scale labels were descriptive specific to the status of the Green management system. For survey section two, waste reducing techniques, and sect ion three, results, the original Melnyk survey scale was a simple numeric scale ranging from zero to ten. Committee members thought it would be more “u ser friendly” if I chose a common Likert scale with descriptive labels, rather than a numeric scale. Concern that changing the scale may change the reliabil ity of the survey instrument, led to research on survey scales. The research confirmed that as long as the scale is betwe en five and eleven choices, there was no discernable difference in the relia bility of the scale. This research also confirmed what committee members stated tha t the scale should be easily understood and not be confusing, as this could lead to frustration and adversely affect response. The decision was made to select five-point Likert scales for section two (waste reducing techniques) and sect ion three (results) survey question. The labels for the scale were based on recommendations from

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154 the literature that had proven user friendly in the past. A Not applicable (N/A) option was added for each question, so as not to force the respondent to answer a question erroneously if it truly did not apply to t heir plant. Survey scale research also confirmed that the addition of an N/A opt ion was helpful in reducing the frustration of survey respondents. A linear transformation was prescribed by Dr. Brannick t o normalize the original Melnyk eleven-point scale and this studies five-point sca le, for survey sections two and three. This allowed for a fair comparison of means to test hypothesis one. The statistical methods used to test hypothesis I a re described in detail in chapter five. On-line Survey Development I was fortunate to collaborate with the Shingo Prize team to conduct this study. Their advice on survey design and administrative techniq ues, and the access they provided to their Shingo database, greatly shape d the survey design and overall methodology of this study. It was the advice o f the executive director Dr. Ross Robson, Executive director of the Shingo Prize, tha t the survey be put online to ease distribution and enhance response rate. He had previous success sending out invitation surveys, with the link to the on-line survey within the body of the email, and requested that I take a similar appr oach. The committee agreed with this approach, and I was provided resource of Chris Paulus at USF to create an on-line version of the Melnyk survey. A cop y of the on-line survey can be seen in (table 8)

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155 An online data table was created to capture survey resp onses. A privacy code was established for each plant to anonymously key their survey responses to their Shingo Prize scoring system data. Point values fo r the Likert scales ranged from one to seven in section one and from one to fiv e for sections two and three. For clarity, scales for each section of the survey are list ed below with their point values in parentheses. The N/A response was recorded as a zero response to indicate that the respondent in fact chose this respons e, but was later changed to a non-value, so as not to skew the results. Scale for survey section 1: Green Management System (1) Not being considered (5) Currently implementing (2) Future consideration (6) Successfully implemented (3) Assessing Suitability (7) ISO14001 certified (4) Planning to implement ( ) Not applicable Scale for survey section 2: Green Waste Reducing Techniq ues Almost never Rarely Sometimes Often A lmost always N/A (1) (2) (3) (4) (5) ( ) Scale for survey section 3: Green Results Strongly Disagree Neither agree A gree Strongly N/A disagree nor disagree agree (1) (2) (3) (4) (5) ( )

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156 Table 8. On-line Survey Instrument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n V V W D I I K D V D F F H V V I \ R X K D Y H D Q \ T X H V W L R Q V S O H D V H F R Q W D F W P H D W R U J E H U J P L O O H U # \ D K R R F R P 7 K D Q N \ R X I R U W D N L Q J W K H W L P H W R F R P S O H W H W K L V L P S R U W D Q W V X U Y H \ Please enter your privacy code here: Please Read Instructions Carefully 1) For each question, please select the cell which best describes its status in your company (only one selection per row please) 2) Please collaborate with appropriate professional s in your organization as needed to assure accuracy in answering the following questions 3) Please answer all questions, if question does no t apply to your plant select "Not applicable" 4) Please press the "Submit Form" button when you h ave answered the last survey question 1. Status of your plant's Environmental Management Sy stem (ISO 14001): Not Being Considered Currently Implementing Future Consideration Successfully Implemented Assessing Suitability ISO14001 Certified Planning to implement Not Applicable If your plant's environmental management system is I SO14001 certified, how many years has that system been in place? 0-1 years.

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157 2. To what extent are the following environmental waste reducing techniques considered within your plant? Almo st Never Rarely SometimesOften Almost Always Not Applicable Product redesign: redesigning the product to eliminate any potential environmental problems (manufacturing or recycling) Process redesign: redesigning the process to eliminate any potential environmental problems Disassembly: redesigning the product or process so as to simplify disassembly and disposal at the end of the product's useful life Substitution: replacing a material which can cause environmental problems with another material which is not problematic Reduce: reducing the level of material and/or components (which are contributing to environmental problems) within products Recycling: making more use of recycled components or making a product which is more easily/readily recycled Remanufacturing: restoring used durable products to "new" condition, to be used in their original function, by replacing worn or damaged parts Consume internally: consuming waste interna lly (e.g. wood pallets used in shipping or product storage used to generate electrical power in cogeneration facility) Prolong Use: reducing environmental problems by increasing the overall life of the product (e.g. engines which last longer before having to be replaced or rebuilt) Returnable packaging: Using packaging and pallets which can be returned after they are finished being used Spreading Risks: shifting responsibilities for environmental problems to a third party or expert better able to deal with issues Creating a market for waste products: treating waste as an input to another product which can be made and sold at a profit Waste Segregation: an intermediate action in which waste streams are separated out into their individual components before being recycled, reused or consumed internally Alliances: working with either suppliers or consumers to address environmental problems and/or issues

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158 Table 8. (Continued) 3. Results: Environmental activities within your plant have : Strongly Disagree Disagree Neither Agree nor Disagree Agree Strongly Agree Not Applicable Significantly reduced overall costs Significantly reduced lead-times Significantly improved product quality Significantly improved its position in the marketplace Helped enhance the reputation of your company Helped your company design/develop better products Significantly reduced waste within the production process Significantly reduced waste within the equipment selection process Had benefits that have definitely outweighed any costs incurred Improved its chances of successfully selling its products in international markets Thank you very much. S ubmit Form R eset Form

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159 Survey Testing Upon completion of the on-line version of the survey, Chris Paulus and I tested the survey to assure the correct point values, for the L ikert scales were entered into the database. As a final test of content validi ty, the survey was sent to several Green manufacturing professionals and several Shi ngo prize examiners. The group of five experts confirmed that the survey st ruck a nice balance between brevity and depth, and was a survey instrument that would accurately assess Green manufacturing practices. Additionally, I solicited the help of ten associates to t ake the survey and offer a critique. The survey testers were asked to judge the sur vey on clarity, ease of use, and overall time required to take the survey. T he consensus view was that the survey was understandable and easy to use. Time to take the survey averaged around five minutes. Once tested, I submitted my research proposal and survey to the Institutional Review Board (IRB). Shortly thereafter, I received a list of eight issues requiring resolution, prior to their approval. After several weeks of collaboration with those referenced in the issues letter, I was able to receive f ormal approval to commence with the study (figure 14).

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160 November 9, 2006 RE: Exempt Certification for Application for Exemption IRB#: 103870 Title: Lean Manufacturers Transcendence To Green Manufacturing: Correlating the Diffusion of Lean and Green Manufacturing Systems Dear Dr. Bergmiller and Dr. Yalcin: On August 31, 2005, the Institutional Review Board (IRB) determined that your A pplication for Exemption MEETS FEDERAL EXEMPTION CRITERIA number two (2) and number four (4). It is your responsibility to ensure that this research is conducted in a manner consistent with the ethical principles outlined in the Belmont Report and in complia nce with USF IRB policies and procedures. Please note that changes to this protocol may disqualify it from exempt sta tus. It is your responsibility to notify the IRB prior to implementing any changes. The Division of Research Compliance will hold your exemption application for a pe riod of five years from the date of this letter or until a Final Review Report is received. If you wish to continue this protocol beyond the five-year exempt certification period, you wi ll need to submit an Exemption Certification Request form at least 30 days before this exempt certification expires. The IRB will send you a reminder notice prior to expiration of the certification; therefore, it is important that you keep your contact information current. Should you complete t his study prior to the end of the five-year period, you must submit an Application for Final Re view Please reference the above IRB protocol number in all correspond ence to the IRB or the Division of Research Compliance. In addition, we have enclosed an Institutional Review Board (IRB) Quick Reference Guide providing guidelines and resources to assist you in meeting your responsibilities when conducting human subjects research. Please read t his guide carefully. We appreciate your dedication to the ethical conduct of human subject resea rch at the University of South Florida and your continued commitment to the Human Research Protections Prog ram. If you have any questions regarding this matter, please call 813-974-9343. Sincerely, Paul G. Stiles, J.D., Ph.D. USF Institutional Review Board IA-EC-05-01 Figure 14. IRB approval

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161 Survey Administration and Data Collection Starting in November of 2005, email survey invitatio ns were sent to the representative at the plant who was the established con tact in the Shingo prize database. Recipients were encouraged to collaborate wi th environmental professionals at their facilities for accuracy. A unique privacy code was included in the body of the email and a link to the on-line su rvey. The survey initially was sent from the email address of the graduate student (P reston) at Utah State University (USU) tasked with adding privacy codes and sen d invitations. I was unable to send the emails, to assure anonymity of the p rivacy codes. The initial response to the emails was very poor, two or three responses. Upon discussion with the Shingo team and close examination of the email, it became evident that there were formatting problems and the recipients were probably unfamiliar with the email address associated with the i nvitation. Formatting issues were addressed, and Dr. Ross Robson (executive direct or) agreed to have the invitation letters sent from his email address. This greatly improved response rate in the month of December 2005. In January I was allowed to perform follow-up phone c alls. I was provided contact information, but not privacy codes. Upon reachi ng someone, I would ask them if they had received and retained the email inv itation. If not, I contacted Preston at USU to have him resend the email to this pe rson, with their unique privacy code. Roughly fifty percent of the contact inf ormation was invalid, as over the years these highly mobile professionals had mo ved on.

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162 In some cases I was forwarded to the environmental prof essional at the plant and some were willing to take the survey. Unfortunately, the advent of automated operators that require phone extensions, made this chall enging in many cases. The follow-up phone call process was very time consuming but yielded eleven more responses to the survey, making the effort well wo rth it. Once all reasonable email and phone call invitation options wer e exhausted, upon the committee members’ advice, Survey administration effort s terminated in February of 2006. The focus of the study no shifted t o analyzing the data. Sample Size and Statistical Analysis The unit of analysis for this study is the individual ma nufacturing plant. The reason for this decision is that two of the major extern ally validated measures (Shingo prize site visit scores and ISO14001 certification ), are administered at the plant level. The Shingo team limited access to p lants that had received site visits during the years from 2000 to 2005, to assure accur acy of the data. A total of one hundred-twenty plants were invited to take the survey of which fifty-one plants responded, and forty-seven responses were usable. This made for a survey response rate of thirty-nine percent. For the plants that participated in the study, the Shi ngo team graciously provided full and confidential access to the Shingo Prize scoring sy stem database. The data set from the survey was merged with the data from the Shingo prize scoring system, keyed by the privacy code. Prior to this point, I believed I would only have knowledge of the plants overall status (i.e. app licant, finalist, or prize

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163 recipient), and stated my hypotheses accordingly. Access t o the scoring system data allows for more complete correlation analysis at the sub-factor level and a much stronger dissertation study. Based on recommendations of my research committee, I purch ased SAS statistical software to analyze the data. Reliability of the data sets was confirmed using Cronbach’s coefficient Alpha tests and repeating fi ndings from previous Lean and Green studies. Hotelling’s T-tests was utilize d to test hypothesis I, comparing the means of the overall Shingo respondents to the means of the general manufacturing population, studied previously b y Melnyk et al. Pearson’s product moment correlation coefficients were utilized t o determine significant correlations between all variables in the study. Regr ession analysis was utilized to determine multi-variant effects on study variables. The complete statistical analysis is detailed in Chapter five: Data Analysis and Results. Chapter Summary This chapter explained the methods used to test the hy potheses associated with the research model defined in Chapter three. Chapte r four explained the steps to create and administer a Green manufacturing survey, who se data served as the set of dependent variables for the study. The survey was directed at known Lean manufacturing plants that had received site visits from Shingo prize examiners. The Shingo prize scoring system data served as the set of independent variables for the study. Control variables were also introduce d to minimize noise and account for external effects not controlled by this study. Data collection steps

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164 were explained in detail and statistical methods utili zed to analyze the data were summarized and will be described in detail in chapter f ive.

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165 Chapter Five Data Analysis and Results Introduction Lean manufacturing data from the Shingo prize scoring system database and Green manufacturing data collected from the on-line su rvey were analyzed to validate the data sets, test the four main hypotheses, and identify statistical relationships between sub-variables. Two statistical appr oaches were employed to validate both the Lean data set and the Green dat a set. The Cronbach coefficient alpha test was applied to all variables to a ssure the reliability of the measurement instrument for each variable. Secondly, co rrelation analysis was performed within the sets of Lean and Green variable s to confirm the results of earlier studies. Specifically, the analysis was intended to show that within both Lean and Green data sets, Management System scores corre late significantly to Waste Reducing Technique scores, which in turn correlate si gnificantly to Results scores. Hypothesis one utilized T-Tests to compare the statistics o f known Lean “Shingo” plants to the statistics of the general manufacturing p opulation, derived in the study where the Green manufacturing survey originated (Melnyk et. al., 2002). Hypotheses two through four were tested using Pearson’s p roduct moment correlation coefficient to determine significant correla tions between the main

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166 Lean and Green variables within the Shingo plant pop ulation. Full correlations analysis was performed between all sub-variables in the study to identify any possible correlations. Multi-variant regression analysi s was performed on all logical combinations of variables in the research model, to identify any possible multi-variant effects. All of this is described in detai l below. Presentation of Data The data set has two major subsets, one set obtained from the Shingo Prize scoring system database and one set obtained from the on -line survey. The independent and control variables are from the Shingo database, and the dependent variables are obtained from the Green on-l ine survey administered to the Shingo plants. The data sets were merged using th e unique privacy code provided in the Shingo team survey invitations to all eligible plants (received site visits between 2000 – 2005). There were a hundred an d ten plants that received the survey invitation, of which fifty-one plants resp onded, and forty-seven responses were usable. The simple statistics for the com plete data set are shown below in table 9. Table 9. Simple Statistics for Data Set Variable N Mean Std Dev Sum Minimum Maximum Quartile 47 2.53191 1.12000 119.000 1.00000 4.00000 Country 47 1.21277 0.41369 57.000 1.00000 2.00000 Year 47 2004 1.27960 94169 2001 2005 IA 47 59.68085 6.30082 2805 45.00000 69.00000 IB 47 54.14894 8.83171 2545 32.00000 67.00000 LMS 47 113.82979 14.06247 5350 79.00000 136.00000 IIA 47 38.70213 4.48143 1819 25.00000 45.00000

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167 Table 9. (Continued) Variable N Mean Std Dev Sum Minimum Maximum IIB 47 38.48936 5.04705 1809 22.0000 53.00000 IIC 47 65.76596 12.08163 3091 34.0000 90.00000 IID 47 181.34043 21.86746 8523 123.00000 220.00000 III 47 79.97872 13.73901 3759 50.00000 106.00000 LWRT 47 404.27660 36.27534 19001 288.00000 471.0000 0 IVA 47 57.51064 6.49372 2703 44.00000 71.00000 IVB 47 57.29787 6.46702 2693 30.00000 71.00000 IVC 47 60.17021 7.47843 2828 41.00000 71.00000 V 47 59.85106 6.77906 2813 45.00000 70.00000 LR 47 234.82979 18.14353 11037 185.00000 274.00000 LEAN 47 752.93617 56.11456 35388 568.00000 851.0000 0 GMS1 47 5.82979 2.24886 274.00000 1.00000 7.00000 GMS2 47 3.57447 2.84181 168.00000 0 10.00000 GMS 47 9.40426 4.62347 442.00000 1.00000 17.00000 GWRT1 42 3.61905 1.01097 152.00000 1.00000 5.00000 GWRT2 46 4.17391 0.76896 192.00000 2.00000 5.00000 GWRT3 42 3.02381 1.23936 127.00000 1.00000 5.00000 GWRT4 47 4.12766 0.92353 194.00000 1.00000 5.00000 GWRT5 46 3.97826 0.82970 183.00000 1.00000 5.00000 GWRT6 46 3.82609 1.17954 176.00000 1.00000 5.00000 GWRT7 41 2.90244 1.26105 119.00000 1.00000 5.00000 GWRT8 42 3.00000 1.22971 126.00000 1.00000 5.00000 GWRT9 44 3.54545 1.17046 156.00000 1.00000 5.00000 GWRT10 47 4.19149 0.96995 197.00000 1.00000 5.00000 GWRT11 42 3.26190 1.06059 137.00000 1.00000 5.00000 GWRT12 40 3.17500 1.41217 127.00000 1.00000 5.00000 GWRT13 45 4.37778 0.80591 197.00000 1.00000 5.00000 GWRT14 47 3.72340 1.05711 175.00000 1.00000 5.00000 GWRT 47 3.66474 0.62402 172.24274 1.78571 4.64286 GR1 47 3.91489 0.85541 184.00000 2.00000 5.00000 GR2 42 3.09524 0.82075 130.00000 2.00000 5.00000 GR3 46 3.43478 0.98098 158.00000 2.00000 5.00000 GR4 47 3.63830 0.81895 171.00000 2.00000 5.00000 GR5 47 4.29787 0.62258 202.00000 3.00000 5.00000 GR6 45 3.62222 0.88649 163.00000 2.00000 5.00000 GR7 47 4.19149 0.79778 197.00000 2.00000 5.00000 GR8 47 3.74468 0.79312 176.00000 2.00000 5.00000 GR9 46 3.93478 0.67994 181.00000 2.00000 5.00000 GR10 47 3.87234 0.82402 182.00000 2.00000 5.00000 GR 47 3.78457 0.54886 177.87500 2.80000 4.80000 GREEN 47 0.68102 0.12841 32.00785 0.35199 0.89238

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168 Validation of Data Two statistical approaches were employed to validate bo th the Lean data set (independent variables) and the Green data set (dep endent variables). The Cronbach coefficient alpha test was applied to all varia bles to assure reliability of the measurement instrument for each variable. Secondly correlation analysis was performed within the data sets of dependent and in dependent variables to confirm the results of earlier studies (i.e. Management System scores correlate significantly to Waste Reducing Technique scores, which in turn correlate significantly to Results scores). The Cronbach coefficient alpha test was performed for all 48 variables in the study to assure r eliability of each variable as a measurement instrument. The following is a brief de scription of the Conbrach coefficient alpha test: Cronbach's coefficient alpha estimates the reliability of the scale by determining the internal consistency of the test or the average correlation of items within the test (Cronbach 1951). Repeated me asurements for a series of individuals will show some consistency. Reliabili ty measures internal consistency from one set of measurements to anot her. The observed value Y is divided into two components, a true value T and a measurement error E The measurement error is assumed to be independent of the true value, that is, Y = T + E Cov ( T E ) = 0 The reliability coefficient of a measurement test is d efined as the squared correlation between the observed value Y and the true value T that is, r 2 ( Y T ) = [( Cov ( Y T ) 2 )/ V ( Y ) V ( T )] = [( V ( T ) 2 )/ V ( Y ) V ( T )] = [ V ( T )/ V ( Y )] which is the proportion of the observed variance due to true differences among individuals in the sample. If Y is the sum of several observed variables measuring the same feature, you can estimate V ( T ). Cronbach's coefficient alpha, based on a lower bound for V ( T ), is an estimate of the reliability coefficient.

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169 When the correlation between each pair of variables is 1, the coefficient alpha has a maximum value of 1. With negative correl ations between some variables, the coefficient alpha can have a value l ess than zero. The larger the overall alpha coefficient, the more li kely that items contribute to a reliable scale. Nunnally and Bernstein (1994) suggests 0.70 as an acceptable reliability coefficient; smaller reliability coefficients are seen as inadequate. Listwise deletion of observations with missing values is ne cessary to correctly calculate Cronbach's coefficient alpha. PROC COR R does not automatically use listwise deletion if you specify the A LPHA option. Therefore, you should use the NOMISS option if the d ata set contains missing values. (SAS, 2006) As suggested the NOMISS ALPHA function was utilized to a void missing values and assure the statistical power of the Cronbach test. A ll variables utilized in the study exceeded the 0.70 reliability coefficient threshol d (Nunnally, Bernstien, 1994), indicating acceptable reliability of the entire data set. Table 10 shows Cornbach coefficient alphas for all forty-eight variabl es utilized in this study. Table 10. Cronbach Coefficient Alphas for Variables Cronbach Coefficient Alpha Variables Alpha Raw 0.792510 Standardized 0.889711 Cronbach Coefficient Alpha wi th Deleted Variable Raw Variables Standardiz ed Variables Deleted Correlation Correlation Variable with Total Alpha with Total Alpha Quartile 0.843355 0.790260 0.465505 0 .886116 Country -.024788 0.792897 0.390706 0 .887164 Year -.002980 0.792935 -.238800 0.8 95672 IA 0.678571 0.782981 0.051250 0.8918 21 IB 0.587173 0.781509 0.236300 0.8893 02

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170 Table 10. (Continued) Deleted Correlation Correlation Variable with Total Alpha with Total Alpha LMS 0.687847 0.773178 0.183555 0.890 025 IIA 0.546041 0.786183 -.078742 0.89 3561 IIB 0.496145 0.785355 -.033785 0.89 2962 IIC 0.158174 0.791676 -.191657 0.89 5054 IID 0.739818 0.760231 0.222568 0.88 9491 III 0.440988 0.781589 0.361629 0.88 7569 LWRT 0.832434 0.747897 0.215885 0.8 89583 IVA 0.444998 0.784998 0.307940 0.88 8314 IVB 0.432834 0.785406 0.589458 0.88 4361 IVC 0.268346 0.788747 0.164639 0.89 0283 V 0.360804 0.786802 0.205377 0.8897 27 LR 0.538862 0.774057 0.500710 0.885 620 LEAN 0.983572 0.762830 0.387892 0.8 87203 GMS1 0.333967 0.790719 0.549172 0.8 84934 GMS2 -.040153 0.793476 0.293940 0. 888508 GMS 0.128559 0.791808 0.452676 0.88 6296 GWRT1 -.153083 0.793297 0.215652 0.8 89586 GWRT2 -.157822 0.793212 0.166796 0.8 90254 GWRT3 -.075067 0.793177 0.582088 0.8 84466 GWRT4 0.101925 0.792617 0.531179 0.8 85189 GWRT5 0.117954 0.792638 0.444371 0.8 86413 GWRT6 0.117166 0.792522 0.366231 0.8 87505 GWRT7 -.029964 0.793030 0.347065 0.8 87772 GWRT8 0.084889 0.792642 0.476089 0.8 85967 GWRT9 0.106873 0.792572 0.504106 0.8 85572 GWRT10 0.136777 0.792546 0.468129 0. 886079 GWRT11 0.020822 0.792841 0.215022 0. 889594 GWRT12 0.166331 0.792256 0.492246 0. 885739 GWRT13 0.183284 0.792428 0.398746 0. 887052 GWRT14 -.137190 0.793318 0.502528 0. 885594 GWRT 0.071505 0.792757 0.760716 0.8 81900 GR1 -.051243 0.793024 0.489833 0.88 5773 GR2 -.177066 0.793357 0.420145 0.88 6752 GR3 -.466179 0.794177 0.200611 0.88 9792 GR4 0.126283 0.792589 0.613550 0.88 4017 GR5 -.151506 0.793142 0.451020 0.88 6319 GR6 -.044812 0.793015 0.443063 0.88 6431 GR7 0.102847 0.792670 0.498411 0.88 5652 GR8 0.106427 0.792651 0.538520 0.88 5085 GR9 0.096134 0.792685 0.468108 0.88 6079 GR10 -.123914 0.793180 0.262671 0.8 88940 GR -.091637 0.793033 0.632830 0.883 742 GREEN 0.108041 0.792828 0.744730 0.8 82131

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171 The other method used to validate the data set was t o verify significant correlations within Lean and Green manufacturing system main variables, identified by previous research efforts found in the li terature review. Both Lean and Green literature indicate that the Management Sy stem correlates strongly to the Waste Reducing Techniques, which in-turn correlate str ongly to Results [(Melnyk, et. al. 2003)(Russo, 2001)(SAE, 1999)(Shingo 2006)]. While there is no attempt at proving causality in this study, I was abl e to show significant correlation between the main variables as stated above The SAS PROC CORR (process correlation) function was util ized to determine correlation between independent and dependent variab les. SAS primarily utilizes the Pearson product-moment correlation to compute “Pe arson correlation coefficient” between the main Lean variables and betwe en the main Green variables in question. As required SAS may apply addi tional correlation methods in addition to the Pearson product-moment correlation function when the PROC CORR function is invoked. The SAS correlation methods associated with the PROC CORR function are summarized below: The Pearson product-moment correlation is a parametric m easure of association for two variables. It measures both the streng th and direction of a linear relationship. If one variable X is an exa ct linear function of another variable Y, a positive relationship exists if t he correlation is 1 and a negative relationship exists if the correlation is -1. If there is no linear predictability between the two variables, the correlat ion is 0. If the two variables are normal with a correlation 0, the two va riables are independent. However, correlation does not imply causali ty because, in some cases, an underlying causal relationship may not exist Probability values for the Pearson correlation are computed by tre ating t = ( n -2) 1/2 ([( r 2 )/(1r 2 )]) 1/2 as coming from a t distribution with ( n -2) degrees of freedom, where r is the sample correlation.

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172 Spearman rank-order correlation is a nonparametric measu re of association based on the ranks of the data values. PROC C ORR computes the Spearman correlation by ranking the data and using the ranks in the Pearson product-moment correlation formula In case of ties, the averaged ranks are used. Probability values for th e Spearman correlation are computed by treating t = ( n -2) 1/2 ([( r 2 )/(1r 2 )]) 1/2 as coming from a t distribution with ( n -2) degrees of freedom, where r is the sample Spearman correlation. Kendall's tau-b correlation coefficient is a nonparametr ic measure of association based on the number of concordances and discordan ces in paired observations. Concordance occurs when paired observa tions vary together, and discordance occurs when paired observations v ary differently. PROC CORR computes Kendall's tau-b by ran king the data and using a method similar to Knight (1966). The data are double sorted by ranking observations according to values of the firs t variable and reranking the observations according to values of the second variable. PROC CORR computes Kendall's tau-b from the number of interchanges of the first variable and corrects for tied pairs (pai rs of observations with equal values of X or equal values of Y). (SAS, 2006) Table 11 summarizes the results of performing the SAS PROC CORR function on the main Lean variables. The table shows significan t correlation between the Lean Management System main variable (LMS) and the L ean Waste Reducing Techniques main variable (LWRT), and significant corre lation between LWRT and the Lean Results main variable (LR).

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173 Table 11. Correlation of Lean Main Variables Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum LMS 47 113.82979 14.06247 5350 79.00000 136.00000 LWRT 47 404.27660 36.27534 1 9001 288.00000 471.00000 LR 47 234.82979 18.14353 11037 185.00000 274.00000 Pearson Correlation Coefficients, N = 47 Prob > |r| under H0: Rho=0 Variable Label LMS LWRT LR LMS LMS 1.00000 0.63618 <.0001**** 0.26044 0.0771 LWRT LWRT 0.63618 <.0001**** 1.00000 0.39812 0.0056** LR LR 0.26044 0.0771 0.39812 0.0056** 1.00000 Significance *P<0.05 ** P<0.01 ***P<0.001 ****P<0.000 1 Table 12 summarizes the results of performing the SAS PROC CORR on the main Green variables and controls. The table shows sign ificant correlation between the Green Management System (GMS) main varia ble and the Green Waste Reducing Techniques (GWRT) main variable, and sig nificant correlation between GWRT and the Green Results (GR) main variabl e. Thus, the two forms of validation (Cronbach alpha and Pearson correlatio n) suggest that although the data set is relatively small it is statistically strong. Thus, the data set is worthy of

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174 further statistical analysis regarding the study’s main hy potheses and other possible relationships within the data sets variables. Table 12. Correlation of Green Main Variables Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum GMS 47 9.40426 4.62347 442.00000 1.00000 17.00000 GWRT 47 3.66474 0.62402 172.24274 1.78571 4.64286 GR 47 3.78457 0.54886 177.87500 2.80000 4.80000 Pearson Correlation Coeff icients, N = 47 Prob > |r| un der H0: Rho=0 Variable Label GMS GWRT GR GMS GMS 1.00000 0.33442 0.0216* 0.19376 0.1919 GWRT GWRT 0.33442 0.0216* 1.00000 0.45715 0.0012** GR GR 0.19376 0.1919 0.45715 0.0012** 1.00000 Significance *P<0.05 ** P<0.01 ***P<0.001 ****P<0.000 1

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175 Hypothesis Testing The four main hypotheses are described in detail in Cha pter 4: Methodology. For ease of reference they are restated with a detailed d escription of how each hypothesis was tested and the test results. Hypothesis I is unique in that it compares the environmental performance of the set of Shingo plants with the set of general manufacturers surveyed originally in the Me lnyk study a few years earlier. The intent of this hypothesis is to show that known Lean manufacturers are exhibiting significantly higher levels of environm ental practices and results than the general manufacturing population. This woul d show evidence of Lean manufacturers’ transcendence to Green manufacturing. Hypothesis I: Lean manufacturers, as recognized by the S hingo Prize team of examiners, are Greener than the general population o f manufacturers, identified in the Melnyk study. Hypothesis I, was tested by performing T-tests, utilizin g the statistics available from the Melnyk study original data set and the Shing o data set for all twenty-six green variables surveyed. Table 13 shows the results of the T-Tests. Notice that for all three main variables and their respective sub-v ariables, the known Lean Shingo companies are significantly “Greener” than the g eneral population of manufacturing plants. These strong results clearly indica te that Hypothesis I is true with a very high level of statistical significance.

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MelnykShingoSignificanceFactorLabelNMeanSDNMeanSDtpSignificanceISO14001 certifiedGMS115100.083470.7870.225 Meaningful difference Years certifiedGMS215100.917473.5742.842 Meaningful difference Product redesignGWRT111632.9961.228423.6191.0113.24 80.0012 ** Process redesignGWRT211663.3801.164464.1740.7694.58 60.0000 **** DissassemblyGWRT311552.6121.208423.0241.2392.1680.0 303 SubstitutionGWRT411633.4081.220474.1280.9243.9970.0 001 **** ReduceGWRT511603.3281.212463.9780.8303.6050.0003 *** RecyclingGWRT611653.1921.276463.8261.1803.3150.0009 *** RemanufacturingGWRT711482.6641.248412.9021.2611.202 0.2297 Consume InternallyGWRT811632.4641.196423.0001.2302. 8510.0044 ** Prolong UseGWRT911543.0041.592443.5451.1702.2330.02 58 Returnable PackagingGWRT1011623.3241.292474.1910.97 04.5510.0000 **** Spreading RisksGWRT1111532.7761.156423.2621.0612.68 30.0074 ** Creating marketsGWRT1211562.6961.228403.1751.4122.4 130.0160 Waste SegregationGWRT1311613.2121.220454.3780.8066. 3550.0000 **** AlliancesGWRT1411542.9841.220473.7231.0574.0920.000 0 **** Reduced costsGR111422.3401.028473.9150.85510.3550.0 000 **** Reduced lead-timesGR211432.0840.912423.0950.8217.08 10.0000 **** Improved product qualityGR311442.2961.012463.4350.9 817.4920.0000 **** Improved market positionGR411402.3921.080473.6380.8 197.8180.0000 **** Enhanced reputationGR511442.9401.236474.2980.6237.4 900.0000 **** Improved product designGR611442.4401.108453.6220.88 67.0680.0000 **** Reduced process wasteGR711442.8921.196474.1910.7987 .3800.0000 **** Improved equipment selectionGR811332.6081.116473.74 50.7936.9090.0000 **** Benefits outweigh costsGR911382.6841.132463.9350.68 07.4380.0000 **** Improved international salesGR1011332.4921.156473.8 720.8248.1000.0000 **** 17 6 Significance *P<0.05 **P<0.01 ***P<0.001 ****P<0.0001 Table 13. T-Test Results for Hypothesis I

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177 Hypotheses II through IV are internally focused within the Shingo plants that responded to the survey. Respectively, these hypotheses relate to correlation between a plant’s level of “Leanness” (LEAN) and its l evel of “Greenness” measured from the perspectives of the management system (GMS), waste reducing techniques (GWRT), and results (GR). The ind ependent LEAN variable is the total score from the Shingo Prize Scoring system. The Green dependent variables are taken from the three sections of the su rvey, each being the average score for that section. For ease of reference the hypot heses are listed below followed by a description of how the hypotheses were te sted and the results of these tests. Hypothesis II: The overall Lean score (LEAN), as measur ed by the Shingo Prize examiners, positively correlates to the Green Manageme nt System score (GMS), as measured by the on-line Green survey. Hypothesis III: The overall Lean score (LEAN), as measured by the Shin go Prize examiners, positively correlates to the Green Waste Re ducing Techniques score (GWRT), as measured by the on-line Green survey. Hypothesis IV: The overall Lean score (LEAN), as measured by the Shin go Prize examiners, positively correlates to the Green Res ults score (GR), as measured by the on-line Green survey. Hypothesis II through Hypothesis IV were tested utilizi ng Pearson’s product moment correlation coefficient tests and looking for pr obability (P-values ) less

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178 than 0.05 to determine significant correlation between the LEAN and GMS, GWRT, and GR. The control variables Quartile, Countr y, and Year were also included in the correlation matrix to determine if t here was significant influence by these factors. The correlation matrix for testing hyp otheses II – IV is shown below in table 14. Notice that P values less that 0.0 5 were not found between LEAN and GMS, GWRT, or GR, thus I was unable to prove these hypotheses statistically. Table 14. Correlation Matrix for Hypotheses II IV Pearson Correlation Coefficients, N = 47 Prob > |r| under H0: Rho=0 Quartile Country Year LEAN GMS GWRT GR Quartile Quartile 1.00000 0.12578 0.3995 -0.05906 0.6933 0.84040 <.0001**** 0.08352 0.5768 0.11968 0.4230 0.16256 0.2750 Country Country 0.12578 0.3995 1.00000 0.12495 0.4027 0.05960 0.6907 0.20410 0.1688 0.38688 0.0072** 0.46051 0.0011 Year Year -0.05906 0.6933 0.12495 0.4027 1.00000 -0.03004 0.8411 -0.21797 0.1411 -0.22244 0.1329 -0.17063 0.2515 LEAN LEAN 0.84040 <.0001**** 0.05960 0.6907 -0.03004 0.8411 1.00000 -0.00534 0.9716 0.10754 0.4718 0.03308 0.8253 GMS GMS 0.08352 0.5768 0.20410 0.1688 -0.21797 0.1411 -0.00534 0.9716 1.00000 0.33442 0.0216* 0.19376 0.1919 GWRT GWRT 0.11968 0.4230 0.38688 0.0072** -0.22244 0.1329 0.10754 0. 4718 0.33442 0.0216* 1.00000 0.45715 0.0012** GR GR 0.16256 0.2750 0.46051 0.0011** -0.17063 0.2515 0.03308 0.8253 0.19376 0.1919 0.45715 0.0012** 1.00000 Significance *P<0.05 ** P<0.01 ***P<0.001 ****P<0.000 1

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179 Full Correlation and Regressions Analysis Due to the fact that hypotheses II – IV could not be proven true, there was a desire to look more deeply into the sub-variables of th e study to unearth any interesting findings. This analysis was conducted in two ways: First a full correlation analysis was performed using Pearson’s product moment correlation coefficient on all main and sub-variables in the study. Of greatest interest for this study is the full correlation of all Lean variables and controls versus all Green variables. The second approach taken was to conduct re gression analysis on all logical combinations of main variables on other main v ariables of the research model. This was an attempt to see if combinations of va riables were strong predictors of other variables in the study. Full Correlation Analysis Table 15 shows the full correlation matrix for all Lea n, Green and control variables. The letters “p” and “n” denote positive an d negative correlations, respectively. The number of n’s or p’s denotes the leve l of significance (see bottom of table 15 for detail). Several interestin g findings can be observed directly from this correlation matrix. These finding s are organized along the left hand axis of table 15, in the following categories: Control variables Lean management system variables Lean waste reducing technique variables Lean result variables

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LABELSGMS1GMS2GMSGWRT1GWRT2GWRT3GWRT4GWRT5GWRT6GWRT7GWRT8GWRT9GWRT10GWRT11GWRT12GWRT13GWRT14GWRTGR1GR2GR3GR4GR5GR6GR7GR8GR9GR10GRGREENVARIABLESEMS/ISO14001 statusYears CertifiedTotal Green mngmt SystemProduct redesignProcess redesignDissassemblySubstitutionReduceRecyclingRemanufacturingConsume InternallyProlong UseReturnable PackagingSpreading RisksCreating marketsWaste SegregationAlliancesTotal Green Waste Reducing TechniquesReduced costsReduced lead-timesImproved product qualityImproved market positionEnhanced reputationImproved product designReduced process wasteImproved equipment selectionBenefits outweigh costsImproved international salesTotal Green ResultsTotal Green scoreQuartileQuartile of "Lean" scores Country Country plant locatedppppppppppppppppppppppppYear Shingo assessment year nnnnn IA Leadership n IB Empowerment LMS Total Lean Mngmt System IIA Vision/Strategy n n IIB Innovation nnn IIC Partnerships nnnnn n IID Operations nn III Support functionsppppp ppLWRT Lean Waste Reducing Techniques n IVA QualitypIVB CostpppppppppppppppIVC DeliverypV Customer Satisfaction & ProfitibilityppppLR LRppppppLEAN Total Lean score n GREEN DEPENDENT VARIABLES FROM SURVEYCONTROL VARIABLES LEAN INDEPENDENT VARIABLES FROM SHINGO PRIZE SCORIN G SYSTEM DATA BASE 180 Significance Positive (p)P<0.05 (pp) P<0.01 (ppp)P< 0.001 (pppp)P<0.0001, Negative(n)P<0.05 (nn) P<0.01 (nnn)P<0.001 (nnnn)P<0.0001 Table 15. Full Lean and Green Correlation Matrix

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181 Control variables Control variable Quartile is the quartile that overall Lean score falls into fro m the lowest scores (Q1) to the highest scores (Q4). It was added to determine if there were differences between quartile groups of plants, as o pposed to the continuous variable Lean. There were no correlations between Q uartile and the Green variables. Control variable Country significantly correlates to the main variables GWRT and GR, and logically to many of their sub-variables. The interesting finding here is that the country that is highly correlated to these Gre en practices and results is Mexico and not the United States. Specifically the Me xican plants show significantly higher adoption rates of the following G reen waste reducing techniques and corresponding Green results: GWRT8: Consuming waste internally GWRT10: Use of returnable packaging GWRT12: Creating markets for waste GWRT13: Segregating waste GWRT14 Creating alliances GWRT: Overall adoption of Green waste reducing techni ques GR3: Improved product quality GR4: Improved market position GR5: Enhanced reputation GR8: Improved equipment selection GR10: Improved international sales GR: Overall Green results

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182 Control Variable Year indicates the year the Shingo assessment was performed. Year correlates negatively and significantly to the fol lowing Green waste reducing techniques: GWRT1: Product redesign GWRT3: Disassembly GWRT5: Reduce Lean Management System Variables There was only one significant correlation between Lean management system variables and all of the Green variables on the study. Lean management system variable Leadership (IA) negatively and significantly correlated to Green resu lts variable GR3: Improved product quality – as a result of Green efforts. Lean Waste Reducing Technique Variables There are several negative correlations between Lean w aste reducing techniques (LWRTs) and sub-variables of GMS, GWRT, and G R. There are also several positive correlations between the LWRT variable (III) Support functions and Green variables in all three Green categories. Sp ecifically the correlations regarding Lean waste reducing technique variables and the Green variables are listed below: IIA: Vision/Strategy negatively correlates to: GMS2: Years of ISO14001 certification GR3: Improved quality as a result of Green efforts IIB: Innovation negatively correlates to: Recycling (GWRT6)

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183 Remanufacturing (GWRT7) Alliances (GWRT8) IIC: Partnerships negatively correlates to: Years of ISO14001 certification (GMS2) Over all Green management system (GMS) Product re-design (GWRT1) Disassembly (GWRT3) Total Green Score (Green) IID: Operations negatively correlates to: Improved product quality, through green efforts (G R3) III: Support Functions positively correlates to: ISO14001 certifications (GMS1) Over all Green management system (GMS) Product redesign (GWRT1) Disassembly (GWRT3) Enhanced reputation (GR5) Total Green Score (GREEN) LWRT: Overall Lean waste reducing technique score negatively correlates to: Improved quality (GR3), as a result of Green efforts Lean Results Variables There are many positive correlations between Lean resul ts (LR) and GMS, GWRT, and GR. It is interesting to note that these Le an results were measured prior to the survey by the Shingo team, with no tho ught to environmental activities within the plant being examined. Specifica lly the correlations between Lean results variables and Green variables are as follow s: IVA: Quality positively correlates to: GMS1: ISO14001 implementation level IVB: Cost positively correlates to: GMS1: ISO14001 implementation level

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184 GMS: Over all Green management system GWRT4: Substitution GWRT10: Returnable packaging GWRT12: Creating markets GWRT13: Waste segregation GWRT: Over all Green waste reducing techniques GR8: Improved equipment selection, by green efforts GREEN: Overall Green score IVC: Delivery positively correlates to: GWRT12: Creating markets V: Customer satisfaction & Profitability positively c orrelates to: GWRT4: Substitution GWRT9: Prolong Use GWRT12: Creating markets GWRT13: Waste segregation LR: Overall Lean results positively correlates to: GMS1: ISO14001 certification GWRT4: Substitution GWRT12: Creating Markets GWRT13: Waste segregation GWRT: Overall Green waste reducing techniques LEAN: Overall Lean score negatively correlates to: GR3: Improved quality, as a result of Green efforts The full correlation analysis yielded many interesting findings that will be discussed in Chapter six. There were several cases of both positive and negative correlations on similar sets of variables indicat ing the potential of confounding effects. This led to the use of more advan ced analysis to identify multi-variant effects. Regression analysis was also perfor med on many of the variables in the data set and is presented below.

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185 Multi-variant Regression Analysis Initial review of the correlation data with committee members revealed that hypotheses II – IV, regarding main Lean and Green va riables within the Shingo data set, were not proven. This led to conversation r egarding multivariate effects within the model of combinations of Lean and Green variables on all other model variables. In order to understand the effects of multi ple independent variables on a dependent variable, multi-variant regression analysi s was performed using logical combinations of Lean and Green main variables as the independent variables and all individual main variables as the dep endent variables. The SAS PROC REG function was utilized for this analysis. Regre ssion analysis was performed on the following combinations of main varia bles from the Lean and Green research model in table 16. Model significance is summarized for each combination of independent variables with respect to th e dependent variables.

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186 Table 16. Multi-variant Regression Statistics Dependent Variable Independent Variables Model Pr > F GMS LEAN, GREEN <0.0001 **** GMS LMS, GWRT 0.0733 GMS LMS, GR 0.4119 GMS LWRT, GWRT 0.0666 GMS LWRT, GR 0.4115 GMS LR, GWRT 0.0735 GMS LR, GR 0.3608 GWRT LEAN, GREEN <0.0001 **** GWRT LMS, GMS 0.0697 GWRT LMS, GR 0.0046 ** GWRT LWRT, GMS 0.0668 GWRT LWRT, GR 0.0053 ** GWRT LR, GMS 0.0145 GWRT LR, GR 0.0010 *** GR LEAN, GREEN 0.0002 *** GR LMS, GMS 0.3814 GR LMS, GWRT 0.0045 *** GR LWRT, GMS 0.4306 GR LWRT, GWRT 0.0056 ** GR LR, GMS 0.3963 GR LR, GWRT 0.0053 ** LMS LEAN, GREEN <0.0001 **** LMS GMS, LWRT <0.0001 **** LMS GMS, LR 0.1967 LMS LWRT, GWRT <0.0001 **** LMS LR, GWRT 0.1364 LMS LR, GR 0.2028 LWRT LEAN, GREEN <0.0001 ****

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187 Table 16. (Continued) LWRT GMS, LMS <0.0001 **** LWRT GMS, GR 0.0182 ** LWRT LMS, GWRT <0.0001 **** LWRT LMS, GR <0.0001 **** LWRT LR, GWRT <0.0198 LWRT LR, GR 0.0212 LR LEAN, GREEN <0.0001 **** LR GMS, LMS 0.1588 LR GMS, LWRT 0.0151 ** LR LMS, GR 0.1942 LR LWRT, GR 0.0185 ** LR LWRT, GWRT 0.0032 ** LR LMS, GWRT 0.0229 Generally speaking, for each of the regression combinatio ns, model significance (P value) was influenced solely by the independent va riables from the same manufacturing system as the dependent variable. That is to say, the Lean independent variables in the model influenced model si gnificance for Lean dependent variables, and Green independent variables influenced model significance for Green dependent variables. This is evid ent by the lack of significant P values for the predictor variable not fro m the same manufacturing system as the dependent variable. However, in two cases both the Lean and Green indepen dent variables were significant, as well as the overall model, for the depe ndent variable LR (Lean results). In both cases, the Green independent variab le was GWRT (Green

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188 waste reducing techniques). The Lean independent vari ables were LMS (Lean management system) and LWRT (Lean waste reducing techniq ues). These results indicate with a high level of significance that G WRT and LMS, and GWRT and LWRT are strong predictors of Lean results (LR). Interestingly, GWRT had a substantially higher P valu e than LMS, indicating that Green waste reducing techniques is a stronger predictor of Lean results than the Lean management system. This surprising result will be discussed further in chapter 6. Given the significance of these findings, t he regression outputs for these two cases are listed below in tables 17 and 18.

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189 Table 17. Regression Results of LR with GWRT and LWRT P redictors The REG Procedure Model: MODEL1 Dependent Variable: LR LR Number of Observations Read 47 Number of Observations Used 47 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 2 3474.20587 1737.10294 6.55 0 .0032 Error 44 11668 265.19165 Corrected Total 46 15143 Root MSE 16.28471 R-Square 0 .2294 Dependent Mean 234.82979 Adj R-Sq 0.1944 Coeff Var 6.93468 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > | t| Intercept Intercept 1 128.41259 29. 79103 4.31 <.0001 GWRT GWRT 1 7.75204 3.85 183 2.01 0.0503 LWRT LWRT 1 0.19296 0.06 626 2.91 0.0056

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190 Table 18. Regression Results of LR with GWRT and LMS Pr edictors The REG Procedure Model: MODEL1 Dependent Variable: LR LR Number of Observations Read 47 Number of Observations Used 47 Analysis of Variance Sum o f Mean Source DF Squares Square F Value Pr > F Model 2 2388.40054 1194.2002 7 4.12 0.0229 Error 44 12754 289.86904 Corrected Total 46 15143 Root MSE 17.02554 R-Square 0 .1577 Dependent Mean 234.82979 Adj R-Sq 0.1194 Coeff Var 7.25016 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > |t| Intercept Intercept 1 162.05991 25.93854 6.25 <.0001 GWRT GWRT 1 8.73196 4.02934 2.17 0.0357 LMS LMS 1 0.35816 0.17880 2.00 0.0513 Chapter Summary This concludes the Data Analysis and results chapter. The analysis and results presented in this chapter will be discussed in detail in the following chapter six.

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191 Chapter Six Discussion of Results Introduction Since the 1990’s researchers have set out to better under stand the relationship between Lean and Green manufacturing systems, given th at both systems focus centrally on the elimination of waste. This dissertati on contributes to the Lean and Green body of knowledge by determining if Lean m anufacturers adopt Green manufacturing system best practices. To restate the resea rch question: Do Lean manufacturers transcend to Green manufacturing? The population of known Lean manufacturing plants (Sh ingo) was compared to the general population of manufacturing plants (Melny k), as stated in hypothesis I. The results are clear that Lean plants adopt signif icantly higher levels of Green manufacturing best practices than the general populatio n. Yet, when comparing adoption levels of Green manufacturing best practices at a high level within the Shingo plant population, as identified in hypotheses 2 – 4, the results are inconclusive. This is very much the result of comparing b est practice variables at a categorical (main variable) level between Lean and Green systems. However, full correlation and regression of the sub-va riables that constitute the main Lean and Green variables of the study yield strong evidence of not only

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192 transcendental behavior, but that synergy exists between Lean and Green manufacturing systems. Specifically, Green best practices p ositively correlate to both Green and Lean results at the sub-variable level. Analysis also yielded some interesting findings related to plant’s choice to v ertically or horizontally integrate its Lean systems and the dichotomous correlation this had to Green system variables. There are indications that a myopic f ocus on Lean at the management system and strategic levels may detract from t ranscendence to Green manufacturing, and perception of Green results. There were also some rather counter-intuitive findings related to the count ry of plant location, all of which are described in detail below. Validation of Data Discussion The data sets for the study were validated in two way s, first by performing the Cronbach reliability tests and secondly by reproducing t he results of early studies regarding the relationship of the main variables to each other. The Cronbach test showed high levels of reliability, thereby indicating that the data sets, albeit small, were statistically powerful and worthy of correlation a nd regression analysis. The more interesting result was how I was able to reproduce the findings of earlier research regarding the relationship of the management system to the implementation of waste reducing techniques and their r elationship to results. Melnyk et. al. (2003), were able to prove that the G reen Management System (i.e. ISO14001) strongly correlated to the Green waste reducing techniques and that the Green waste reducing techniques strongly corre lated to Green results,

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193 with the same survey instrument utilized in this dissert ation study. As shown in table 12 of chapter five, the results were reproduced for the forty-seven Shingo plant data set, which was much smaller than the roughly eleven hundred plant data set from the Melnyk et. al. study. This is very str ong validation that the data set for this study holds sufficient statistical power. Similar results were found regarding the relationship between the Lean variables LMS, LWRT and LR. That is to say, table 11 shows signif icant correlation between the Lean management system (LMS) and Lean wast e reducing techniques (LWRT), and significant correlation between LWRT and Lean results (LR). Unfortunately, there is no previous study that utilized the exact same criteria to produce these results originally, as was don e for the Green study (Melnyk et. al., 2003). However, all leading models of the Lean manufacturing system specifically indicate the critical importance of the Lean management system creating the environment for Lean waste reducing techniques to take hold, and the how results only come from continuous impl ementation and sustaining of Lean waste reducing techniques. (Liker, 20 04) (Shingo, 2003) (SME, 2006) Hypothesis Testing Discussion Hypothesis I was unique in that it compared the Green s urvey statistics of the entire Shingo plant survey respondents to the statistics of the general population of manufacturing plants surveyed originally by Melnyk e t. al. (2003). As described in detail in Chapter 4: Methodology, Melnyk et. al. took extraordinary

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194 care to assure that the population chosen for their surv ey was based on accepted industry data bases of manufacturers and filtere d to assure they were discrete manufacturers, in sectors likely to implement en vironmental management systems. It is therefore reasonable to assert that the “Melnyk” p opulation represents the general population of manufacturing plants for compar ison to the Lean Shingo plants. It is also reasonable to assert that the Shingo plants represent the known Lean population, given that all earned the distinctio n of receiving site visits from Shingo examiners, and received high scores on the Shingo scoring system index. As described in the methodology chapter of this dissertation, all Shingo plants are discrete manufacturers, as required in the Sh ingo application criteria, and industry sectors where ISO14001 is common. All of th is is stated to assure an “apples to apples” comparison between the Shingo pl ants and Melnyk plants. Hypothesis I Findings The T-test analysis (table 13) for hypothesis I provides strong statistical evidence that the known Lean Shingo companies are significantly greener than the general manufacturing population. In twenty-five of the tw enty-six measures of Greenness the Shingo companies are significantly Greene r, at P<0.05 level of significance. In looking closely at table 13 it shows the T-test results of Shingo versus Melnyk statistics, it can be observed that in many ca ses (19 out of 26) the significance level is P<0.01.

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195 Notice for the Green results (GR) section, variables GR1 through GR10, that in all cases the significance is P<0.0001, the highest practical level of statistical significance. The significance level of the Green resul ts section is disproportionately higher than the significance levels for the Green waste reducing techniques (GWRTs). Yet, we know that the GWR Ts strongly correlate to GR variables. This suggests that Lean plants that imp lement Green waste reducing techniques are realizing disproportionately b etter results of their Green efforts than the general population. This suggests the re may be synergy between Lean and Green efforts within the Shingo pla nts. That is to say, plants that commit themselves to Lean best practices, not only realize strong Lean results, they also realize better results from their Gr een best practices than the general population. The logical explanation for this finding is that Lean plants have a well-honed infrastructure for identifying and eliminating waste, through total employee involvement and continuous improvement. If Green wast es were identified as opportunities for improvement, the efficiency by which Lean plants would reduce these waste, and generate measurable Green results, wou ld logically be much higher than a plant without the Lean culture. Ofte n is the case in non-Lean plants that “band-aid” solutions are deployed to add ress an environmental symptom. Lean plants possess a disciplined approach to pr oblem solving that gets to the root cause of the problem efficiently and i mplement systemic solutions that yield sustained results.

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196 The findings of this hypothesis alone provide strong evi dence of transcendence to Green manufacturing by leading Lean manufacturers. It is clear from the statistics that the level of adoption of both Lean and Green best practices are very high across the board for the Shingo companies. Th is is clear evidence that Lean companies are implementing Green manufacturing syst ems. This suggests that they may be taking a holistic view of waste elimin ation that includes both Lean and Green wastes. The findings also suggest eviden ce of synergy between the two systems. Hypothesis II – IV Findings Hypotheses II-IV were more inwardly focused than hypoth esis I. These hypotheses sought to determine if higher levels of Lea nness among the Shingo plants correlated to higher levels of Greenness within the same Shingo population of survey respondents. As indicated in C hapter 5, no significant correlation was found between higher overall levels of Leanness (LEAN) and the three main variables for the Green manufacturing syste m; Green Management System (GMS), Green waste reducing techniques (GWRT), a nd Green results (GR). These findings were disappointing, because they did not support the findings of hypothesis I that showed such significant diff erence in Green variables between the known Lean Shingo plants and the general manufacturing population. Perhaps the convenient explanation for the lack of stati stical significance between Lean scores and Green scores is that we are deali ng with all Lean

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197 plants, and perhaps splitting hairs. It took a panel of five Lean experts from the Shingo team to perform thorough evaluation of these plants to come up with different Lean scores. It could be that there are such s ubtle differences between their Leanness, it does not reflect in the high measur es of Greenness. Of course, the fact that there is sufficient stratification of data within the Shingo set to show significant correlation between the main variab les (LMS, LWRT, and LR) challenges the “splitting hair” theory. The alternative theory is that there may be a limit, or zero sum gain, to the amount of improvement activity that a company can commi t to and execute at any point in time. Melnyk et. al. (2003) and Florid a (1996) observed that the size of the company, and hence the size of the resource pool, significantly correlated to the level of environmental practices. Ideally, th e “zero sum gain” theory should have born out statistically by showing reverse cor relation between the main Lean and Green variables. Interestingly, it was f ound that the plant that scored the highest overall GREEN score had the lowest ove rall LEAN score. But this was just one data point, and reverse correlations f or the entire Shingo data set were not found for the main variables. With no strong positive or negative correlations to rep ort, it became evident that the high-level statistics (main variable correlations) w here not telling the whole story. This led to speculation that there was something going on at the subvariable level that warranted further analysis. Perh aps several sub-variable positive and negative correlations were canceling each other out when viewed at

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198 the high-level. This led to extensive analysis at the sub-variable level during the summer months, the results of which are discussed below. Full Correlation Analysis Discussion Full correlation analysis was performed for all main va riables and sub-variables in the study (i.e. Lean, Green, and control variables) Table 15 shows the matrix of Lean & control variables from the Shingo prize dat abase as row headings and Green variables obtained from the survey as column hea dings. Several interesting correlations can be observed directly from this matrix, some of which are counter-intuitive. For simplicity this discussion is o rganized by the categories of the Shingo prize variables (row headings on the le ft side of table 15). Their correlations to the Green variables are contained withi n each section, specifically: Control variables Lean Management System Lean Waste Reducing techniques Lean results Control Variable Findings Quartile Control variable Quartile is the quartile of overall Lean scores that a plant f alls into by breaking the data set into quarters. The score of (1) was applied to the lowest quartile LEAN scores and the score of (4) was app lied to the highest quartile LEAN scores and scores of (2) and (3) for the second and third quartiles

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199 respectively. The decision to introduce the Quartile con trol variable was intended to determine if blocks of Lean plants showed significant d ifference in Green scores, since the continuous variable LEAN did not show any correlation for the main hypotheses variables of GMS, GWRT, and GR. Quar tile, similar to the continuous variable LEAN, did not show any correlation to any of the Green scores, thus reinforcing the point that the overall or m acro perspective when comparing Lean and Green performance is non-indicative Year Control variable Year measures the year the site visit was conducted by the Shingo examiners who generated the set of Lean scores in the Shingo database. The expert opinion is that Lean plants, as a function o f their continuous improvement culture, continue to become “Leaner” ove r time from the point they were assessed. It is important to clarify that Year is the calendar year the site visit was conducted and it might have made more sense to define this variable as “years since site visit was conducted”. Thus, a negative cor relation actually suggests a positive finding. The statistics reflect a nega tive correlation between the control variable Year and three Green waste reducing technique variables, Product design, Disassembly, and Reduce Given the assumption that a plant continues to get lea ner over time, as suggested by the Shingo experts, a lower score in Year suggests that the Lean scores are slightly lower than they would be if the pla nt were measured today. Thus, the inverse correlation implies that the plants wi th older Lean scores are

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200 showing significantly higher Green scores relative to th eir Lean scores, which may be slightly understated. This could suggest that o ver time these plants became both Leaner and Greener, which supports the over all hypothesis of the study. It would be interesting to perform a longitud inal study on these plants to better understand the changes in Leanness since first meas ured by the Shingo examiners. The problem with this finding is there are so many assu mptions. It could be argued that since the five year period when Shingo sco re were obtained coincided with a major economic downturn (i.e. 9/11/200 1), that these plants actually were forced to reduce Lean efforts and cut back r esources. This would suggest they could have been less Lean today than when they were measured. Conversely, Lean literature indicates that what makes L ean companies great is how they stick to their commitment to Lean even during the toughest times (Shingo, 2003). During economic downturns, Lean compa nies send idle workers to advanced training or focus them on process improvemen t, while non-Lean companies simply lay-off employees. As a result, when the economy picks up again, Lean companies tend to “leap-frog” their nonLean competitors. Toyota is a classic example of this strategy as they have successfully b een “leap frogging” other automakers for years this way. Toyota maintains bil lions in cash reserves to buoy employees during difficult times, so as not to lose the investment they make in their people. (Liker, 2004)

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201 Country Control variable Country correlates positively and significantly to overall Gree n waste reducing techniques (GWRT), Green results (GR), an d their sub variables. As mentioned previously, the counter-intuitive findin g is that the Mexican plants were significantly higher than the US plants in many Green waste reducing technique (GWRT) and Green result (GR) categories. To refresh the reader, the positive correlations related to Mexican plants are as f ollows: GWRT8: Consuming waste internally GWRT10: Use of returnable packaging GWRT12: Creating markets for waste GWRT13: Segregating waste GWRT14: Creating alliances GWRT: Overall adoption of Green waste reducing techni ques GR3: Improved product quality GR4: Improved market position GR5: Enhanced reputation GR8: Improved equipment selection GR10: Improved international sales GR: Overall Green results The Shingo Prize is available to manufacturers in Nort h America, thereby including plants from Mexico and Canada, in addition t o the US. (Note: Ten Mexican plants were in the sample, yet no Canadian pl ant responded to the survey). The set of significantly higher Green waste r educing techniques that the Mexican plants employ paints a picture of material reso urcefulness and collaboration. Let’s revisit the complete description o f each of these significant GWRTs from the Green survey.

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202 GWRT8 (Consume internally): Consuming waste internall y (e.g. wood pallets used in shipping or product storage used to generate el ectrical power in cogeneration facility) GWRT10 (Returnable packaging): Using packaging and p allets that can be returned after they are finished being used GWRT12 (Creating markets for waste products): Treati ng waste as an input to another product which can be made and sold at a profi t GWRT13 (Waste Segregation): An intermediate action in which waste streams are separated out into their individual components bef ore being recycled, reused or consumed internally GWRT14 (Alliances): Working with either suppliers or co nsumers to address environmental problems and/or issues Together the waste reducing techniques imply that these plants go to great lengths to conserve material resources. It is rather easy to visualize a process by which waste streams are being separated in components f or reuse, recycling, or internal consumption. Reusable packaging is returne d to suppliers, perhaps as a kan ban signal for replenishment. Waste that can b e consumed internally is burned to create energy for the facility. Markets are established to sell process by-products that can be used in processes of other local ma nufacturers. Alliances are formed with suppliers and customers to discuss better ways to conserve resources and reduce environmental impact. The picture painted by these significant GWRTs seems to im ply a resourceful culture where there is a natural tendency to utilize a ll that can be utilized prior to dumping it into landfills, which may also be limited i n availability. In contrast to this picture of the Mexican industrial community is the p icture of the US manufacturing plant. The US has massive infrastructures for providing raw materials and disposing of wastes that may seem on the sur face more efficient than reusing or reprocessing byproducts.

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203 These findings also imply a close-knit industrial community in Mexico, where suppliers, manufacturers and even consumers are part of a n industrial community. This seems similar to the industrial parks of Japan (i.e. Toyota City), where suppliers are located close enough to manufacturer s to provide Just-intime shipments, an essential element of the Lean syste m. Close proximity would facilitate both the selling of waste products as inputs to other plants and forming alliances. Perhaps there is also more of a cultural tend ency to work together as a community in Mexico than in the US. In contrast, pla nts in the US seem rather spread out along our vast landscape so it may not be as l ogistically practical to return packaging or sell and deliver waste products to ot her plants. The US culture is also known for individual behavior t hat may not lend itself as much too forming alliances to address environmental issue s. The US also has the dubious distinction of being the most wasteful society where the average US citizen generates one hundred times the waste of someone in the third world (Prokop, 1993). Given all of these factors, it is now logical to see how the Mexican plants are significantly higher in the five spe cific GWRT sub-variables and the overall GWRT main variable. The significant difference in Green results (GRs) among st Mexican plants is not surprising given that the Mexican plants exhibited high er adoption rates of Green Waste Reducing Techniques. This is consistent with the cor relation analysis performed on the main Green variables for the overal l data set. Specifically, the Green results variables where the Mexican plants were si gnificantly higher than

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204 the US plants are listed below, with their full survey definition for further discussion: GR3: Significantly improved product quality (as a resu lt of Green efforts) GR4: Significantly improved position in the market p lace GR5: Helped enhanced the reputation in the market pl ace GR8: Significantly reduced waste within the equipmen t selection process GR10: Improved chances of successfully selling its products in international markets. GR: Overall Green results Improved quality speaks to how the techniques used to reduce material wast e in a process are the same used to improve product yield an d hence quality (this is addressed later in the chapter). Improved market posit ion, enhanced reputation in market place and improved international sales addr ess the positive effects the Mexican plant’s Green efforts have on the market place. There are growing requirements that sub-contractors to m ajor manufacturers or entire countries must assure sound environmental practices i n order to ship product to that company or country. This is true for IS O14001 certified companies that must commit to doing business with enviro nmentally conscious partners and for the European Union who recently passe d trade restrictions that require any electronics manufacturer shipping product to the EU must assure they are lead free (ROHS, 2006). This may be quite a competitive differentiator for Mexican plants that embrace Green practices for pote ntial customers with strong environmental policies.

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205 It should be noted that the Mexican plants in this study may be “transplants” from US Corporations that probably require sound environme ntal practices in order to comply with their ISO14001 certification requirements o r corporate policy to assure a positive public image. This would serve as a sta rting point and/or catalyst for the Mexican plants’ environmentally conscious behavior. It is also likely that these plants are newer than domest ic plants in the study, for reasons of expansion or outsourcing to lower labor cost markets. The fact that Mexican plants show significant results in the equipment selection variable suggests that they may have taken advantage of modern t echnology that is more environmentally friendly. The Rothenburg study of a utomotive plants, cited in the literature review, found that legacy plants had lower levels of environmental performance than newer plants and argued that this w as due to older technology that is generally less environmentally conscious and resour ce efficient. (Rothenburg et. al. 2001) Lean Management System Findings Curiously, there was only one correlation between the entire category of Lean management system and all Green variables, and it was n egative. Specifically, Leadership significantly and negatively correlated to the improved product quality – as a result of Green efforts To better understand this relationship, it is helpfu l to state the definition of these variables from the S hingo criteria and the Green survey:

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206 IA. Leadership This subsection is designed to evaluate leadership at all levels of an organization with regard to application of world-class strategies and core business system practices that drive world-class results. Lead ership creates an organizational culture and infrastructure t hat aligns the company’s mission, strategy and policy to deploy lean/wor ld-class practices and achieve world-class results. Please discuss how your organization uses leadership to dep loy worldclass and lean strategies and practices to achieve world-cl ass results. Examples of the items that could provide evidence in this section include, but are not limited to: • Statements of vision, mission, values, strategies and g oals • A planning process for establishing and deploying visio n, mission, values, strategies and goals (e.g., Hoshin Kanri, Policy Deployment, Management By Objective, etc.) • Allocation of resources for deploying vision, mission, values and strategy • Sustained personal commitment and involvement of all the organization’s managers to find and eliminate waste ( muda), or any non value-added activities and costs • Knowledge management system and business results that a re deployed to all levels of the company • Communication and measurement of quality, cost and d elivery standards throughout the organization • An organizational philosophy that encourages and re cognizes innovations, entrepreneurship and improvements whereve r they originate in the organization (Shingo, 2003) GR3: Significantly improved product quality The only rational explanation for this negative corre lation is that presence of a comprehensive Lean management system implies a very stron g focus by senior management on the implementation of Lean waste reduci ng techniques and measurable results. One of the major performance mea sures of Lean is “Quality”. This finding may suggest a bias on the par t of the plant, in an effort to show success of the Lean system, to associate all quality imp rovements with the lean system, and to discount the contribution of Green efforts towards quality

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207 improvement. To the degree that a plant had integr ated its Lean and Green management systems, it becomes more difficult to determ ine how much quality improvement is due to Green efforts. Lean Waste Reducing Technique Findings There are several negative correlations between Lean W aste Reducing Techniques (LWRTs) and Green main and sub-variables. Yet there are positive correlations between support function s and several Green variables. Curiously, support functions and Partnerships exhibit equal but opposite correlations to nearly the same set of Green variables. These relatio nships will be discussed categorically relative to each LWRT sub-variable in th e following order: IIA Vision and strategy (IIA) IIB Innovation IIC Partnerships III Support functions IID Operations LWRT – Overall Lean waste reducing techniques Vision and Strategy Lean vision and strategy significantly and negatively correlates to years ISO14001 certified and Improved quality – as a result of Green efforts To better understand these relationships, it is helpful to state t he full definition of these variables from the Shingo criteria and the Green surve y:

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208 IIA. Manufacturing vision and strategy This subsection requires an outline of the company’s manu facturing vision and strategy as it relates to the selection and use of the specific methods, systems and processes detailed in subsections B, C, and D of this section. (Shingo, 2003) GMS2: Number of years the plant’s Green management system has been ISO14001 certified GR3: Significantly improved product quality This finding is consistent with negative correlation betw een Lean leadership and improved quality The fact that vision and strategy also negatively correlates with years ISO14001 certified indicates that while these plants have well establish ed visions and strategies for their Lean system, they are in their infancy regarding their Green systems vision and strategy. Together, thes e negative correlations make the point stronger that a myopic focus on Lean at the strategic level detracts from management commitment to Green and percep tion of the benefits of the Green system. This finding may suggest a bias on the part of the plan t, to associate all quality improvements with the Lean system, and to discount the co ntribution of Green efforts towards quality improvement. This suggests that awareness of the complementary natures of Lean and Green systems at the executive level is essential for their integration and resulting synergist ic benefits. Innovation Lean waste reducing technique variable IIB (innovation ) negatively and significantly, correlated to Green waste reducing techniq ue variables Recycling, Remanufacturing, and Alliances To better understand these relationships, it is

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209 helpful to state the definition of these variables fr om the Shingo criteria and the Green survey: IIB. Innovations in market, service and product This subsection is designed to evaluate a company’s market service and product innovation. Any available information regard ing competitors’ benchmarking of services and products should be included. T wo potential approaches could be pursued: (1) innovative efforts to r educe the cost of existing product(s) and product development; and (2) i nnovations in market service. Both approaches are viewed as enhancing b usiness growth and performance. The second approach generally a pplies to companies that are primarily assemblers or those who manu facture a commodity-type product with limited opportunity for new product development. The methods and processes documenting market service and p roduct innovation may include, but are not limited to: • Verifiable cost reductions in logistics, sales, service, po st sales service, technical support, etc. for an assembler or a manufacturer of a commodity product • Using quality function deployment, concurrent or simul taneous engineering, etc. for product development • Benchmarking competitors’ products and services • New market development and current market exploita tion • Design for manufacturability, testing, maintenance, a ssembly, etc. • Variety reduction • Converting a commodity-type product to a more special ty differentiated product • Innovations in market service and logistics • Broadening sales mediums to include avenues such as e-co mmerce, the internet, etc. (Shingo, 2003) GWRT6 (Recycling): making more use of recycled component s or making a product which is more easily/readily recycled GWRT7 (Remanufacturing): restoring used durable pro ducts to "new" condition, to be used in their original function, by replacing wo rn or damaged parts GWRT14 (Alliances): working with either suppliers or co nsumers to address environmental problems and/or issues.

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210 This finding also speaks to the notion that a strong lea n focus regarding product and market innovations may create myopia toward Green This result also speaks to the matter of limited resources. That is to say as long as the disciplines of Lean and Green product innovation are co nsidered unique and not integrated, it would be difficult to simultaneously su pport separate design efforts from a resource perspective. Partnerships Partnerships negatively and significantly correlates to Years ISO14001 certified overall status of the Green management system, Product desi gn, Disassembly, and the overall Green score To better understand these relationships, it is helpful to state the definition of these variables fr om the Shingo criteria and the Green survey: IIC. Partnerships with suppliers/customers and environmen tal practices This subsection is designed to evaluate the company’s effor ts to deploy world-class practices by partnering with suppliers and custo mers, and to assess how well the company integrates suppliers and custo mers into the value-creation process. Discuss how your organization uses pa rtnering to deploy world-class practices and/or to achieve world-class r esults. Documentation in this section may include but is not lim ited to: • The integration of the company, its suppliers and i ts customers in establishing value-creating methods and practices across compa ny boundaries in production or product development • Distribution and transport alliances to insure product quality and productivity • Initiatives regarding environmental issues (i.e., recy cling, reducing industrial waste, ISO 14000, etc.) • Supplier satisfaction measures • Union partnership initiatives • Benchmarking projects for process improvement. • Cooperative endeavors with schools and training orga nizations to ensure a qualified workforce • Cooperative community endeavors that demonstrate the company and its employees are socially re sponsible

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211 (Shingo, 2003) GMS2 (Years certified): Number of years the plant’s G reen management system has been ISO14001 certified GMS (Overall GMS status): Overall status of Green ma nagement system, implementation status and years certified. GWRT1 (Product redesign): redesigning the product to e liminate any potential environmental problems (manufacturing or recycling) GWRT3 (Disassembly): redesigning the product or process so as to simplify disassembly and disposal at the end of the product's usef ul life GREEN: Overall survey score From the description, Partnerships speaks to the breadth v ersus the depth of the Lean system implementation. It is an overall measure a s to how the plant has disseminated its Lean practices out to its broader “value chain” of suppliers and customers. This is an external versus internal focus, also d escribed as a “horizontal integration” versus “vertical integration” of the plant’s lean system, respectively. With the amount of resources it takes to i ntegrate and improve external processes, it would be no surprise that it woul d detract from resources for going deeper into the internal processes to implem ent Green system elements. Let’s explore these relationships categorical ly. The fact that Partnerships negatively correlates with t he Green management system variables supports the notion that these particular companies are more externally focused on Lean waste elimination than exp anding their internal Lean waste reducing efforts to include Green practices. These plants may have chosen to outsource environmentally challenging processes to supply chain partners, thus avoiding the need to implement Green s olutions.

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212 The Green management system is the strongest indicator to a plant’s overall commitment to the Green system. It drives Green waste r educing techniques and results, as indicated in the Melnyk study (2002) an d confirmed in the data validation table 12. It then follows logically that if Partnerships negatively correlates with Green management system, it also correla tes negatively to the overall Green score. This is perhaps yet another form o f validation of how critical the Green management system is to the overall Green syst em. From the expanded survey description Product redesign an d Disassembly are both direct indicators of a plant’s product design capabi lities. Having an internal design team that is extensive enough to consider advanc ed environmental aspects in its product design, may be indicative of verti cal integration. If so, this would be consistent with the inverse correlation with pa rtnerships that is a measure of horizontal integration. Perhaps these pl ants outsource their product design to one of their value chain partners where emp hasis may lie mostly on fulfilling specific Lean objectives. Curiously though, this variable also measures “initiati ves regarding environmental issues”, and in particular ISO14001. It is counter-intu itive that this would result in a negative correlation to several Green variables, in particular, Overall Green management system and Years certified that are direct me asures of ISO14001 implementation! There is perhaps a logical explanatio n for this and it has to do with the weight the Shingo examiners place on the env ironmental element of this variable.

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213 When I first spoke to Dr. Ross Robson (Executive director of the Shingo Prize) regarding the use of the Shingo criteria as my indepe ndent variables, I voiced concern about the fact that they were already measurin g some “Green” elements and this may bias the results. He indicated that the we ight currently applied to this particular variable was negligible and the main f ocus was on the Lean enterprise elements. He then went on to say that it w as essentially a place holder that one day, perhaps as a result of my resear ch, may be fleshed out and have more weight applied to it. Hopefully, my research will indicate the Green practices complementary to the Lean system, which could be woven into this category of t he Shingo criteria. I do think that environmental considerations are current ly mis-placed in the partnership category and should reside in the support f unctions category of the Shingo criteria. Support Functions Next we will discuss the positive correlation between Support functions and the set of Green variables {Status of Green management system implementation, Overall Green management system, Product redesign, Disassemb ly, Enhanced reputation, and Total Green score} Let’s begin with the detailed definition of these variables from the Shingo Prize criteria and the Green survey: III Non-manufacturing support functions This section is designed to evaluate (1) the degree of integration between manufacturing and all nonmanufacturing functional units; and (2) the extent to which improvement techniques and strategies h ave been applied in non-manufacturing functions up and down th e value stream (new product development efforts are detailed in Sect ion IIB and need not be repeated here). Non-manufacturing support function s may include

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214 accounting, finance, human resources, sales and marketing materials, purchasing, quality, MIS, etc. Address only those non-m anufacturing functions that fall under the scope or control of the a pplicant site. Evidence could include, but is not limited to, a discussio n of: • Alignment of non-manufacturing functions to support the manufacturing function • The integration of non-manufacturing functions wit h manufacturing • Incorporation of continuous improvement in the mission or vision statements, goals or strategies of all non-manufacturing functions • Elimination of waste or non-value-added activity in all functional units of the organization (e.g., closing of financial books in hours rather than days) • Commitment to continuous improvement projects and/or change processes in long-range plans, capital budgets, training and human resource development, marketing plans and strategic rev iews by all functional business units (Shingo, 2003) GMS1 (Status of GMS): Status of plants Green manag ement system implementation. GMS (Overall GMS status): Overall status of Green ma nagement system, implementation status and years certified. GWRT1 (Product redesign): Redesigning the product to e liminate any potential environmental problems (manufacturing or recycling) GWRT3 (Disassembly): Redesigning the product or process so as to simplify disassembly and disposal at the end of the product's usef ul life GR5 (Enhanced reputation): Helped enhance the reputa tion of your company GREEN: Overall survey score From the detailed description of support functions it is clearly a measure of internal or vertical integration of the Lean system. The definition for support functions describes close knit integration of non-manufactur ing support groups and manufacturing to continuously eliminate waste in a ll facets of the business. This suggests holistic view of waste minimization through out all plant functions. Perhaps as all plant functions become enlightened to wast e elimination, this

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215 translates to environmental waste elimination. After all, waste in any form is still waste. Identified in the Green literature review are many examples of the importance of support functions to the overall success of the Green system For example, both Lean and Green literature emphasize the importance of Activity based (or Total Cost) Accounting to account for waste in the product cost, so that it stands out as an opportunity for cost reduction (see literature view for details). This is in contrast to traditional standard based cost accounting th at hides these costs in overhead or worse yet categorizes them as assets (i.e. inv entory). It is logical that accounting practices implemented to support Lean ma nufacturing would also support Green manufacturing. Another good example is how materials groups and logist ics groups are critical to support Lean and Green initiatives. If a plant has a strong materials and purchasing team that is looking for suppliers to support t he elimination of Lean wastes in the supply chain, they could easily undertake th e elimination of environmental wastes as well, by assuring that less hazard ous materials were purchased for example. The same can be said for a l ogistics support department that seeks to reduce the distance and create p ull/kan ban systems to support the JIT principles of the Lean system. This direct ly supports several Green waste reducing techniques, such as returnable packagin g, disassembly, and remanufacturing that rely on a strong logistics infr astructure.

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216 I believe it is fair to say, based on the literature review, that Lean and Green systems/strategies depend on strong support functions to cre ate an infrastructure for broad based waste elimination. The significant cor relation between Lean variable III (Support functions) and Green variables i n the GMS, GWRT, GR categories, and most strikingly the overall Green score, offers sound statistical evidence that the plants that have taken a holistic appr oach to Lean, are also taking a holistic approach to Green. The generalized conclusion that can be drawn from this finding is that as the Lean waste elimi nation culture spreads throughout the plant, it leads to transcendental behavior to seek out and eliminate Green wastes. In the literature review, Pa nizzolo speaks to how vertical integration of Lean practices precedes horizonta l integration amongst leading Lean manufacturers. (Panizzolo, 1998) There is a saying that Dr. Jeffery Liker (2004) uses rega rding successful deployment of the Lean system. And, that is “it is best to go an inch wide and a mile deep”. The point here is that for the Lean syste m to sustain, it takes a laser like focus on a particular process and team to culturally i ngrain the Lean system. Spreading the deployment of the Lean system too quickly throughout the plant or the extended enterprise can result in an unsustainable system, as the culture reverts back to the old habits. This would explain why the plants that chose to go deep instead of wide, sought out additional Green wa ste reducing practices. They were compelled culturally to do so.

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217 Regarding the dichotomous relationship between partnerships and support functions the short logical explanation is that a typical plan t, with limited resources, struggles to support both a broad based intern al Lean system and a broad based external Lean system. Simply put, plants have either vertically integrated or horizontally integrated their Lean syst ems. It was observed during statistical analysis that partnerships and support functions are indeed inversely correlated to one another at strong (P<0.01) level o f significance. This provides strong statistical evidence that with presumably limited resources a plant can’t go both “deep” internally and “wide” externally with i ts Lean implementation. And, that the plants that favor going deep internally, by taking a holistic approach to implementing the Lean system throughout all facets of t he operation, transcend to Green manufacturing. Lean Results Discussion It was not intended this way, but simply as a matter o f coincidence, the best findings have been saved for last. The correlations be tween many Green variables, in all three categories (GMS, GWRT, and GR ) and all four Lean results variables (i.e. Quality, Cost, Delivery, Customer satis faction and profitability) are so strong, that it can be said without hesitation that L ean companies who embrace Green practices, have significantly better Lean performance results. In this case, synergy is realized when Green best practices sig nificantly correlate to both Green and Lean results. This implies that the Gr een manufacturing system serves as a catalyst to the Lean system, yielding better L ean results than plants that do not have a Green manufacturing system in plac e.

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218 It is important to emphasize that the Lean system was m easured in this study by Shingo examiners with little thought to the environm ental practices going on in the plant. This minimizes any risk of biasing the Lean R esults scores, relative to Green management system and Green waste reducing techni ques. These Green best practices were only identified from the surv ey that was administered well after the Lean scores were placed in the Shingo Pr ize database. Let’s discuss in detail these remarkable findings of Green vari ables to Lean results. Again, this section is organized in the order of Lean results variables seen in the left hand side of table 15, with detail regarding cor relations with respective Green variables within each section, specifically: IVA – Quality IVB – Cost IVC – Delivery V – Customer satisfaction and Profitability LR – Overall Lean results Quality The Lean results variable Quality correlates significantly and positively to the status of the Environmental management system/ISO14001 This Lean variable measures quality performance as measured by a group of Lean experts, with little eye toward environmental matters. Before discu ssing this correlation further, let’s first define these variables from the S hingo Criteria and the Green survey.

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219 IVA. Quality and quality improvement The objective of the quality & quality improvement category is to insure that no human or machine errors ever get into custome rs’ hands and that in-process defects are continually being reduced. The goal is zero defects. Both trend and level data should be presente d and the basis/definition for all quality measurements should be reported. Expected measurements: • Rework as a percent of sales or production costs • Customer rejects due to quality (ppm) • Finished product first pass yield and percentage • Unplanned scrap rate(s) Supplemental data could include: • Overall cost of quality as a percent of sales, total m anufacturing cost or other appropriate baseline • Process variation measures • Warranty cost as a percent of sales • Other appropriate measures (Shingo, 2003) GMS1 (Status of GMS): Status of plants Green manag ement system implementation. In looking closely at the criteria for Quality there is considerable reference to process yield, rework, scrap, process variation, warranty co sts, customer rejects, total manufacturing costs. Obviously these are true indi cators of process quality and are appropriate for this Lean variable. Yet, it is from this vantage point of the Lean system that one can begin to see the direct connecti on to the objectives of a Green system. The ideal Green process has perfect yield with no scrap: All resources end up in the finished product with no solid o r hazardous waste byproducts. Products have a long and useful life, with minimal customer rejects or warranty costs. Total cost of manufacturing is minim ized as higher levels of resource efficiency are achieved.

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220 It is a fundamental requirement of ISO14001 that the plant establish environmental goals and objectives that drive the orga nization to continually reduce environmental waste, and have a formal managem ent review process to make sure the goals are realized. You can’t achieve ISO1 4001 certification with out it. The metrics and goals of the Environmental ma nagement system typically include the same criteria listed in the Shingo quality criteria. Thus, it is only logical that the evidence of a formal EMS, as measur ed in this study by the variable GMS1, correlates strongly to quality improvem ent. As an alternative explanation, it is also reasonable t o assume that the quality improvements have an indirect association with the envi ronmental management system. That is to say, the results may be truly the fu nction of a comprehensive Quality management system (ISO9000) that may have le d to the implementation of ISO14001. Much has been written about the presen ce of a formal Quality Management System (ISO9000) and a formal Environment al Management System (ISO14001) (King, Lenox, 2001). It was, afte r all, the success of ISO9000 that led to the birth of IS014000. They ar e very similar in structure and companies that are comfortable with ISO9000 would nat urally be drawn to ISO14000 if they were interested in environmental im provement. Cost The Lean results variable Cost significantly and positively correlates to status of the Environmental management system/ISO14001 Overall GMS score, Reduce, Returnable packaging, Creating markets, Waste segregation Over all Green

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221 waste reducing techniques, Improved equipment selection, Total Green score To better understand these relationships, let’s explore the complete definition of the variables from the Shingo Prize criteria and the Green survey: B. Cost and productivity improvement The purpose of the measured cost and productivity impr ovement category is to assess the improvement trend and level in cost and productivity. Both trend and level data should be presented and the basis/definition for all cost and productivity measurements should be reporte d. Expected measurements: • Total inventory turns separated as appropriate into raw, WIP and finished goods. • Value added per payroll dollar (sales minus purchased goods and services divided by total payroll dollars) • Manufacturing cycle time (start of product production to completion) Supplemental data could include: • Physical labor productivity (units/direct hour) • Energy productivity • Product cost reduction • Percent machine uptime • Changeover reductions • Resource utilization (e.g., vehicles, plant and wareh ouse floor space, etc.) • Transport and logistics effectiveness and cost • Other appropriate measures (Shingo, 2003) GMS1 – Status of environmental management system (IS O14001) GMS – Overall Green management system score GWRT3 – Substitution replacing a material which can ca use environmental problems with another material which is not problemati c GWRT10 – Returnable packaging: Using packaging and pa llets which can be returned after they are finished being used GWRT12 – Creating markets: treating waste as an input to another product which can be made and sold at a profit GWRT13 – Waste Segregation: an intermediate action i n which waste streams are separated out into their individual components bef ore being recycled, reused or consumed internally GWRT – Overall Green Waste Reducing Techniques

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222 GR8 – Improved equipment selection GREEN – Overall Green score This particular finding is perhaps the most powerful of the entire study. There can be little debate that one of the most important o verall measures of Lean and manufacturing in general is total cost reduction. To m ake this point, each of the other Lean results measures (i.e. Quality, Delivery, C ustomer satisfaction, and Profitability) have cost reduction components built into their criteria, because the ultimate measure of any business in a capitalist society i s financial. What is most striking is that not only does this variable correlate wi th several Green subvariables, but that it correlates strongly with the mai n variables Overall Green management system, Overall Green waste reducing technique s, and Overall Green score It can hardly be more evident that the Green system positively correlates to total cost reduction, as measured by an ob jective, nonenvironmentally biased panel of experts. From the Shingo criteria, Cost is a broad based measure of operational costs generally associated with Lean manufacturing systems as wel l as traditional production cost accounting systems. Thus, Green variables that positively correlate with variable IVB can be said to positively co rrelate to manufacturing cost reduction in a very generally applicable fashion. To better understand the relationship between the Green best practices and cost red uction let’s explore the Green variable correlations categorically as they relate to the Lean cost variable IVB to better understand the logic behind th ese relationships.

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223 The status of the Environmental management system/ISO14001 an d the overall Green management system variables both positively and significantly correlate to Cost. This is a strong indication the presence of an ISO1400 1 certified environmental management system, is closely associated with cost reduction in the manufacturing plant. Substitution of hazardous raw materials, use of returnable packaging waste segregation and creating market for waste products positively and significantly correlate to cost. All of these waste reducing techniq ues speak to material resource efficiency and avoiding the generation of envi ronmental wastes. This is a clear indication that emphasizing total waste reducti on drives total cost reduction. Total cost reduction is the ultimate bottom line measu re of a manufacturing operation and the one measure that is most highly reg arded by the executives and shareholders who set policy and strategy for the ma nufacturing plant. Thus, it is of critical importance in making the case that Gree n is compatible with Lean to show a positive correlation to Lean cost reduction. The fact that the main Green variables GMS, GWRT and the overall measure of the Green system (GREEN) correlate strongly to Cost puts to rest any argument that Green strategies are not cost effective. These findings indicat e that the existence of a Green manufacturing system is an essential catalyst to th e Lean system to realizing the greatest cost reduction. This result is a strong indicator that a focus on total waste reduction (Lean and Green) results in to tal cost reduction, and the

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224 ultimate financial justification for integrating Lean and Green manufacturing systems. Delivery The Lean results Delivery positively and significantly correlates with the Green variable Creating markets To better understand these relationships, let’s explore the complete definition of the variables fro m the Shingo Prize criteria and the Green survey: IVC: Delivery and service improvement The purpose of the delivery and service improvement cate gory is to identify whether customers are getting what they need in the time and quantity necessary. Both trend and level data should be presented and the basis/definition for all delivery and service measu rements should be reported. Expected measurements: • Percent of line items shipped on-time (define on-tim e window) and/or percent of complete orders shipped on-time (define on-t ime window) • Customer lead time (order entry to shipment) • Premium freight as a percent of production costs Supplemental data could include: • Mis-shipments • Warranty response and service • Other appropriate measures (Shingo, 2003) GWRT10: Creating a market for waste products: Treatin g waste as an input to another product which can be made and sold at a profit This is a logical relationship, given that both are ind icators of delivery and logistics of products and bi-products respectively. This ma y suggest that Lean companies with particularly strong delivery and logisti cs performance, are

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225 inclined to utilize this capability to find creative a lternatives to sending waste to landfills, and instead profit from delivering waste products to companies that can use their waste as process inputs. It is reasonable to assume that if a company seeks markets for the waste products it would strive to deliver them efficiently. This could then spill over to the delivery and logistics capabilities of their main pr oducts, which results in improved performance as measured by the Shingo expert s. The results from this section could indicate that this integrated approach to forward and reverse logistics is taking place at some of these plants. Customer Satisfaction and Profitability Lean results variable Customer satisfaction and Profitability positively and significantly correlates to Green waste reducing technique variables Substitution, Prolong Use, Creating markets, Waste segregation To better understand these relationships, let’s explore the complete definition of the variables from the Shingo Prize criteria and the Green survey: V: Customer satisfaction and Profitability This section is intended to evaluation the outcomes of q uality, cost and delivery on customer satisfaction and business results. For each measurement presented, three (3) or more years of resu lts should be documented. Customer Satisfaction Evidence of customer satisfaction may be presented throu gh any valid approach used by the company. Survey data should describe sample size, survey format, frequency and efforts to avoid bia s. Measures reported must be clearly defined and could include, but are not limited to: • Market share • Reorder rate

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226 • Customer survey results • Customer awards • Customer audits • Field performance data • Other appropriate measures Profitability Measures of level and trend should be clearly defined a nd should document the unit’s overall relevant business financial attainment. Expected measurements: • Operating income on sales ratio • Operating income on manufacturing assets ratio Supplemental data could include: • Reductions in fixed and/or variable costs • Cash flow • Product line margins • Other appropriate measures (Shingo, 2003) GWRT4: Substitution: replacing a material which can ca use environmental problems with another material which is not problemati c GWRT9: Prolong Use: reducing environmental problems b y increasing the overall life of the product (e.g. engines which last lo nger before having to be replaced or rebuilt) GWRT12: Creating a market for waste products: Treati ng waste as an input to another product which can be made and sold at a profi t GWRT13: Waste Segregation: An intermediate action i n which waste streams are separated out into their individual components bef ore being recycled, reused or consumed internally Let’s explore these correlations first from the perspecti ve of Customer satisfaction and then from the perspective of profitability. The Shingo criteria of customer satisfaction appears sufficient for measuring true satisfaction of the end user of the manufacturing plant’s products. In looking at the GWRT definitions, there seems to be at least two logical relationships to customer satisfaction. First, it would seem desirable to customers to know that their products were produced in a least hazardous way through Substituting hazardous materials with

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227 more benign materials. Secondly and certainly more lo gically, P rolonging the use of products would naturally translate to customer satis faction, as customers would get significantly more use out their product and thus greater value for their purchase. From the perspective of Profitability a logical argument can be made for all four GWRT variables. First, Substitution of hazardous materials is a practice identified in Waste Minimization/Pollution preventio n literature, which can reduce waste management costs, processing costs, and even raw mater ial purchasing costs (EPA, 2001). Secondly, products with Prolonged use can command a market price premium over brands that do not last as lo ng. This is commonly seen in the automotive industry. Prolonged use, also m eans less warranty repair costs. Thirdly, Creating a market for waste products means that instead of paying someone to take your waste, you are being paid for your waste. Finally, waste segregation means steps are being taken to get the most return on saleable waste products, and reduce waste management costs overall. Each of these examples either lower operating costs and/or allow for a higher price in the market place, which together translate into enhanced pr ofitability. The overall Lean results correlated positively and significantly with the Statu s of the Environmental management system/ISO14001, Substitution, Creating markets, Waste segregation, and Total Green waste reducin g techniques. Since each of the Green sub-variables listed have been discussed as to their correlation with specific Lean results sub-variables, ther e is little to offer at this

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228 point other than to state that it is further proof, t hat these particular Green subvariables share a very positive relationship with the o verall set of Lean results. For completeness, the definitions of the Green variable s that positively and significantly correlate to Overall Lean results are as follows: GMS1 – Status of environmental management system (IS O14001) GMS – Overall Green management system score GWRT3 – Substitution replacing a material which can ca use environmental problems with another material which is not problemati c GWRT10 – Returnable packaging: Using packaging and pa llets which can be returned after they are finished being used GWRT12 – Creating markets: treating waste as an input to another product which can be made and sold at a profit GWRT13 – Waste Segregation: an intermediate action i n which waste streams are separated out into their individual components bef ore being recycled, reused or consumed internally GWRT – Overall Green Waste Reducing Techniques What is worth discussing is the fact that Overall Lean results correlates positively and significantly with Overall Green waste reducing techniques This is a remarkable finding in terms of its implications to the future integration of these manufacturing systems. What this finding implies, is tha t of the population of Lean companies in this study who have opted to compleme nt their Lean system implementation with a broad set of Green waste reduci ng techniques are realizing significantly better results in both Green r esults and Lean results than the other Lean plants in the study. This finding not only suggests that Lean and Green systems can co-exist, but that there is evidence of synergy by the virtue of the fact that Green waste reducing techniques simulta neously improve Green and Lean results. And, the evidence from hypothesis I (p.6), whereby known

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229 Lean manufacturers exhibit disproportionately higher Gr een results than the general population of manufacturing plants, indicatin g that the Lean system is having a positive effect on Green results. It’s important to note that the Lean results were measu red completely separately from the Green waste reducing techniques by a set of Le an experts with no particular eye towards environmental behavior. It is also important to state another view of this correlation, given that causality of Green waste reducing techniques cannot be proven, just logically suggested. T he complementary view, given this correlation, is that successful Lean plants, as s een by their strong Lean results, tend to seek out new forms of waste to eliminat e, which includes the use of Green waste reducing techniques. That is to say, tha t rather than assume the application of Green waste reducing techniques contribut ed to Lean results, the success of the Lean program, as seen by the strong Lean re sults, served as a catalyst to the implementation of Green waste reducing techniques. This would be another example of Lean transcendence to Green manufacturing. Regression Discussion In order to fully explore this complementary relation ship between Green waste reducing techniques ( GWRT ) and the Lean system, regression analysis was performed combining GWRT with the main Lean variables Lean management system and combining GWRT and Lean waste reducing techniques (LWRT) as sets of independent variables and Lean results (LR) as the dependent variable.

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230 The results of the regression analysis are in tables 17 a nd 18 of the results chapter. In both cases the overall model was significant and GWRT was significant along with the Lean counter parts. These results suggest a com plementary nature of Green waste reducing techniques when integrated with Lean management systems and Lean waste reducing techniques in improving Lean results This is further proof that integrating Lean and Green best p ractices can have very powerful and positive results. The overall findings im ply there are opportunities to integrate Lean and Green into a single “Zero Waste Manufacturing” system that can remove redundancy and improve the efficiency of holistic waste reduction. Chapter Summary This chapter discussed the results presented in Chapter F ive in order to explain the meaning of the statistics and the implications of the se findings to the general manufacturing population. This discussion will be summar ized into specific conclusions in the next chapter. Chapter seven will also describe industrial application of these conclusions, and opportunities for f urther research.

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231 Chapter Seven Conclusions and Recommendations Review of Research Phenomena such as global warming and rapid population growth make us realize the fragile and finite nature of our planet earth. As we continue to exceed the earth’s capacities to provide natural resources and process wastes, we actually reduce these capacities, triggering a downward spiral toward ecological collapse. Philosophical frameworks, such as Sustainable De velopment and Industrial Ecology, have emerged to help us visualize a future where we enjoy the benefits of industrialization without environment al devastation. As the whole world seeks to industrialize, and manufacturing is pushed to developing nations, waste-free manufacturing systems are ever more critical to the future of humanity. Designing elegant industrial systems that mir ror the earth’s waste-free processes presents the ultimate challenge for industrial en gineers in the twentyfirst century, and is the key to our sustainable future. This study took one step toward industrial sustainability by exploring the relationship between the two leading manufacturing syst ems that target waste: Lean manufacturing and Green manufacturing. While Gr een manufacturing more directly addresses the global environmental challen ge, Lean manufacturing has emerged as the most economically efficient system for producing quality

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232 products, on time, tailored to customer needs. Althou gh Green manufacturing has proven to lower operating costs, limitations of econ omic equations that do not properly account for natural capital, mute the tr ue benefits of Green manufacturing systems. Thus, there has been great inte rest in marrying Lean and Green systems, so as to simultaneously realize economi c and environmental sustainability. The literature review, detailed in chapter two of th is dissertation, found studies that explored the Lean and Green relationship in a v ariety of ways. Dr. Sandra Rothenberg studied the correlation between the level of automotive manufacturers’ Leanness and environmental metrics (e.g. waste emissions, water and energy usage, etc.). Dr. Richard Florida, discovered that larger more technically advanced companies more readily embraced th e Green manufacturing practices, rather than smaller less advance d companies that chose traditional waste management practices. Ross and associates (and the EPA) case study of Boeing, fo und that Lean creates a culture highly conducive to environmental waste minimization and pollution prevention. They found that Lean initiat ives have environmentally beneficial by-products, such as less space and energy needs p er unit of output, and reduction in material scrap. They also identified that environmental agencies have a window of opportunity to integrate environme ntal practices into Lean systems, to leverage the rapid expansion of Lean. The EPA indicates it is very interested in research that helps “build a bridge” bet ween Lean and Green

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233 systems, so that the rapid deployment of Lean systems serve s as a catalyst for Green manufacturing and resulting environmental impro vements. Simultaneous to the research on the relationship betwe en Lean and Green systems, was research regarding the major components withi n Lean and Green systems. Researchers at the Shingo Prize team at Utah S tate University (Shingo, 2003), Jeffery Liker (2004), and Society of A utomotive Engineers (SAE, 1999), were expanding the definition of Lean from a set of process improvement tools to an entire system of operation. They defined Lean in dimensions of the management system that creates the Lean culture, waste r educing techniques that are proven to eliminate waste in the process, and measurable business results that companies realize by following the Lean b usiness model. In parallel to Lean system research, Green manufacturin g researchers such as Melnyk et.at. (2003), Russo (2001), and the EPA (2003) were looking into the relationships between the international ISO14001 Envi ronmental Management System (EMS) and environmental waste minimization an d pollution prevention techniques. They found that the existence of a formal environmental management system was essential in creating the culture t hat drove environmental improvement activity. Both Lean and G reen research efforts in recent years have made it clear that a systemic approach, that combines a formal management system with aggressive implementation of the waste reducing techniques, are critical to driving sustained re sults.

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234 Synthesizing all of this literature led me to create a series of Venn diagrams to visually depict the evolution of Lean and Green manuf acturing systems, specifically in relationship to each other. The Venn diagrams depict four evolutionary phases, and are copied from chapter thre e for convenience below. The first phase “parallelism” describes the traditional and still commonly practiced view, that these are two separate waste reducin g systems that may coexist within a single manufacturing operation, but sha re little in terms of resources, best practices, and results. In this evolutiona ry phase, there is still skepticism that these systems are complementary, and that trade-offs will have to be made between environmental and business improvem ent. The second diagram “convergence” is the view described in the Lean and Green studies referenced in the literature review. There i s a general feeling these systems are complementary, and elimination of waste in any form is good for business. Best practices are being shared between discipli nes. Lean companies may incorporate some Green practices within th eir Lean systems, but are not committing the implementation of a broader G reen system, and vice versa. The third view “transcendence” helped me visualize the next logical phase of this evolution, which really had not been explored. In t his view the expansion of one of these systems, and the resulting waste reducing culture created, triggers transcendence to the other system. Manufacturing plants t hat deeply commit to Lean systems develop such a strong culture of waste reductio n, they commit to a

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235 Green manufacturing system as a logical next step in the ir waste elimination quest. It can also be said for companies who first comm it themselves to Green manufacturing, that they eventually seek the most effi cient model of manufacturing (Lean) as a logical continuation of thei r efforts to reduce environmental impacts. My mind then wondered to a utopian phase of the fut ure, “Synergy”, whereby the distinction between these two systems ends and a single and holistic Zero Waste Manufacturing system emerges. In this culture employees are encouraged to target all forms of waste, and have in their arsenal the best practices from both disciplines. This zero waste approach eliminates the redu ndancy and conflicting practices between Lean and Green systems, thus continuall y improving the efficiency of the waste elimination process/system itself. Higher levels of effectiveness are evident as waste elimination efforts simultaneously improve both Lean and Green result metrics. The Earth itself s erves as the only respectable process benchmark for Zero Waste Managers. Sust ainability is realized, as manufacturers provide the products we need, without the traditional sacrifices to environmental quality.

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236 UNIVERSE OF MANUFACTURING WASTES Lean Manufacturing System Green Manufacturing System UNIVERSE OF MANUFACTURING WASTES Green Manufacturing System Lean Manufacturing System PARALLELISM: The traditional view whereby Lean and Green best p ractices are considered distinct sets of solutions targeting dif ferent forms of wastes. Some consider these efforts as conflicting. Best p ractices are administered by separate organizations operating in “parallel un iverses” of waste reduction. CONVERGENCE: The moder n view, whereby Lean and Green best practices are considered complementary. Best practices from one discipline are successfully applied to reduce the other discipline ’s wastes. Continuous improvement teams are starting to look at solutions that are both Lean and Green. Figure 15. Evolution of Lean and Green Manufacturing Systems

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237 UNIVERSE OF MANUFACTURING WASTES Green Manufacturing System Lean Manufacturing System SYNERGY: The Future, whereby distinctions between Lean and Green systems ends, and Zero Waste Manufacturing is the new holistic manufacturing system. Elimination of all forms of waste is the new corpor ate mantra. Synergy is realized as aggressive efforts to reduce waste results in co ntinuous efficiency, quality, service and environmental improvements. New best pr acti ces evolve as new forms of waste are identified, beyond the present b oundaries of Lean or Green wastes. The Earth itself serves as the model for manufactur ing perfection and the never-ending pursuit of zero waste manufacturers TRANSCENDENCE: The view suggested in this study Companies that are actively implementing Lean or Green manufacturing s ystems not only fully explore the common solutions (intersection of Lean and Gree n best practices) but also start down the path of implementing the other manuf actu ring system. Lean and Green manufacturing systems serve as a dualcatalyst to each other. Employees throughout the company implement a broad set of bes t practice targeting the full spectrum of wastes associated with both Lean and Gr een manufacturing systems. UNIVERSE OF MANUFACTURNG WASTES Zero Waste Manufacturing System Figure 15. (Continued)

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238 The Venn diagrams were helpful in defining a research gap and articulating the research opportunity that formed the basis for this study Was there evidence of transcendence to Green manufacturing by Lean manufactur ers? Specifically, was there a linear correlation between a company’s lev el of Lean system implementation and its level of Green system implemen tation, measured from the perspective of the management system, waste reducing techn iques, and results? This led to the search for objective and credible instrum ents for both Lean and Green manufacturing systems, which measured all three ma jor system components (i.e. management system, waste reducing techni ques, and results). After thorough research, it became evident that the m ost complete and objective measure of the Lean system was the Shingo Prize for E xcellence in Manufacturing, administered by Utah State University’ s School of Business. The Shingo prize has been objectively measuring manufactur ing plants with a panel of Lean experts since 1988. The Shingo prize criteria is now officially the basis for the new national lean certification, that was creat ed in collaboration with the Shingo team, Association for Manufacturing Excellence (A ME), and Society or Manufacturing Engineers (SME), three leading associatio ns of manufacturing excellence. (SME, 2006) The Executive Director of the Shingo Prize, Dr. Ross Ro bson, had recently become aware of the potential relationship of Lean an d Green systems, through conversations with Ross & Associates, who were studying the G reen aspects of Boeing’s Lean efforts, for the EPA. Dr. Robson, was e ager to support further

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239 research on this subject, and granted me confidential acce ss to the Shingo Prize database that housed objective measures of leading Lea n manufacturers best practices. He also provided support of his staff to admin ister an on-line survey to measure the Green practices of these leading Lean manuf acturers. I was fortunate to locate a recent survey on Green m anufacturing best practices (Melnyk et. al. 2003) that categorically mirrored the Shingo scoring system, yet was very user friendly. The survey struck a nice balance b etween brevity and breadth of the Green system by covering the managemen t system, waste reducing techniques, and results, in an efficient twent y-six questions survey. The Melnyk survey was also generic enough to be applicable to any manufacturing sector. All too often, environmental research instrume nts are very industry specific, down to the use of chemical composition (i.e. T RI database, EPA), making it very difficult to compare environmental perf ormance across manufacturing sectors. The manufacturing plants that were deemed eligible f or the study had attained high enough levels of Leanness to earn a site visit by t he Shingo examiners. These companies can all be considered Lean as confirmed b y the panel of experts, but vary in degrees of Leanness based on their Shingo Prize scoring system scores. The one thousand point Shingo Prize scorin g system scale, which covered all critical aspects of the Lean management system, waste reducing techniques and results, provided the ideal set of independent variables for the study. The population of “Shingo” manufactu ring plants was controlled by

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240 the year (2000 and later) of examination to assure th e scores were reasonably accurate depictions of their current states. The year of examination was also used as a control variable in the study to account for ch anges from when the plant was examined and when it completed the Green sur vey. The Green system survey, borrowed from the Melnyk study was administered to the one hundred and ten eligible Shingo plants, via an invitation email from Dr. Ross Robson, the Executive Director of the Shingo Prize. Chris Paulus of USF, created the on-line survey and database to capture Gre en survey results. Each plant was provided a privacy code to enter in the surv ey as a confidential way to key the survey results with the Shingo prize scoring system database. It took several months and several rounds of reminder emails an d phone calls to yield the forty-seven usable responses that comprised the data set for the study. The methodology is detailed on Chapter four of this dissert ation. SAS statistical software was utilized to determine if sta tistically significant correlations existed between Lean and Green system compon ents. This analysis was performed at the high level variables associated wi th the main hypotheses and at the sub-variable level for the individual be st practices and metrics that make up each high level variable for both Lean and G reen systems. Regression analysis was also performed to better understand multi-v ariant relationships. Statistical analysis and full discussion of the results are d etailed in Chapters five and six of this dissertation, respectively, and the conclusi ons are summarized below.

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241 Conclusions 1) Known Lean plants are significantly Greener than the ge neral manufacturing population. The survey statistics of the Shingo plants in this study were compared to the survey statistics from the original Melny k study, which surveyed the general manufacturing population. The results ind icate that the Shingo plants were significantly Greener in all but one of the twen ty-six Green manufacturing system measures. These findings are strong evidence of transcendence to Green manufacturing by leading Lean manufacturers. For all ten Green results variables, the Shingo plants were significantly higher at the P<0.0001 level, than the Melnyk population. Thi s is disproportionate to comparison of statistics of Green waste reducing techniques between Shingo and Melnyk plants. This suggests that having a Lean system infrastructure serves as a catalyst to the successful implementation of co rresponding results of Green best practices. The evidence that plants with Lea n systems yield higher Green results supports the philosophical notion of Lean and Green synergy. 2) Mexican Lean plants are Greener than United States L ean plants. Within the set of Shingo plants utilized in this study, Mexican pla nts exhibit higher levels of Green waste reducing techniques and corresponding results than plants located in the US. The particular waste reducing techniques th at the Mexican plants more readily adopt focus on material conservation, per haps at the expense of additional labor. Mexican plants also seem more incline d to develop industrial partnerships to resolve environmental issues. As a result Mexican Lean plants

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242 experience significantly higher levels of performance f rom their environmental efforts in the areas including quality, sales, market posi tion and reputation. 3) There is a critical need for strategic integration of Lean and Green manufacturing systems at the management systems level. No significant correlations were found between Lean and Green manage ment system variables. Additionally, there were several negative correlations between Green management system and Lean waste reducing techniques, and Lean management system (and strategy), and Green waste redu cing techniques and results. These findings suggest that there is very little integration of Lean and Green manufacturing systems at the management system or strategic level. It has been proven statistically for both Lean and Gre en systems that the management system is critical to create the culture/envir onment that drives the implementation and sustaining of waste reducing techni ques. It was also found that waste reducing techniques strongly correlate to resu lts. Thus, without an integrated Lean and Green management system, it is unl ikely that integration of Lean and Green waste reducing techniques will occur, and synergistic results will be minimal. But, if integration were to occur at the strategic level, it would stimulate holistic approaches to waste reduction and corre sponding synergies at the plant level. Integration of management systems may be the most impor tant and attainable goal of post-doctoral research for the following reason s. The management system articulates management commitment in the form of policy, measurable

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243 objectives, resource allocation, and a formal review pro cess. It is the management system that establishes formal commitment and leadership of the plant’s executives and senior managers. Without it, the re is constant infighting as to what waste reducing techniques should be implemen ted, and they are rarely sustained. With a management system in place, t here is clear and active leadership that prioritizes and synchronizes waste reductio n across the entire plant. In manufacturing plants with weak or no management syste ms, process improvements are localized to the functional area wher e the interested manager can affect change. True systemic waste reduction requires t otal cross-functional collaboration and senior management to remove barrie rs and break the ties when functional managers are at odds. It takes a holi stic and strategic view that weighs the short term needs to the broader, even globa l, challenges of the business and the environment 4) Green manufacturing drives Lean results, particularly i mproved cost performance. Shingo plants that have succeeded in implementing Gree n management systems and Green waste reducing techniques, sh ow significantly higher Lean results than Shingo plants less environment ally inclined. This is an indication of synergy in that Green manufacturing practices simultaneously improve Green and Lean results when implemented in a Lean environment. The fact that Lean results were measured objectively by a t eam of Lean experts, with

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244 little regard to environmental practices, makes this par ticular conclusion very strong. Green variables from all three categories (management system, waste reducing techniques, and results) positively and significantly corr elated to all categories of Lean results (Quality, Cost, Delivery, Customer satisfact ion and profitability). Most striking, is how strongly the Green variables (includ ing GREEN -overall green survey score) correlated to the Lean variable Cost perhaps the most important measure of Lean, as viewed by stakeholders. This is a very powerful conclusion that financially justifies further research int o the integration of these systems into a single Zero Waste Manufacturing strategy. 5) Plants that choose vertical versus horizontal integrat ion of their Lean systems transcend to Green manufacturing. It was found that transcendence to Green manufacturing was significantly stronger in Lean plant s that chose to vertically integrate their Lean systems versus plants that chose to h orizontally integrate their Lean systems. The Lean variable Partnerships measures horizontal integration of the Lean system throughout the extende d enterprise of suppliers and customers. The Lean variable Support functions measures vertical integration of the Lean system within the internal fu nctions of the manufacturing plant. Respectively, Partnerships and Support Functions negatively and positively correlate to a very similar set of Green var iables in all three categories (management system, waste reducing techniques, and result s). The conclusion drawn from these statistics is that manufacturing plants th at implement Lean

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245 holistically throughout all plant functions transcend to holistic approach to waste elimination itself, and embrace Green manufacturing practices. Additionally Partnerships negatively correlates to Support Functions indicating a plant may have to choose, based on resource constraints, t o deploy Lean horizontally or vertically. There are two sayings in the Lean community that speak to vertical integration preceding horizontal inte gration of the Lean system. One is “Clean up you own house, before you ask others to clean up theirs”. The second is when implementing Lean “go an inch wide and a mile deep” (Liker, 2004). Both of these sayings are meant to emphasize the critical importance of institutionalizing the Lean system to the point where it takes hold culturally before moving on the next process of business partner. Else, thi ngs will quickly resume to the old way and the Lean system cannot sustain itse lf. The goal of Lean system implementation is to create a “ learning organization” empowered to continuously eliminate waste. This takes relentless reinforcement. It is easy to imagine how employees in a work environm ent that constantly reinforces the importance of waste elimination develop a keen eye for any form of waste, including environmental waste. It appears fr om this study, the plants that were strongest in vertical integration also were st rongest in Green waste reducing techniques. This illustrates how building a le arning organization of empowered waste eliminators is an essential point of tr anscendence to Green manufacturing.

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246 6) Focus on synergistic Lean and Green practices to optimi ze the finite amount of human resources working on waste reduction. By virtue of the fact that no company has unlimited human resources to work on improve ment projects, priority must be given to projects that eliminate “th e most waste for the buck”. This means prioritizing solutions that maximize Lean and Green synergies and eliminate several forms of Lean and Green wastes simulta neously. There is evidence of best practices negatively correlating with the other systems’ best practices, indicating points of conflict between systems. O n the other hand there are indications of very complementary practices that real ize benefits in both disciplines. Companies interested in improving performa nce results associated with both Lean and Green systems must focus on the comple mentary practices and find alternatives to conflicting ones. 7) It is time to create a Zero Waste Manufacturing system model. This study indicates that there are substantial research opportuni ties to create a holistic Lean and Green manufacturing model that maximizes comp lementary Lean and Green practices and minimizes conflicting practices, to impr ove the efficiency and effectiveness of total waste reduction efforts. The Lean manufacturing system has matured over the past sixty years and is now r eaching a point of total consensus and standardization. Green manufacturing is ne wer than Lean and has yet to realize consensus on a single system model, accep t for the management system component (ISO14001). Given the ma turity and success of Lean, it makes sense to use Lean as the core of the Zero Waste Manufacturing system model.

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247 The fact that Green manufacturing practices serve as a ca talyst to Lean results indicates the great potential for integration. In sh ort, Lean manufacturing can provide the structure and broad acceptance Green manufa cturing has been missing. Green manufacturing will enhance the performa nce of Lean efforts and address ever more pressing environmental issues companies and society face. Uniting Lean and Green into a single well-defined Ze ro Waste Manufacturing system, will realize efficiencies and synergies well beyon d what was found in this study. Besides, now that Lean manufacturing is reaching such a state of maturity and general acceptance, leading edge companies are pr obably looking for ways to differentiate their Lean programs from competitors and are facing growing public pressure to address environmental issues. 8) There may be Zero Waste Manufacturers in our midst. Strong evidence of transcendence and synergy between Lean and Green manufa cturing systems makes me wonder whether some of the companies in this study are already practicing what’s been dubbed “Zero Waste Manufacturing” Granted, it was not proven that all manufacturers get Greener as they get Leaner, but there is evidence that several of the known Shingo plants are st rongly committed to Green manufacturing. What is not known is whether they have attempted to integrate these strategies or do they simply co-exist wit hin the same plant. I very much hope I will have the opportunity to study t he population of the Shingo plants exhibiting the highest levels of Green manufact uring practices and understand where integration exists. I have also spoken to Dr. Jeffery Liker

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248 (Toyota Way) about understanding more about what Toy ota is doing to integrate Green into their Lean systems. Implications for Practitioners Until a Zero Waste Manufacturing (ZWM) model emerge s, practitioners should begin to seek ways to integrate Lean and Green manufa cturing systems within their own plants. This study showed several areas where Lean and Green manufacturing systems are complementary and even synergi stic. Yet it also indicated conflicting practices remain. Practitioners shoul d evaluate their current Lean and Green practices and emphasize the complementary and synergistic practices while seeking alternatives to conflicting practi ces that interfere with the objectives of the other system. Practitioners at the strategic level should focus on int egrating Lean and Green management systems. Manufacturing executives should take a close look at their policy statements, metrics/goals, resource allocation training, management review processes, etc., and begin to integrate them. I ntegrating Lean and Green management systems will encourage cross-functional collabora tion toward minimizing a holistic set of wastes. Lack of integration will cause confusion by employees, who struggle to align their tactical priorit ies with the company’s dual system objectives. Care must be taken in establishing me trics and waste reduction targets that, while broad-based, do not over whelm and paralyze practitioners. Highest priority and resource allocation should be given to

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249 synergistic projects that simultaneously improve several Le an and Green waste metrics. Beyond improving the overall efficiency of waste reduct ion efforts and reducing confusion amongst employees, there is an added benefit t o employee morale when integrating Green into the Lean strategy. Case studies of Green companies indicate how employees are energized working for socially conscious companies trying to make the world safer for them and their children. Environmental and socially conscious behavior on the pa rt of executives creates a trusting environment, which has proven vital to the Lean system. (Smith, 2005) (Hawkins, 1999) Companies serious about Lean make social pacts with employ ees to secure their employment. Employees willingly provide creative solut ions to eliminate waste without fear that efficiency improvements may cost them their jobs (Liker, 2004). Lean companies know that, as the company improves its qu ality and efficiency through total employee involvement they will grow t heir market share and will need all of their employees to meet the future the m arket demand. By adding environmental commitment to management trust, Lean co mpanies can create an ideal work environment that attracts the most creative and talented employees, fueling even greater business success. Perhaps of greatest concern to the executive is the impr ession on the external stakeholder of the business. No doubt, the operational success of an integrated “Zero Waste Manufacturing” strategy will satisfy customers and shareholders

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250 alike. But, there is also the aspect of corporate ima ge. It seems in the past few years, global warming has become front and center in th e minds of consumers, insurers, and even shareholders. It is now true that environmental considerations are required to sell products in the Europ ean Union (ROHS, 2006). Large corporations are lining up to proclaim their commitments to reducing Green house gases. Insurance companies are ver y nervous about the costs of global warming triggered natural disasters and t his is spilling into risk assessment. And, stock traders avoid risky businesses like the p lague. It is no surprise that global corporations are jumping onto the Green bandwagon. As if these factors weren’t stimulus enough for executives to fo rmally integrate Green into their Lean management systems, take a look at “thi s just in” from California. 8/31/06 SACRAMENTO (AP) — California would become the first state to impose a cap on all greenhouse gas emissions, including tho se from industrial plants, under a landmark deal reached Wednesday by Gov. Arnold Schwarzenegger and legislative Democrats. The agreeme nt marks a clear break with the Bush administration and puts California on a path to reducing its emissions of carbon dioxide and other greenhouse gases by an estimated 25% by 2020. "The success of our system will be an example f or other states and nations to follow as the fight against climate change con tinues," Schwarzenegger said in a statement. The bill would require the sta te's major industries — such as utility plants, oil and gas refineries, and cement kiln s — to reduce their emissions of the pollutants widely believed to contribute to gl obal warming. A key mechanism driving the reductions would be a market prog ram allowing businesses to buy, sell and trade emission credits with ot her companies. The bill was praised by environmentalists as a step toward fighti ng global climate change but criticized by some business leaders, who say it would increase their costs and force them to scale back their California operations. "Adopting costly and unattainable regulations will drive businesses and jobs out of California into other states and even into other countries with no commitmen t to improve air quality," said Assembly Republican leader George Plescia, a LaJolla Republican. Notice the argument about the negative effect this can have on industry. Now we have an imperative from the largest and most technicall y advanced industrial state in the US to find approaches to reduce environm ental impact that do not

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251 adversely affect traditional industrial efficiency. I nterestingly enough, due to the market based approach chosen by California and the EU companies that get a head start on reducing Greenhouse emissions can sell the ir credits to companies lagging behind. This means that Green is now a commodi ty. Manufacturing executives now have great incentive to integrate Lean and Green into a single Zero Waste Manufacturing (ZWM) system. Practitioners working at the tactical or process level sh ould seek vertical integration of the Lean system to include Green waste r educing techniques. Going “an inch wide and a mile deep” is good advice f or both Lean and Green system implementation. Solutions like Kan ban systems sati sfy the need to create “pull systems” critical to the Lean system and sati sfy a returnable packaging requirement for Green systems. Another example that comes to mind is to include envi ronmental wastes into the popular Lean technique known as “Value stream mapping” (VSM). VSM is used to look at a plant at a high-level (A single sheet of paper) and identify Lean wastes. The first step is to create a current state ident ifying various forms of Lean wastes with a timeline on the bottom capturing va lue added time versus total lead-time. This is a tool to show at a high le vel the opportunities for waste elimination and to target areas based on the greatest waste reduction potential. Imagine if overlaid on this value stream map were env ironmental waste wastes, such as energy loss, product scrap and hazardous and greenh ouse gas emissions. This would allow the prioritization of pro jects from a total waste

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252 minimization perspective. This is an excellent opportun ity for integration of Lean and Green systems that could be implemented by practitio ners rather easily. Implications for Academics Lean researchers should seek robust measures of the Lean syste m and not watered down versions. I was very fortunate in this stu dy to have access to the most robust and objective measure of Leanness, the Shing o Prize Model database. I believe this made for solid research. Rec ently, the Shingo criteria have now become the national gold standard for the Le an body of knowledge, to which Lean professionals can receive certification. This will serve to standardize Lean systems to the Shingo model, making research based o n this model generally applicable. While it may seem unorthodox, I found the hybrid app roach of using objective data for the Lean variables and a survey instrument fo r the Green variables afforded a strong data set. Previous studies had limit ed measures of Leanness, some missing the boat completely (i.e. King, Lenox’s choi ce to use ISO9000 as their measure for Lean). As time goes on, the Shing o data set only gets larger and there will no doubt be better ways to entice more respondents to similar research in the future. In so doing, future Lean resea rchers can have a very strong and objective measure of Lean without sacrifices t o sample size. I do feel that this study’s focus on operational practice s rather than results is an important implication for future researchers. The man agement system and

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253 waste reducing techniques identified in this study are g enerally applicable to most discrete manufacturers. This opens the door for mor e detailed comparison of a broader set of Green practices and their effect on Lean practices and on Lean and Green results. This could lead to a common set of Green best practices that make for a generally applicable model for a Green manufacturing system. Lean has had over fifty years to settle into a generally applicable system model. Green is still in its relative infancy, and ne eds more time and research to reach the state of the Lean system. It is my sincere belief that any future research effort s to advance the Green model must have an eye toward Lean. It is hard to im agine any discrete manufacturer being interested in a Green system that d oes not complement a Lean system. I dare suggest that perhaps defining an i ndependent Green system model at all may be a futile effort. Instead a Zero Waste Manufacturing system model that leverages the complete Lean manufact uring system for its core and integrates complementary and synergistic Green p ractices will gain broad acceptance in industry. Limitations of Research Study The sample size of fort-seven companies seems small to ma ke such bold claims in this study. Comfort can be taken in the validation process utilized, but there is always greater security in numbers. With every passing ye ar, more companies apply for the Shingo prize, and now that it is the b asis for the national Lean certification, the sample size for future research is grow ing. Standardization of

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254 the Lean model will be very helpful in increasing samp le size for future research on this subject. The survey instrument itself was a limiting factor. To assure high response rates, surveys must be short in nature. This Green survey instr ument was limited, particularly in the area of waste reducing techniques an d result areas. Noticeably missing from both categories were references t o Green house gas emissions and energy, which in the past few years have b ecome a very important issue and should be included in any future G reen study. Also, had time and resources not been a factor, the use of object ive measures as in EPA emissions data would have made for a stronger study. W ork will have to be done to normalize emissions data by industry sector for fair comparison. Also, surveys do not convey the details of what is reall y going behind the scenes that led to the results seen in the survey data. Hav ing worked in manufacturing plants for twenty years, I know there is no substitute f or visiting a plant and observing the process and talking to people throughout the organization. This is why the Shingo examiners conduct thorough site visits. H ad time permitted to conduct case studies of each respondent, it would have yi elded much richer understanding of where integration and conflict were occurring between Lean and Green manufacturing systems components. I sincerely h ope I will be able to conduct such studies as a post-doctoral research effort.

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255 Opportunities for Future Research While this study identified that Lean and Green systems exhibit synergies and have great potential for integration, work must now b egin to better understand integration points. The first step is to create a sing le Zero Waste Management model. The management system is the driving force for any manufacturing system and actually the most attainable point of integr ation. The management system component is the most generally applicable aspect o f the broader manufacturing system, across manufacturing and other ind ustrial sectors. An academic exercise is required to compare and contrast the specific elements of generally accepted Lean and Green management system models. For example, now that the Shingo Lean management system m odel is the national standard, it can be merged with the ISO14001 interna tional Environmental Management System standard, to create a single Zero Wa ste Management (ZWM) system standard. The ZWM model must satisfy the requirements of both Lean and Green management system standards while maximi zing synergies between these systems. The second opportunity is to integrate complementary L ean waste reducing techniques and Green waste reducing techniques into a sin gle robust set of “Zero Waste Techniques” (ZWTs). To achieve this objectiv e, an academic exercise that identifies obvious synergistic techniques (i.e kan ban, value stream mapping) can be combined with field research. Case st udies should be conducted for the plants in this study to understand how they are integrating their

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256 Lean and Green efforts. Companies outside this study kno wn for their strong Lean and Green performance (i.e. Toyota) should also be included in these studies. From these case studies a holistic set of ZWTs can emerge that can serve to build the ZWM model. This leads to the obvious need to create a single set of “ZWM wastes” that an integrated ZWM strategy seeks to eliminate and correspon ding result metrics. The set of Lean wastes has been agreed upon for many ye ars (Defects, Overproduction, Transport, Waiting, Inventory, Motion and excess-Processing (D.O.T.W.I.M.P.)), which has led to the standardizat ion of waste reducing techniques, and a supportive management system. For ZWM to share the same success as Lean, it too will ne ed great specificity at this level. The set of Green wastes will need to be a pplicable and relevant to any manufacturer, or industrial organization, as are the Lean wastes. This will take further research to identify a short list of Green wast es, that when merged with the Lean wastes, creates the dozen or so ZWM wastes. Once this is complete, it will simplify the aforementioned process of identifyin g a holistic set of ZWTs that most efficiently reduces these wastes. Very related to identifying a common set of wastes is t o create a common set of performance metrics. To clarify, the wastes are general ly the physical inefficiencies in the plant that once reduced reflect i n a higher level metric. Examples of this in the Lean world are metrics like qua lity, cost, delivery and cycle-time. Cycle time is known as the driving metric for Lean as it measures

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257 how well product flows through the plant. It is said that a plant with perfect flow must be waste free from a Lean perspective. A similar set of Green metrics must be derived to monito r, or drive, Green waste reduction efforts and integrated with the generally a ccepted Lean metric set. As seen in this study, there are already several common re sult metrics between Lean and Green systems (Cost, quality, etc.) Clearly, g enerally applicable metrics of environmental impact (e.g. Green house and h azardous emissions) would need to be added to this set. All of this resear ch should culminate in a series of articles, books, courses, templates and other tool s to promote Zero Waste Manufacturing. In order to fulfill the philosophical objectives of Su stainable Development and Industrial Ecology, practical tools and instruction are r equired to show people the way. Industrial engineering is an ideal discipline to p romote ZWM research and curriculum development, as it addresses some of the most pressing issues affecting industry today. All of the components of ZW M are core to the industrial engineering discipline. Fervent interest in Lean thro ughout industry, growing concern about Green house gases (i.e. California legisla tion), and the EPA’s desire to “build a bridge” between Lean and Green, p oint to great potential for funded research for industrial engineers on this subject

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258 Summary Perhaps the greatest challenge and opportunity for i ndustrial engineers in the twenty-first century is to devise industrial systems harmon ious with earth’s natural systems. As industrial engineers we must provide solutions that insure local industrial optimization does not come at the ex pense of global optimization and sustainability. In a world were natural resource s are dwindling and human resources are growing exponentially, the traditional i ndustrial engineering notion of efficiency that encourages higher natural resource con sumption per labor hour, seems woefully out of date and dangerously unsust ainable. The key to our sustainable future is proving that industrial and envi ronmental efficiency are not opposing objectives, rather, they are the same objectiv e. This study sought to understand if, in fact, manufacturer s were evolving to this modern view of industrial efficiency by implementing b oth Lean and Green manufacturing systems. By showing how leading Lean man ufacturers are embracing and benefiting from Green manufacturing, th is research will encourage further integration and broader implementa tion of Lean and Green manufacturing systems. I believe that a single integra ted Zero Waste Manufacturing system will simultaneously reduce the envi ronmental impact of manufacturing while assuring economic success, thus fulfill ing the main objectives of Industrial Ecology and Sustainable Develo pment.

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259 References Ahuja, G. (1996). Does It Pay to Be Green? An Empir ical Examination of the Relationship Between Emissions Reduction and Firm Perf ormance. Business Strategy and the Environment, 5 (1), 30-37. Allerton, H.G. III (1990). Hazardous Waste Minimizat ion: Source reduction in the aerospace industry. Journal of Environmental Health 53 (4): 2829 Amaoke-Gyaampah, K., J.R. Meredith (1989). The operat ions management research agenda: an update. Journal of Operations Management 8 (3): 250-262 Arrow, K.J. (1974), The Limits of Organization Norton, New York, NY Barbera, A.J. and V.D. McConnell (1990), The Impact of Environmental Regulations on Environmental Performance: Direct and I ndirect effects. Journal of Environmental Economics and Management 18:50-65. Boerner, C. & Chilton, K. (1994). The Folly of Dema nd Side Recycling. Environment: 36(1): 7-33 Byers, R.L. (1992). Regulatory Barriers to Pollution Prevention. Pollution Prevention Review 4: 19-28 Cattanach, R.E., Holdreith, J.M., Reinke, D.P., Sibik, L.K.(1995) Environmentally Conscious Manufacturing and Marketing Chicago, IL: Irwin. CEEM Information Services (1995). International Environmental Systems Update 2 (4) Chase, R.B. (1980). A classification and evaluation of research in operations management. Journal of Operations Management 1 (1) 9-14 Chase, R.B., E.L. Prentice (1987). Operations Managem ent: a field rediscovered. Journal of Management 13 (2) 351-366 Christiansen, G.B, R.H. Haveman (1981). Public Regulat ion and the slowdown of productivity growth. Journal of Environmental Economics and Management 8: 381-390.

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263 MacDuffie J.P. (1995). Human resource bundles and manuf acturing performance: organizational logic and flexible produ ction systems in the world auto industry. Industrial Labor Relations Review, 48 (2), 197 Maxwell, J., S. Rothenberg, and B. Schenk (2001), Does Lean Mean Green? The Implications of Lean Production for Environm ental Management, Working Paper, MIT, Cambridge, MA. McCarthy, J.E. (1992) Packaging Waste: Can the U.S. lea rn from other countries? Biocycle. 10: 80 83 Meadows, D.H., Meadows, D.L., & Randers, J. (2004) Limits To Growth: 30 Year Update Chelsea: Green Publishing Co. Melnyk, Steven A.; Sroufe, Robert; Calantone, Roger J. (2003). Assessing the impact of environmental management systems on corporate and environmental performance. Journal of Operations Management, 21, 329-351. Miller, J.G., M.B.W. Graham (1981). Production/opera tions management: agenda for the 80s. Decisions Science 12 (4) 547-571 Monden, Y. (1983). Toyota Production System Atlanta: Institute of Industrial Engineers Montabon, Frank; Melnyk, Steven A.; Sroufe, Robert; C alantone, Roger J. (2001) ISO 14000: Assessing Its Perceived Impact on Corporate Per formance. Journal of Supply Chain Management, 2 (36), 2-4 Morris, S.A. (1997). Environmental pollution and Com petitive Advantages: An exploratory study of U.S. industrial-goods manufacture rs. Academy of Management Proceedings, 411-415. Moxen, J., Strachan, P.A., (1998). Managing Green Teams: Environmental Change in Organisations and Networks Greenleaf: Sheffield. National Academy of Engineering, (1997) The Industrial Green Game Washington DC: National Academy Press. National Geographic (2004). Global Warming 206 (3), 1-96 Neely, A. (1993). Production/operations management: research process and content during the 1980s. International Journal of Operations and Production Management 13 (1) 5-18

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265 Sakakibara, S., B.B. Flynn, R.S. Schroeder, W.T. Morri s, (1992). The impact of just-in-time manufacturing and its infrastructure on pe rformance Working Paper 92-8. Minneapolis: University of Minnesota Saunders, T. (1993) The Bottom Line of Green is Black New York: Harper Collins Publishers. Scallon, Monica; Sten, Mark J. (1997) Environmental Posi tioning for the Future: A Review of 36 Leading Companies in the Pacific Northw est Region of the USA. Greening the Boardroom. Sheffield: Greenleaf Publishing, 1997. Schermerhorn, J.R., (1989) Management for Productivity New York, NY: John Wiley & Sons, 1989 Schmidheiny, S. (1992) Changing Course Cambridge: MIT Press Schronburger, R.J.(1982). Japanese Manufacturing Techniques: Nine Hidden Lessons in Simplicity New York, NY: The Free Press Shingo, S., (1989). A Study of the Toyota Production System: From an Indust rial Engineering Viewpoint. Portland, OR: Productivity Press. Shingo (2003). Shingo Prize for Excellence in Manufacturing: Applicati on Guidelines 2003 – 2004 College of Business, Utah State University, Logan, Utah. Skinner, W. (1974). The Focused Factory, Harvard Business Review, 52, 113121 Smith, D. (2005). to be of use Novato, CA. New World Library. Society of Manufacturing Engineers (SME)(2006) Lean Certification Website www.sme.org/leancert Tchobanoglous, G., Theisen, H., Vigil, S., (1993) Integrated Solid Waste Management New York, NY: McGraw-Hill, 1993 The World Commission on Environment and Development. Our Common Future Oxford: Oxford University Press, 1991 Unknown (1990). Special Advertising Section: Earth. Business Week, June 82 121 U.S. Census, (2003). Current Industrial Reports: Pol lution Abatement Costs and Expenditures. U.S. Bureau of Census. Washington, DC : U.S. Government Printing Office

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267 APPENDICES

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268 Appendix A: Expanded Literature Review Shingo Prize Achievement Criteria The Shingo Prize recognizes organizations that use world-class manufacturing strategies and practices to achieve world-class results. All a pplicants who receive a site visit will be publicly recognized as Finalists. Recipients will b e selected from this prestigious group. The Shingo Prize achievement criteria provide a fra mework for identifying and evaluating world-class manufacturing competence and performanc e. The criteria comprise a business systems model for manufacturing excellence, organiz ed into five principle sections as pictured on the previous page. The world-class strategies and practices that are r eferred to in the criteria are presented in sections I through III of these guidelines. World-c lass results are discussed in sections IV and V. There are expected measurements for quality, cost, delivery and business results. Any exceptions to reporting the expected measuremen ts should be reviewed with a representative from the Shingo Prize office. Shingo Prize applicants must prepare an Achievement Report that details key activities and results for each section of the Achievement Criteri a based on relevant facts and data spanning a period of three years or longer should b e reported. Each subsection’s point values serve as a guide to determine the proper amo unt of material to provide. ENABLERS LEADERSHIP CULTURE & INFRASTRUCTURE (Section Total: 150 Points) Implementing world-class strategies and practices r equires an aligned management infrastructure and organizational culture. This sec tion examines the management systems and organizational culture, the inputs or enablers in a systems model that are necessary to deploy world-class practices and achieve world-clas s performance. The two elements evaluated are leadership and empowerment. A. LEADERSHIP (75 POINTS) This subsection is designed to evaluate leadership at all levels of an organization with regard to application of world-class strategies and core b usiness system practices that drive worldclass results. Leadership creates an organizational culture and infrastructure that aligns the company’s mission, strategy and policy to deploy le an/world-class practices and achieve world-class results. Please discuss how your organization uses leadershi p to deploy world-class and lean strategies and practices to achieve world-class res ults. Examples of the items that could provide evidence in this section include, but are n ot limited to: • Statements of vision, mission, values, strategies and goals • A planning process for establishing and deploying vision, mission, values, strategies and goals (e.g., Hoshin Kanri, Policy Deployment, Manag ement By Objective, etc.) • Allocation of resources for deploying vision, mis sion, values and strategy • Sustained personal commitment and involvement of all the organization’s managers to find and eliminate waste, muda, or any non value-added a ctivities and costs • Knowledge management system and business results that are deployed to all levels of the company

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269 Appendix A. (Continued) • Communication and measurement of quality, cost an d delivery standards throughout the organization • An organizational philosophy that encourages and recognizes innovations, entrepreneurship and improvements wherever they ori ginate in the organization B. EMPOWERMENT (75 POINTS) This subsection is designed to evaluate the degree of employee empowerment to effect change within the organization, particularly as it relates to deploying world-class strategies and practices. Employee involvement and empowerment means that a highly specific environment exists that unleashes and fully utilize s each person’s talents, skills, diversity and creativity through individual commitment and te am effectiveness. This evolutionary process gives each employee the opportunity to feel confident, to be heard and to be respected. The result is job enrichment, maximum pr oductivity, achievement of organizational objectives and a continued commitmen t to employee development. Please discuss how your organization uses employee involvement and empowerment to deploy world-class strategies and practices. Exampl es of items that could provide evidence for this section include, but are not limited to: • Magnitude of employee training in world-class pra ctices, separating orientation training from regular employee training • Use of teams (e.g., corrective action teams, cros s-functional teams, process improvement teams and/or self-directed teams) to deploy world-c lass strategies and practices to achieve world-class results • Suggestion systems or other mechanisms that demon strate management’s willingness to receive innovative and/or improvement ideas from al l sources • Recognition and reward systems for the company/pl ant (e.g., gainsharing), teams and/or individuals contributing to demonstrated improvemen ts • Company procedures that facilitate all employees sharing problems and exchanging ideas with customer and/or supplier employees • Measures that document employee satisfaction and morale such as employee turnover, absenteeism and employee survey results • Efforts to maintain an ergonomic, clean and safe work environment for all employees • Specific safety program results, such as, reporta bles and lost time. CORE OPERATIONS MANUFACTURING STRATEGIES & SYSTEM INTEGRATION (Section Total: 450 Points) This section focuses on the core manufacturing stra tegy, practices and organizational techniques deployed to achieve world-class results. It should provide information about the value chain practices and techniques the company us es to achieve world-class results. A. MANUFACTURING VISION & STRATEGY (50 POINTS) This subsection requires an outline of the company’ s manufacturing vision and strategy as it relates to the selection and use of the specific me thods, systems and processes detailed in subsections B, C, and D of this section. B. INNOVATIONS IN MARKET SERVICE & PRODUCT (50 POIN TS) This subsection is designed to evaluate a company’s market service and product innovation. Any available information regarding competitors’ be nchmarking of services and products should be included. Two potential approaches could be pursued: (1) innovative efforts to

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270 Appendix A. (Continued) reduce the cost of existing product(s) and product development; and (2) innovations in market service. Both approaches are viewed as enhan cing business growth and performance. The second approach generally applies to companies that are primarily assemblers or those who manufacture a commodity-typ e product with limited opportunity for new product development. The methods and processes documenting market servic e and product innovation may include, but are not limited to: • Verifiable cost reductions in logistics, sales, s ervice, post sales service, technical support, etc. for an assembler or a manufacturer of a commod ity product • Using quality function deployment, concurrent or simultaneous engineering, etc. for product development • Benchmarking competitors’ products and services • New market development and current market exploit ation • Design for manufacturability, testing, maintenanc e, assembly, etc. • Variety reduction • Converting a commodity-type product to a more spe cialty differentiated product • Innovations in market service and logistics • Broadening sales mediums to include avenues such as e-commerce, the internet, etc. C. PARTNERING WITH SUPPLIERS/CUSTOMERS & ENVIRONMEN TAL PRACTICES (100 POINTS) This subsection is designed to evaluate the company ’s efforts to deploy world-class practices by partnering with suppliers and customer s, and to assess how well the company integrates suppliers and customers into the value-c reation process. Discuss how your organization uses partnering to deploy world-class practices and/or to achieve world-class results. Documentation in this section may include but is not limited to: • The integration of the company, its suppliers and its customers in establishing valuecreating methods and practices across company bound aries in production or product development • Distribution and transport alliances to insure pr oduct quality and productivity • Initiatives regarding environmental issues (i.e., recycling, reducing industrial waste, ISO 14000, etc.) • Supplier satisfaction measures • Union partnership initiatives • Benchmarking projects for process improvement. • Cooperative endeavors with schools and training o rganizations to ensure a qualified workforce • Cooperative community endeavors that demonstrate the company and its employees are socia lly responsible D. WORLD CLASS MANUFACTURING OPERATIONS & PROCESSES (250 POINTS) This subsection focuses on deploying the world-clas s/lean manufacturing practices necessary to achieve world-class performance. This section could include intermediate results and anecdotal evidence concerning the techniques and practices listed below. Please discuss how your organization uses any of th e world-class/lean manufacturing practices or other similar activities. Documentatio n could include, but is not limited to: • Time-based or just-in-time manufacturing • Systematic identification and elimination of all forms of waste • Value Stream Mapping

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271 Appendix A. (Continued) • Value Analysis • 5S Standards and Disciplines • Standardized work • Total productive, preventive or predictive mainte nance • Quick changeover or setup reductions (SMED) • Source inspection and poka-yoke • Visual workplace/visual manufacturing • Cellular manufacturing • Continuous flow • Multi-process handling and autonomation (jidoka) • Pulling work through the production sequence (kan ban) • Distributing work intelligently and efficiently ( heijunka or load leveling) • Six sigma or statistical process control • Theory of constraints • Breakthrough kaizen events (kaikaku) • Tools of quality (i.e., pareto charts, storyboard ing, cause and effect diagrams, 5-why’s or similar problem-solving techniques) • Production Process Preparation (3P) NON-MANUFACTURING SUPPORT FUNCTIONS (Section Total: 100 Points) This section is designed to evaluate (1) the degree of integration between manufacturing and all nonmanufacturing functional units; and (2 ) the extent to which improvement techniques and strategies have been applied in nonmanufacturing functions up and down the value stream (new product development efforts a re detailed in Section IIB and need not be repeated here). Non-manufacturing support functi ons may include accounting, finance, human resources, sales and marketing, materials, pu rchasing, quality, MIS, etc. Address only those non-manufacturing functions that fall un der the scope or control of the applicant site. Evidence could include, but is not limited to, a di scussion of: • Alignment of non-manufacturing functions to suppo rt the manufacturing function • The integration of non-manufacturing functions wi th manufacturing • Incorporation of continuous improvement in the mi ssion or vision statements, goals or strategies of all non-manufacturing functions • Elimination of waste or non-value-added activity in all functional units of the organization (e.g., closing of financial books in hours rather t han days) • Commitment to continuous improvement projects and /or change processes in long-range plans, capital budgets, training and human resource development, marketing plans and strategic reviews by all functional business units OUTPUT RESULTS QUALITY, COST & DELIVERY (Section Total: 225 Points) This section is designed to evaluate the outputs of the core business systems or the performance of the world-class/lean practices descr ibed in sections II and III of the criteria. Evidence in this section includes multiple measures of quality, cost and delivery. Each measurement presented, should be documented with th ree or more years of data. When measurements have been in place less than three yea rs, present whatever data is available. Data reported should show, to the extent possible, not only the trend, but also the performance level attained and potential industry b enchmark comparisons.

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272 Appendix A. (Continued) The current goal for each key measure should be rep orted as well. Note that there are expected measurements for quality, cost, delivery a nd business results. Any exceptions to reporting the expected measurements should be revie wed with a representative from the Shingo Prize office. Results data reported may be b ased on either “profit or cost center” policy. An expected measures spreadsheet and defini tion elaboration will be provided to each applicant upon notification of an intent to ap ply. The spreadsheet must be included in the Achievement Report. Adjustments for extraneous factors such as inflation and changes in product mix should be clearly documented. A. QUALITY & QUALITY IMPROVEMENT (75 POINTS) The objective of the quality & quality improvement category is to insure that no human or machine errors ever get into customers’ hands and t hat in-process defects are continually being reduced. The goal is zero defects. Both trend and level data should be presented and the basis/definition for all quality measurements s hould be reported. Expected measurements: • Rework as a percent of sales or production costs • Customer rejects due to quality (ppm) • Finished product first pass yield and percentage • Unplanned scrap rate(s) Supplemental data could include: • Overall cost of quality as a percent of sales, to tal manufacturing cost or other appropriate baseline • Process variation measures • Warranty cost as a percent of sales • Other appropriate measures B. COST & PRODUCTIVITY IMPROVEMENT (75 POINTS) The purpose of the measured cost and productivity i mprovement category is to assess the improvement trend and level in cost and productivit y. Both trend and level data should be presented and the basis/definition for all cost and productivity measurements should be reported. Expected measurements: • Total inventory turns separated as appropriate in to raw, WIP and finished goods. • Value added per payroll dollar (sales minus purch ased goods and services divided by total payroll dollars) • Manufacturing cycle time (start of product produc tion to completion) Supplemental data could include: • Physical labor productivity (units/direct hour) • Energy productivity • Product cost reduction • Percent machine uptime • Changeover reductions • Resource utilization (e.g., vehicles, plant and w arehouse floor space, etc.) • Transport and logistics effectiveness and cost • Other appropriate measures C. DELIVERY & SERVICE IMPROVEMENT (75 POINTS)

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273 Appendix A. (Continued) The purpose of the delivery and service improvement category is to identify whether customers are getting what they need in the time an d quantity necessary. Both trend and level data should be presented and the basis/defini tion for all delivery and service measurements should be reported. Expected measurements: • Percent of line items shipped on-time (define ontime window) and/or percent of complete orders shipped on-time (define on-time window) • Customer lead time (order entry to shipment) • Premium freight as a percent of production costs Supplemental data could include: • Mis-shipments • Warranty response and service • Other appropriate measures BUSINESS RESULTS (Section Total: 75 Points) This section is intended to evaluation the outcomes of quality, cost and delivery on customer satisfaction and business results. For each measure ment presented, three (3) or more years of results should be documented. Customer Satisfaction Evidence of customer satisfaction may be presented through any valid approach used by the company. Survey data should describe sample size, s urvey format, frequency and efforts to avoid bias. Measures reported must be clearly defin ed and could include, but are not limited to: • Market share • Reorder rate • Customer survey results • Customer awards • Customer audits • Field performance data • Other appropriate measures Profitability Measures of level and trend should be clearly defin ed and should document the unit’s overall relevant business financial attainment. Expected measurements: • Operating income on sales ratio • Operating income on manufacturing assets ratio Supplemental data could include: • Reductions in fixed and/or variable costs • Cash flow • Product line margins • Other appropriate measures

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274 Appendix A. (Continued) Business Prize Scoring System The Shingo Prize Examiners review business applicat ions based on two evaluation dimensions: (1) Strategy & Deployment and (2) Resul ts. Each of the Achievement Criteria’s subsections require applicants to furnish informati on relating to one or both of these dimensions. Sections I through III refer primarily to information on Strategy & Deployment. Sections IV and V refer primarily to overall organi zational results. However, it is fully appropriate to include “intermediate” results (numb er of leadership initiatives, number of teams, team participation rates, number of suggesti ons per year, cycle time reduction in a specific process, etc.) in sections I through III. Specific factors relating to each evaluation dimens ion are described below. Strategy & deployment Strategy is the means, processes or methodologies a n organization pursues to achieve its business plan and manufacturing goals. Deployment i s the action the organization takes to achieve the intended strategy. Scoring is based on: the acceptance and use of Shingo’s comprehensive view of “waste” as any non-value added activity and its prevention as the only path the degree of organizational focus on value-added activities the existence of goals focused on continuous impr ovement and world-class manufacturing the understanding of the importance of business p rocesses as an area for analysis and improvement the effective use of appropriate tools, technique s and technologies in a variety of improvement initiatives the demonstrated cooperation and integration betw een employees’ efforts at all levels Results Results are an organization’s demonstrated achievem ents in reaching each manufacturing and business goal. Scoring is based on: the demonstrated improvement trend in each key ar ea the level of performance in each key area the use of outside benchmarks in intelligent goal setting the choice and use of appropriate measures for ea ch specific purpose, and the proper technical adjustments the intelligent use of the measured results to st imulate further improvement Scoring Guidelines When using this scoring grid, select the quadrant t hat tends to best describe the company’s current practice based upon the individual descript ors, then qualitatively decide whether the current practice is high, mid, or low. A qualitativ e percentage is selected and multiplied by the point value of the criteria element to determin e a current practice score. Strategy & deployment Organizations which fully match the descriptors wou ld score at the top of the indicated range, etc. 100% I 80% • tenacious strategic focus on high-value-added pro cesses and issues • major, fully completed waste prevention applicati ons that could be considered best practices examples • clear and ingrained use of all appropriate human and technical resources in an integrated manner

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275 Appendix A (Continued) 80% I 60% • recognition of strategic priorities with frequent consideration beyond day-to-day issues • many good waste-prevention projects, some of whic h are around key processes and issues • frequent use of appropriate human and technical r esources to reach beyond the conventional solution, but occasional problems in g etting integrated action 60% I 40% • existence of some strategic ideas but rarely appl ied systematically • a few good waste-prevention/reduction application s, more are planned as time permits • some use of human and technical resources beyond conventional, but difficult to get integrated cooperation and action 40% I 20% • no evidence of strategic focus; reactive only to day-to-day issues • minor, incomplete, limited-value applications of waste reduction • no evidence of use of human and technical resourc es in problem solving Results Organizations which fully match the descriptors wou ld score at the top of the indicated range, etc. 100% I 80% • excellent improvement trends in key strategic are as and within the wasteprevention projects • high and predictable levels of performance with a ctive programs based on goal setting • creative choice of appropriate indicators with de monstrated validity • evidence of ingrained, routine feedback of result s to those responsible for improvement 80% I 60% • generally good improvement trends in the key stra tegic areas and in improvement projects • good level of performance in most areas and proje cts; some attention to goal setting • appropriate measures used with demonstrated valid ity • good evidence of feedback of results to those inv olved in improvement on a regular basis 60% I 40% • good improvement trend in some key areas and appl ications • reasonable-to-good level of performance in some a reas and applications • adequate choice of measures used but little demon strated validity • little evidence of results feedback as a routine 40% I 20% • no apparent improvement trend in key areas; mixed results in applications • levels of performance that are either low or not predictable • poor choice of measures and insufficient use • no evidence of systematic feedback of results Eligibility The Business Prize may be awarded to any qualifying applicant in each of the following categories. 1. Large manufacturing companies, which can include : Whole Company Division or Business Unit Single Plant 2. Small manufacturing companies, which can include : Whole Company

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276 Appendix A. (Continued) Division or Business Unit Manufacturing entities in existence three or more y ears, located and operated in the United States, Canada or Mexico that conform to the U.S. S tandard Industrial Classification (SIC) of Manufacturing are eligible to apply for the Prize. For individual entities engaged in both service and manufacturing, classification is determ ined by the larger percentage of sales. Additional eligibility requirements that an entity interested in challenging for the Shingo Prize must meet include the following: If a single applicant business entity individuall y comprises more than 50 percent of the business unit, then the entire business unit must b e included in the application, unless the business unit can provide a substantive justificati on that the remaining entities are not integral to the operation of the business unit or a pplying entity. Questions regarding eligibility should be clarified prior to submitting the Intent to Apply Form. A Prize Recipient is ineligible to re-apply for t he Prize for five years. At least 50% of the business’ revenue must be der ived from manufacturing activities. Small businesses are defined as independent corpora te entities with fewer than 500 full-time equivalent employees. Small businesses may challeng e for the Prize provided that the above provisions are met. A division or business un it of a small company may apply as a separate entity. In order to apply, the entity must be operated essentially as a complete business. Large businesses are defined as corporate entities with 500 or more full-time equivalent employees. Large business entities may challenge fo r the Prize according to the following provisions. Manufacturing business entities (subsidiaries, bu siness units, divisions and plants) wishing to apply must have at least 50 full-time equivalent employees and have clear lines of distinction from other organizational units. Separa te organizational units of a large business may compete individually, but must apply in the lar ge business category, regardless of the number of employees in the specific unit. Multiple entities within one company, subsidiary, business unit, or division may apply individually in the same year, unless the applying entities together comprise a clear majority of the next larger business unit (i.e., company, su bsidiary, business unit or division), in which case the application will automatically be consider ed on the basis of the larger entity. APPLICANTS NEED TO PROVIDE 1. Intent to Apply Form organizational informatio n sufficient to determine eligibility (see page 19). 2. Achievement Report written documentation of th e company’s efforts and achievements in manufacturing excellence conforming to the crite ria outlined in these guidelines. The Achievement Report should generally not exceed 100 pages. Examination Process All applicants who receive a site visit will be pub licly recognized as Finalists. Recipients will be selected from this prestigious group. The examination process has four steps. First, Achi evement Reports are submitted and distributed for review by members of the Board of E xaminers. The review will occur prior to

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277 Appendix A. (Continued) September 1, 2003. High-scoring applicants are desi gnated as Finalists and will receive site visits. Second, site visits will be conducted betwe en approximately September 1st and November 22nd each year. Third, based on the applic ation review and the site visit results, the Board of Examiners will recommend Finalists to the Shingo Prize Board of Governors to become Prize Recipients. Finally, the Board of Gove rnors reviews the recommendations and may either ratify or reject the Board’s recommendat ions. Companies will be notified by the end of January. Decisions made by the Board of Governors are final and are not subject to appeal. Business applicants will receive written feedback on notable accomplishments and opportunities for possible improvement based upon the items reviewed during the Achievement Report and the site visit. SITE VISITS Candidates for the Shingo Prize will receive a site visit by a team of examiners. A single facility application will generally require a team of five ( 5) to eight (8) examiners. The primary objective of the site visit is to verif y, clarify and amplify the information contained in the Achievement Report. In terms of clarification, companies should be prepared to update all metrics reported in their Achievement Report during the site visit.

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278 Appendix A (Continued) The Russo Model Methodology: Sample: The study explored the adoption and impact of ISO 140 01 within a sample of electronics plants, broadly defined. The plant, or faci lity, was chosen as the unit of analysis for two reasons. First, it is facilities—not firm s—that are registered under ISO 14001. The ISO 14001 registration process was desig ned specifically to operate at this level, as it was patterned after the ISO 9000 quality standards (Tabor, Stanwick, and Uzumeri, 1996). Second, data wi thin the Toxic Release Inventory is organized at the plant level, and aggre gation beyond that level creates imprecision. In order to balance the need for a viabl e sample size with comparable industry environments, six segments of the electronics in dustry were selected for analysis: SIC 3571 (Electronic computers), SIC 3651 (Hou sehold audio and video equipment), SIC 3661 (Telephone and telegraph equip ment, SIC 3671 (Electronic tubes), SIC 3672 (Printed circuit boards), and SIC 367 4 (Semiconductors and related devices). Thus, there is a high degree of commo nality to the sample, responding to criticism of studies with samples that are too dispersed (Griffin and Mahon, 1997). The numbers of observations for the two studies are shown in Table 1. I used as the population all facilities in these seg ments where manufacturing took place and which employed at least 100 persons. Data fur nished by Dun and Bradstreet listed 1104 such establishments. A university survey research center randomly selected and contacted facilities from the set of 1104 facilities in early 2000. A tota l sample of 316 facilities provided interview data. Given that 95 of the original 1104 sites were not actually manufacturing sites or were used for other lines of bu siness, the interviewed sample consisted of 31.3% of the population. All facilities we re contacted multiple times, and the main reason for non-response was inability to g et to the respondent either due to absence or having an answering machine respond to all interview attempts. Refusals by respondents were a relatively minor occurren ce, at roughly 5% of nonrespondents. When contacting firms, in order to avoid biases, interviewers did not leave phone messages, as this might have affected the ch ance of a return phone call. The level of success we enjoyed might be due to t he relative lack of knowledge about ISO 14001, the desire of environmental manager s to receive copies of the results of this study, or a desire to improve the netwo rk among environmental professionals. In early 2001, a second wave of surveys w as sent to firms that had not yet registered to ISO 14001 to ascertain whether o r not they had done so. Of the 316 facilities that were contacted, a number wa s dropped from each analysis because the interviewee did not provide inform ation on all variables that were used in analyses. In addition, for the study of toxic releases, an additional 196 facilities had to be handled differently because they d id not produce enough toxic emissions for any effluent to report to the Environmen tal Protection Agency (This raises the issue of selection bias, with which is explicitly a ddressed below). Table 1 provides a summary of the available facilities and obser vations for the adoption study and emissions study, organized by Standard Indust rial Classification area.

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279 Appendix A (Continued) Study Period. I used the years 1996 through 2000 for the study of ISO 14001 adoptions. Although the ISO 14001 standards were fin alized in late 1996, their general nature was well known prior to that point, a nd in fact several respondents claimed to have “registered” earlier in 1996. This i s feasible, since the drafts of ISO 14001 were available by 1995 (Epstein, 1995). For the emissions study, as toxic emissions data is only available through 1999, that yea r is the last one used in that analysis. Variables Dependent Variable. To explore whether or not environmental performa nce is influenced by ISO 14001 registration, I needed a defe nsible measure of environmental performance. The development and use o f metrics in this area are a challenge (Committee on Industrial Environmental Per formance Metrics, 1999). One candidate, environmental reputation scores, are h ighly correlated with financial returns (Brown and Perry, 1995) and calculated at the firm, not facility level. Fines and/or spill performance might also be used, but these a re episodic in nature, and might not pick up the continuous nature of emissions perf ormance. A better approach than either of these is to use data from the E nvironmental Protection Agency’s Toxic Release Inventory, or TRI. This database contains information on the release of 579 individually listed chemicals and 28 chemical categories on a facility-by-facility basis. Using TRI data raises several methodological issues. The first issue arises from the wide variation of toxicities of the substances that are emitted by plants. Some are highly and immediately toxic, while others are of less concern. In order to address this problem, I used a method originated by Kin g and Lenox (2000). This consisted of dividing each chemical by a quantity used by the EPA to set an upper limit on what could be discharged without having to re port an incidence of a spill to the EPA. These “reportable quantities” vary with the toxicity of a given substance; the more toxic the substance, the lower the reportable quantity. Reportable quantities run from 1 to 5000 pounds. At the limit, a report must be made if just 1 pound of a highly toxic chemical is emitted (for exampl e, methyl isocyanate, which was released in Bhopal, India, in 1984). For a given facility and year, I divided each chemical emitted by a facility by these reportable quan tities, and then aggregated across the chemicals released at a facility to produce wha t is called a “release index.” Because this data was highly skewed, the logar ithmic transformation (after adding 1) was taken prior to using this variable and i ts lagged values. Using the dependent variable and its lag effectively estimates cha nges in emissions from year to year. Independent Variable. For the study of emissions, the independent variable was a dichotomous variable, coded 1 if the facility had ISO 14001 registration, and 0 otherwise. Because information on the month and year of registration was on hand, a facility was considered registered for a year if it wa s registered for at least half of the year. If it registered later, it was coded as bei ng registered during the next year. Once registered, all facilities in the sample stayed reg istered in subsequent years. In using the date that an EMS was operational, a measu rement issue arose. In order to receive ISO 14001 certification, an EMS mu st be in place at the facility. Therefore, a confound would exist if an EMS that was cr eated as part of ISO 14001

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280 Appendix A (Continued) registration was treated equally with those that existe d prior to registration. To address this issue by allowing for time lags, an EMS was coded a s being in place if it was operative for at least a full year prior to the year in question. So for example, an EMS that went into effect in 1996 would result in the EM S variable being coded 1 from 1998 forward. For earlier years, the variable would be co ded 0, as it would for any facility that had no EMS. Control Variables. It was important to account for the influence of othe r factors on ISO 14001 adoption and toxic emissions. The effect of si ze was controlled by including the number of employees at each facility. It would have been better to obtain actual outputs for facilities, but this is classified information. Instead, I used an estimate for the number of manufacturing employee s for each of the years 1996 through 1999, taken from interviewees. Also included was the age of the plant, to try to pick up any influence of its vintage. Because plants routinely go through upgrades, I tried to reduce the impact of variation among older plants by employing the natural logarithm of plant age in calculations. To pick up the effect of overall environmental regul ation in the state, based on Meyer (1995) I included a measure of total toxic relea ses per dollar of state GDP. Two controls pick up ownership patterns within the sampl ed firms. Two dummy variables were coded one if the owner of the plant wa s Japanese or European, and were coded 0 otherwise. Remaining plants were owned by American companies or had corporate parents based in other countries. Press re ports suggest that the Japanese embraced ISO 14001 enthusiastically, and some obse rvers have argued that the system may be preferred by European plants to the Eco-Management and Audit Scheme (EMAS) system often used in Europe. Becau se California is generally viewed as the location of cutting edge manufa cturing in this industry, I included in regressions a dummy variable set equal to 1 if the plant was located in California. Also included were dummy variables for each of the 6 4 -digit SIC code groups, omitting SIC 3571 to avoid overdetermination. For one of the analyses of firms reporting TRI emissions, no facilities from SIC 3571 ha d data, so SIC 3651 was omitted. If there are any inherent differences in th e profiles of emissions for industries, these should be picked up by these dummy var iables. Finally, I included dummies for the years 1997 through 2000 for the ado ption study, and 1997 through 1999 for the emissions study, in both cases omitting 199 6 to avoid overdetermination. Statistical Methods. In the study of ISO 14001 adoptions, event history methods were used to analyze the adoption of ISO 1400 1 (Tuma and Hannan, 1984). The methodology is specifically developed to an alyze discrete events occurring within time. For example, events such as the co rporate takeover bids (Davis and Stout, 1992), entry into new markets (Have man, 1993) and dissolution of strategic alliances (Park and Russo, 1996) have been anal yzed with this technique. Essentially, event history methods are well-suited to lo ngitudinal situations where events take place across a specified time period. To th e extent that changes in the independent variables are associated with longer or shor ter waiting times until

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281 Appendix A (Continued) registry occurs, statistical significance is generated. It could be said that event history compares to logistic analysis as pooled, cross-secti onal time series analysis compares to cross-sectional analysis. The difference in b oth cases is that multiple time periods are involved, and each “individual” (her e, the facility) contributes an observation to the data set for each time period. Th e exponential specification was employed to model events. Because the ISO 14001 standards were basically sketched o ut by the beginning of 1996, time was measured in months from January, 1996 until registry for a given facility occurs. If no registry occurs, the facility contrib utes is considered “rightcensored,” a situation that event history methods were specifically developed to address. Once registration takes place, a facility is cod ed as having experienced an event, and removed from analysis in subsequent years. T he number of observations does not equal the number of years times t he number of facilities for two reasons. In two cases, plants were closed prior to th e study period end, and for a larger number of cases, facilities were opened subsequ ent to 1996. Both of these situations are easily accommodated with the RATE progra m. For observations for the year 2000, the length of the spells varied. If t he facility adopted ISO 14001, the months until adoption were used. For non-adopters, t hree months was used unless the facility was contacted in the second wave of surveys, in which case, twelve months was used. Both types of non-adopters were consid ered censored cases. In estimations of emissions performance, I used the two types of regression analyses to test hypotheses that are described below. Th ere was a potential for heteroskedasticity in the regression, as heteroskedastici ty was found in a previous study that used TRI data (Klassen and Whybark, 1999). T wo tests for heteroskedasticity in the emissions study were conducted. First, I used the Goldfeld-Quandt test to test whether residuals varied w ith either the number of employees or toxic emissions. In both cases, the test sug gested no relationship. The more general White (1980) test was also applied t o the data, and it too indicated that heteroskedasticity was not evident. A more serious potential problem with the study of e missions concerns the lack of Toxic Release Inventory data for facilities and emissi ons. Making the situation especially noteworthy is that the chance that data is missi ng is tied to the level of emissions itself: unless a facility manufactures or processes m ore than 25,000 pounds or otherwise uses at least 10,000 pounds of any o f EPA’s listed chemicals, it does not report to TRI (United States Environmental P rotection Agency, 2001). This was the major reason for missing emissions data. A secondar y reason and much less frequently-occurring reason was that TRI identificati on numbers for several facilities could not be found, even after substantial e fforts to track down this information. Altogether, missing TRI data occurred for more than half of observations that had all other variables on hand. It is possible that this situation can produce sample sele ction bias (Heckman, 1979), because if facilities fail to report to TRI, the ir emissions reductions will not affect the estimates for emissions. So a sample selectio n correction was undertaken using a SAS “macro” program designed for t he purpose. This program corrects for any selection bias by creating an additiona l variable, l that captures the

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282 Appendix A (Continued) effect of emissions on the chance of not reporting to TR I. The coefficient on l should be positive, based on the fact that the greater the emissions, the more likely is a facility to make a TRI report. Even with a sample selection bias correction, the number of observations is small relative to the whole sample. In an effort to includ e all observations in an analysis, a final analysis was conducted with a Tobit approach that c ould accommodate censored data (Johnson and DiNardo, 1997). This model i s appropriate when the dependent variable is only reported when it is above or below some level. In using this model, the data from the many non-reporting faci lities can contribute its full richness, rather than acting solely through the sample se lection bias variable, l In order to conduct this analysis, a key tradeoff had to b e made because the missing lagged values had to be modeled. So to estimate the lagged effects, two variables were entered. The first is a dummy variable that is co ded 1 if the facility reported data in the last reporting period, and zero otherwi se. The second variable picks up the reported emissions themselves, and is set equal to th ose lagged emissions if reported, and zero otherwise. Together, these variab les model a process where reported emissions step upward after a threshold level, and then increase with the level of actual lagged emissions. The analysis used, an option within the SAS LIFEREG routine, explicitly accounts for observations for which the dependent variable is missing. In all regressions, a fixed effects model was employed With this specification, a string of dummy variables—one for each facility—is included in the model. These dummy variables have the effect of setting a separate i ntercept term for each facility, which is a powerful method for accounting for many factors that are specific to the various plants (Hsiao, 1986).

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About The Author Gary G. Bergmiller obtained a Bachelor of Science in Electrical Engineering from Northeastern University in Boston Massachusetts. He receive d his Masters of Science in Engineering Management from the University of South Florida. His research interests include Lean manufacturing, Green (env ironmentally conscious) manufacturing, sustainable development, and cont inuous process improvement cultures. Gary has spent 20 years in indust ry helping corporations such as GE, Philips, and Cox Enterprises create continuou s improvement cultures and is currently Principle of Zero Waste Manufa cturing, a research and consulting firm. In the Spring of 1997 Gary commenced work on his Ph.D. which he received from the University of South Florida in 2006