Tag Six Sigma Chap One

7/30/2019 Tag Six Sigma Chap One

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MASTERING LEAN

SIX SIGMA


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MASTERING LEAN

SIX SIGMA

ADVANCED BLACK BELT

CONCEPTS

SALMAN TAGHIZADEGAN

MOMENTUM PRESS, LLC, NEW YORK


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Mastering Lean Six Sigma: Advanced Black Belt Concepts

Copyright Momentum Press, LLC, 2014.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system,

or transmitted in any form or by any meanselectronic, mechanical, photocopy, recording, orany otherexcept for brief quotations, not to exceed 400 words, without the prior permission

of the publisher.

First published by Momentum Press, LLC

222 East 46th Street, New York, NY 10017

www.momentumpress.net

ISBN-13: 978-1-60650-404-8 (hardback, case bound)

ISBN-10: 1-60650-404-5 (hardback, case bound)

ISBN-13: 978-1-60650-406-2 (e-book)

ISBN-10: 1-60650-406-1 (e-book)

DOI: 10.5643/9781606504062

Cover design by Jonathan Pennell

Interior design by Exeter Premedia Services Private Ltd. Chennai, India

10 9 8 7 6 5 4 3 2 1

Printed in the United States of America


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In memory of my parents who asked so little and gave so much,

God bless their soul

To my loving wife, Leila who makes my life so beautiful and our daughters Sara and

Setareh who bring so much joy to our lives.

I love you more than life itself


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vii

Contents

Preface xix

acknowledgments xxi

aboutthe author xxiii

Part I desIgnand develoPthe requIred Processes (the need) 1

1 masterIng lean sIx sIgma PrIncIPles 3

1.1 Lean Six Sigma: Theory and Constraints 3

1.1.1 What Is Lean Six Sigma and What Lean Six Sigma Can Do for You? 3

1.1.2 Statistically What Is Six Sigma? 5

1.1.3 What Is Lean Concept? 6

1.2 Lean Six Sigma Master Black Belt 7

1.3 Lean Six Sigma Black Belt Overview 71.3.1 Dene 8

1.3.2 Measure 9

1.3.3 Analyze 11

1.3.4 Improve 11

1.3.5 Control and Sustain 11

2 lean sIx sIgmaand masterblackbelt roles (who Isthe leader?) 13

2.1 Master Black Belt Roles in the Organization 13

2.2 Master Black Belt (MBB) Qualication 14

2.2.1 Leadership Roles 14

2.2.2 Technical Activity Roles 17

2.2.3 MBB Job Description 17

2.2.4 Completion of Curriculums 18

2.3 MBB Program Development 21

2.4 Decision-Making SolutionsEvaluating Alternatives 21

2.5 Developing and Utilizing a Professional Network 22

2.6 Employee Empowerment and Motivation Techniques 22


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viii Contents

2.7 Efcient and Effective Coaching, Training, and MentoringSelf-Directed 23

2.8 Advanced Presentation Skills 23

2.9 Rewards and Recognition 24

3 lean sIx sIgma Infrastructure: desIgnIngand engIneerIng

(lean sIx sIgma dePloyment) 25

3.1 Initiate Financial Growth Need Projects 25

3.2 Elements of Successful Six Sigma Implementation 28

3.2.1 Management System Support and Commitment 28

3.2.2 Well-Trained Belts 29

3.2.3 Well-Dened Projects and Infrastructure 29

3.2.4 Lean Six Sigma Success Models 29

3.3 Roadmap for Deployment Phase 31

3.3.1 Envision Financial Growth Needs Projects 31

3.3.2 Launch the Project Initiative 31

3.3.3 Engineer, Execute, and Manage the Project 32

3.3.4 Continuous Progress and Maintaining the Momentum 32

3.3.5 Changing the Way Organizations Work 32

3.4 Strategies to Overcome Organizational Resistance to Changes 33

3.5 Converting Goals/Objectives into Actionable Projects 33

Part II launchIngthe objectIves 35

4 launchIngthe lean sIx sIgma Project InItIatIve:

what worksand what doesnt 37

4.1 SWOT Analysis 37

4.1.1 Strength 38

4.1.2 Weakness 38

4.1.3 Opportunities 39

4.1.4 Threats 39

4.2 Project Selection Criteria 40

4.3 Making the Others Buy in and Support for Your Projects 42

4.3.1 Identify Project Stakeholders 42

4.3.2 Analyze Project Stakeholders 43

4.3.3 Create Project Stakeholder Plan 43

4.4 Six Sigma Teaming 43

4.4.1 Barriers to a Six Sigma Culture 43

4.4.2 Why Team? 44

4.5 Six Sigma Teaming: Forming/Storming/Norming/Performing model 44

4.5.1 Forming or Orientation 45

4.5.2 Storming of Dissatisfaction 46


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CONTENTS ix

4.5.3 Norming or Resolution 47

4.5.4 Performing or Production 48

4.5.5 Adjourning 48

4.6 Conict Management: The Five Conict Handling Modes 49

4.6.1 Avoiding 49

4.6.2 Accommodating 49

4.6.3 Collaborating 49

4.6.4 Competing or controlling 49

4.6.5 Compromising 49

4.7 Conict Resolution 50

4.7.1 Effective Conict Resolution Behaviors 50

4.7.2 Key Conict Points to Consider 50

4.7.3 Conict and Power 50

4.8 Leadership Decision-Making Processes and Tools 51

4.8.1 Decision-Making Approaches 51

4.8.2 Decision-Making Tools 51

4.8.3 Team Decision Through Consensus 53

4.9 Project and Process Assessment Matrix 53

4.10 Six Sigma Financial Reporting (Using Financial Measurement

to Analyze Performance) 54

4.10.1 Plan of Action 54

4.10.2 Financial Accountabilities 56

Part III LeadIngthe effort

5 LeadIngand engIneerIng MuLtIPLe Lean SIx SIgMa ProjectS 59

5.1 Managing Multiple Project and Project Reviews 59

5.1.1 Project Management and Reviews 59

5.1.2 Why Review? 59

5.1.3 Holding Reviews 60

5.1.4 Lean Six Sigma Black Belts: The Criteria for Selection 60

5.2 How to Master the Skills of Lean Six Sigma Facilitation 66

5.2.1 How to Become an Effective Facilitator 66

5.2.2 Strategic Roles of the Facilitator in the Organization 66

5.2.3 Effective Elements of Communication Strategies and Skills 67

5.2.4 Time your Time from Time to Time 68

5.2.5 Building Team Commitment and Interactions 68

5.3 Communication Planning 68

5.3.1 Six Sigma Project Communication 685.3.2 Communication Plan Considerations 69


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x Contents

5.4 Project Closure 71

5.5 Lean Six Sigma Master Black Belt Deployment Plan 71

5.6 Case Study: Lean Six Sigma Deployment Plan 72

5.6.1 Strategy and Goals for Six Sigma 72

5.6.2 Performance Metrics (Overall Program) 73

5.6.3 Project Selection Criteria 73

5.6.4 Project Identication/Prioritization 73

5.6.5 Organization Structure/Roles 73

5.6.6 Training Requirements 77

5.6.7 Management Review Process 78

5.6.8 Communication Plan 78

6 desIgnand develoP organIzatIonal lean sIx sIgma roadmaP:

delIverIng contInuous breakthrough Performance 85

6.1 Roadmap for Successful Corporate Results 85

6.2 Design for Lean Six Sigma Process 85

6.3 Vision of Lean Six Sigma Process 86

6.3.1 Where and When Do We Use Lean Six Sigma? 86

6.3.2 Why Use Lean Six Sigma? 86

6.4 Design for Lean Six Sigma Roadmap 86

6.4.1 Phase 0: Concept and Ideation 87

6.4.2 Phase 1: Dene, Feasibility, and Planning 87

6.4.3 Phase 2: Designing and Developing 87

6.4.4 Phase 3: Verifying and Validating the Developed Design 88

6.4.5 Phase 4: Production and Commercializing 88

6.4.6 Phase 5: Control and Sustaining 88

6.5 Lean Six Sigma Continuous Process Improvement Roadmap 90

6.5.1 Phase 0: Concept 90

6.5.2 Phase 1: Dene 916.5.3 Phase 2: Measure 91

6.5.4 Phase 3: Analyze 91

6.5.5 Phase 4: Improve 92

6.5.6 Phase 5: Control and Sustaining 92

6.6 Leading the Efforts 92

6.6.1 Project Report and Reviewing Progress 93

6.6.2 Communication 94

6.6.3 Awards and Appreciation 94

6.7 Maintaining and Gaining the Momentum 94


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Contents xi

6.8 Tollgate Review 94

6.8.1 Develop a RACI Matrix 96

6.9 Lean Six Sigma Culture and the Way it Works 97

7 defIne concePtsand strategIes 99

7.1 Concepts, Vision, and Ideation Phase 99

7.2 What is Six Sigma Dene Phase 100

7.3 Lean Six Sigma Variation 102

7.3.1 Positional Variation 104

7.3.2 Cyclical Variation 104

7.3.3 Temporal Variation 106

7.4 Lean Six Sigma Project Selection Process 106

7.4.1 Business Strategy 107

7.4.2 Financial Impact Analysis 107

7.4.3 Operational Engineering 108

7.5 Lean Six Sigma Process Management and Project Life Cycle 109

7.5.1 Business Process Management 109

7.5.2 BPM Project Life Cycle 111

7.6 Who is a Customer? 112

7.7 Voice of Customer 113

7.8 Kano Model of Quality 1137.9 SWOT (Strength, Weaknesses, Opportunities, Threats) Analysis 114

7.9.1 Strength 114

7.9.2 Weakness 115

7.9.3 Opportunities 115

7.9.4 Threats 115

7.10 Project Scope, Charter, and Goals 115

7.11 Lean Six Sigma Metrics and Performance Measures 120

7.11.1 Critical to Quality 121

7.11.2 Critical to Business and Voice of Business 122

7.11.3 Cost of Quality 122

7.12 Specic, Measureable, Attainable, Realistic, Time-Phased 124

7.12.1 Specic 124

7.12.2 Measurable 124

7.12.3 Attainable (Achievable) 124

7.12.4 Realistic 124

7.12.5 Time-Phased 125

7.13 Force Field Analysis 125

7.13.1 Dene the Current Process Problem 125


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xii Contents

7.13.2 Dene the Improvement Goals 126

7.13.3 Dene the Driving Forces 126

7.13.4 Dene the Restraining Forces 126

7.13.5 Establishing the Comprehensive Change Strategy 126

7.13.6 Force Field Analysis Example 126

7.14 Tollgate Review and Checklist for Dene Phase 126

7.14.1 Dene Phase Deliverables and Checklists 128

8 measure concePtsand strategIes 131

8.1 The Seven Quality Control Tools for Measurement 131

8.1.1 Cause-and-Effect Diagram (Fishbone or Ishikawa) y = f(x) 131

8.1.2 Data Collection (Process Measurement and Characterization):

Voice of Customer (VOC) 134

8.1.3 Pareto Chart 135

8.1.4 Histogram 137

8.1.5 Scatter Diagram and Correlation 138

8.1.6 Control Charts 139

8.1.7 Stratication (Trent, Flow, or Run Chart) 140

8.2 The Design of Seven Management/Planning Tools 141

8.2.1 Afnity Diagram 141

8.2.2 Interrelationship Diagram 142

8.2.3 Tree Diagram 143

8.2.4 The Matrix Diagram or Matrix Chart 144

8.2.5 Matrix Data Analysis 145

8.2.6 Process Decision Program Chart (PDPC) 146

8.2.7 Arrow Diagram (the Activity Network Diagram) 146

8.3 Process Mapping 147

8.3.1 SIPOC Chart (Supply, Inputs, Process, Output, Customer) 148

8.3.2 Value Stream Mapping 150

8.4 Kaizen Events: Planning and Execution 151

8.5 Lean: Improves Efciency/Six Sigma and Improves Effectiveness 153

8.6 Quality Function Deployment 154

8.6.1 What is QFD Quality? 154

8.6.2 Building a House of Quality 154

8.7 Measurement System Analysis (MSA) 157

8.8 Process Measurement 158

8.8.1 Data Collection 158

8.8.2 Principles of Variation 160

8.8.3 Type of Variation 160


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Contents xiii

8.8.4 Type of Data 160

8.8.5 Science of Statistics 160

8.8.6 Classication of Numerical Data 162

8.8.7 Qualitative Data (Nominal or Ordinal) 162

8.8.8 Quantitative Data (Interval or Ratio) 162

8.8.9 Sampling Strategy 164

8.8.10 Data Analysis 165

8.9 Tollgate Review and Checklist for Measure Phase 165

8.9.1 Measure Phase Deliverables and Checklists 166

9 analysIsof concePtsand strategIes: advanced statIstIcal

analysIsachIevIng ultImate Performance scIentIfIcally 167

9.1 Descriptive Statistics 167

9.1.1 Descriptive Statistics Techniques and Graphing: Stem and Leaf 172

9.1.2 Histogram 178

9.1.3 Measure of Center Tendency 179

9.1.4 Measures of Variability 180

9.2 Descriptive Measures 195

9.2.1 Measurement System Analysis 195

9.2.2 Accuracy/Bias 195

9.2.3 Stability (Consistency) 1959.2.4 Linearity 195

9.2.5 Gage Repeatability and Reproducibility (or Gage R&R) 197

9.2.6 Measurement System Components 198

9.3 Probability Distributions and Concepts 199

9.3.1 Denition, Experiment, Outcome, and Sample Space 199

9.3.2 Probability of Event (Ei) as Relative Frequency 201

9.3.3 Marginal and Conditional Probabilities 203

9.3.4 The Rules of Probability (Union of Events) 205

9.3.5 The Rules of Probability (Intersection of Events) 209

9.4 Discrete Random Variables: Probability Distribution 214

9.4.1 Binomial Probability Distribution 216

9.4.2 Poisson Probability Distribution 224

9.4.3 The Hypergeometric Probability Distribution 226

9.5 Continuous Random Variables Probability Distributions 227

9.5.1 Normal Probability Distribution 227

9.5.2 t-Distribution 242

9.5.3 Normality Test 243


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xiv Contents

9.5.4 Exponential Distribution 244

9.5.5 Reliability Engineering 244

9.6 Inferential Statistics and Sampling Distribution 247

9.6.1 Random Sampling and the Distribution of the Sample Mean 247

9.6.2 Central Limit Theorem (CLT) 256

9.6.3 Condence Interval for the Mean (m) of Normal

Population (s known) 259

9.6.4 Condence Interval for the Mean (m) of Normal

Population (s unknown) 263

9.6.5 Selecting the Necessary Sample Size 266

9.7 Hypothesis Testing, Inferences Procedures, and Proportions Testing 268

9.7.1 Hypothesis Testing for the Mean (m) and Variance (s2)

of the Population 272

9.7.2 p-Value Application 279

9.7.3 Hypothesis Testing Usingp-value Approach (Using Equal Mean) 281

9.7.4 Hypothesis Testing on the Mean (m) of a normal

Population for Small Sample 284

9.7.5 Inference Procedures for Two Populations: Applying the Concepts 288

9.7.6 Comparing Two Normal Population Means (m1m

2)

Using Two Small, Independent Samples: Apply the Mechanics 292

9.7.7 Comparing the Variance of Two Normal Populations (s1

2s2

2)

Using Independent Samples-F test (Small Sample Size):

Apply the Mechanics 301

9.7.8 Estimation and Testing for Population Proportions 304

9.7.9 Condence Interval for a Population Proportion: Large Sample 304

9.7.10 Hypothesis Testing for a Population Proportion 306

9.7.11 Comparing Population Proportion: Two Large

Independent Samples 313

9.8 Advanced Analysis of Variance (ANOVA) 319

9.8.1 One-Way Analysis of Variance 319

9.8.2 Randomized Block Design and Analysis of Variance 339

9.8.3 Two-Way Analysis of Variance 348

9.9 Linear Regression Analysis 360

9.9.1 Scatter Plots and Correlation Analysis 360

9.9.2 Simple Linear Regression Model and Analysis 364

9.9.3 Linear Regression Model 364

9.9.4 Least Square Criteria 365

9.9.5 Inferences on the Slopeb1, Concept: t-Test 375


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Contents xv

9.9.6 Condence Interval forb1

Slope 380

9.9.7 Prediction by Regression Analysis: Condence Interval

for an Individualy, Givenx 381

9.10 Multple Regression Analysis 385

9.10.1 Multiple Linear Regression Model Building 386

9.10.2 Hypothesis Testing and Condence Interval 390

9.10.3 Polynomial and Nonlinear Regression Model Building 397

9.11 Tollgate Review and Deliverables for Analysis Phase 398

9.11.1 Analysis Phase Deliverables and Checklist 399

10 Improve ConCeptsand strategIes 401

10.1 Advanced Lean Six Sigma Experimental Design 401

10.1.1 Experimental Design Terminology 402

10.1.2 Elements of an Experimental Design 404

10.2 One-Factor-At-A-Time Design (OFATD)x1,x2, ...,xk 405

10.3 Full Factorial Design 407

10.3.1 How to Calculate the Effects 408

10.4 Fractional (Reduced) Factorial Design (FFD) 421

10.5 Robust Engineering Design and Analysis 427

10.6 Response Surface Designs and Process/Product Optimization 438

10.7 Central Composite Design (CCD): Optimum Design 439

10.8 Failure Mode Effect Analysis (FMEA) 453

10.9 Poka-Yoke (Japanese term for mistake proong, pronounced

Poh-kah Yoh-kay). 458

10.10 5S Kaizen Principles 459

10.10.1 SI = Sort (Seiri) 459

10.10.2 SII = Set in order (Seiton) 459

10.10.3 SIII = Shine (Seiso) 459

10.10.4 SIV

= Standardize (Seiketsu) 460

10.10.5 SV = Sustain (Shitsuke) 46010.11 Tollgate Review and Deliverables for Improve Phase 460

10.11.1 Improve Phase Deliverables and Checklist 461

11 Control ConCeptsand strategIes 463

11.1 Process Control Strategy 463

11.2 Process Control Objectives 463

11.3 Sustaining the Improved Process 464

11.4 Ten Essential Process/Quality Control Tools 465


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xvi Contents

11.5 Control Chart Types 470

11.5.1 X-bar (x) and R-Chart 470

11.5.2 R-Chart Limits Models 472

11.5.3 Steps for Developing X and R Charts 474

11.6 p-Chart: Attribute Control Chart 475

11.7 cChart 478

11.8 Control Limits versus Specication Limits 479

11.9 Process Capability Ratio, Cp and Cpk 480

11.10 Tollgate Review and Deliverables for Control Phase 484

11.10.1 Control Phase Deliverables and Checklist 484

12 case studIes: lean sIx sIgma aPPlIcatIons 487

12.1 Defect Reduction in Injection Molding Production Components 487

12.1.1 Dene Phase 487

12.1.2 Measure Phase 492

12.1.3 Analyze Phase 496

12.1.4 Improve Phase 499

12.1.5 Control Phase 501

12.2 Overall Equipment Effectiveness: A Process Analysis 502


12.2.2 Measure Phase 50512.2.3 Analyze Phase 507



12.3 Powder Coat Improvement 513


12.3.2 Measure Phase 517

12.3.3 Analyze Phase 519



aPPendIces 527

APPendIxI HIghlIghtsofSymbolsandAbbrevIatIons 529

aPPendIxII statIstIcal tablesand formulas 530

aPPendIxIII valuesofy = exP(h) 538

aPPendIxIv dPmo toSigmato yIeld% conversIon table 540

aPPendIxv standard normal dIstrIbutIon 542

aPPendIxvI crItIcal valuesoft(t-dIstrIbutIon) 544


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Contents xvii

aPPendIxvII crItIcal valuesof chI-square dIstrIbutIon

wIth degreesof freedom 548

aPPendIxvIII uPPercrItIcal valuesofthe f-dIstrIbutIon 553

aPPendIxIx cumulatIve PoIsson ProbabIlIty dIstrIbutIon table 566

aPPendIxx cumulatIve bInomIal ProbabIlIty dIstrIbutIon 574

aPPendIxxI confIdence IntervalforPoPulatIon ProPortIon: small samPle 597

aPPendIxxII scorecardforPerformance rePortIng 605

bIblIograPhy 607

Index 609


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xix

PrefaCe

In an environment of intense global economic competition in which competitors with the

objective of lowering product manufacturing costs are embracing robust manufacturing, servic-

ing, and technologies, a new method of thinking such asMastering LeanSix Sigma is required

in order to outperform the manufacturing techniques of the competition. A proactive way ofmeeting the increasing competition is to focus on maximizing productivity and achieving qual-

ity at the lowest manufacturing cost and at a faster rate than the competitors, in addition to

building capacity to continuously introduce new ideas of quality/ reliability and process opti-

mization methodologies. These measures lead to highest customer satisfaction and a robust

bottom line.

Mastering LeanSix Sigma provides Advanced Black Belts concepts (ABC). This is one

of the fundamental building blocks of any organizations Lean Six Sigma deployment, be it a

manufacturing organization or performing transactional processes. The development of a Mas-

ter Black Belt program is a critical component of corporate success in the strategic implementa-

tion of Lean Six Sigma objectives.This book has been developed to help organizations deploy Six Sigma and support certied

Master Black Belts with the necessary preparation so that they face the challenge of managing

multiple Lean Six Sigma projects and lead a company-wide Six Sigma initiative.

Becoming a Master Black Belt involves a great deal more than just learning advanced

statistical tools and methodologies.Mastering Lean Six Sigma provides students with a com-

prehensive Lean Six Sigma leadership and analytical tools, methodologies and road maps to

drive successful implementation of Lean Six Sigma and other process improvement techniques

within the organization.

The curriculum takes students beyond the tools and techniques that they practiced and

mastered during the Black Belt projects and provides them with the techniques to manage and

lead an overall Lean Six Sigma program. Various Lean Six Sigma examples and case studies

are given throughout the text in addition to analysing what makes a successful Lean Six Sigma

program, the pitfalls to avoid, and how these can be translated into success of the organization.

Mastering LeanSix Sigma provides an overview of various Lean Six Sigma tools, which

are analyzed clearly in graphical forms with many examples from manufacturing or transac-

tional practices. They are aimed at the following:

i. Creating the need for organizational strategic goals

ii. Launching the objectives and leading the efforts

iii. Developing the Lean Six Sigma roadmap DMAIC (dene, measure, analyze, improve,

control) and DDVPC (dene, design, verify, production, control). DDVPC is for new

product in either manufacturing or services


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xx Preface

iv. Complete and comprehensive analysis of DMAIC, DDVPC methodologies, statistical

tools, with numerous examples and graphics

v. Various case studies with step-by-step DMAIC and DDVPC phases

Mastering Lean Six Sigma is aimed at preparing and coaching Black Belts in leading,

teaching, training black belts/green belts in Six Sigma methodologies and statistical analysis

skills to help them deploy full Lean Six Sigma initiatives.

KeYWOrDS

Mastering Lean Six Sigma, Advanced Black Belt concepts, Lean Six Sigma mastering, Six

Sigma Defne Concepts and Strategies, Six Sigma Measure Concepts and Strategies, Six Sigma

Analysis Concepts and Strategies, Six Sigma improve Concepts and Strategies, Six Sigma Con-

trol Concepts and Strategies, Lean Six Sigma Roadmap


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xxi

aCknowledgments

Much of my appreciation goes to my family. To my loving wife, Leila, and our daughters, Sara

and Setareh, thank you for your long-lasting patience and continuous support. The completion

of this project would have been impossible without your full support and for that I cant thank

you enough. Further I would like to thank my colleagues and especially my students for theirextensive support throughout the program.

Finally, my thanks to Joel Stein at Momentum Press for his support and patience through-

out the publishing process and other members of the Momentum Press team for their support

and assistance in making this book a reality.


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xxiii

aboutthe author

Salman Taghizadegan, Ph.D. is one of the leading Lean Six Sigma masters who has extensive

experience in Lean Six Sigma teaching, coaching, and training students academically through

universities with industrial projects. Further, he teaches and practices plastics processing,

design, control, and analysis. He received B.S. in Chemistry from Western Illinois University,B.S. in Chemical Engineering from the University of Arkansas, M.S. in Chemical Engineering

from the Texas A&M University, and Ph.D. in Chemical Engineering with emphasis on plastics

and control from the University of Louisville.

He has over 25 years of academic and full-time industrial experience in Lean Six Sigma,

plastics engineering, chemical processing, design, and control engineering, primarily in injec-

tion molding industries. He has authored numerous technical publications along with his rst

book in Six Sigma entitledEssential of Lean Six Sigma. He has spent most of his professional

career as an adjunct professor in engineering, as a highly technical specialist in Lean Six Sigma,

in the plastics industry, as a leader in quality and process improvement, as well as managing of

waste reduction in the manufacturing environment. Dr. Taghizadegan is certied Black Belt andMaster Black Belt through the University of California at San Diego. Currently he is teaching

Lean Six Sigma Green Belt, Black Belt, and Master Black Belt at the California State Univer-

sity in addition to his full-time industrial career.


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PART I

DesignanD Developthe RequiReDpRocesses (the neeD)


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3

CHAPTER 1

MasteRing lean six sigMapRinciples

In an environment of intense global economic competition in which competitors with the objec-

tive of minimizing product manufacturing costs are embracing robust designing, product devel-

opment, production, servicing, and technologies,Mastering Lean Six Sigma offers leadership

skills, Six Sigma tools and methodologies to key players who aim to outperform the manufac-

turing techniques of their competition. A proactive way of meeting the increasing competition is

to focus on maximizing productivity and achieving quality at the lowest manufacturing cost and

at a faster rate than the competitors, in addition to building capacity to continuously introduce

new ideas of quality and reliability engineering and robust process optimization methodolo-

gies. These measures lead to highest customer satisfaction and a robust bottom line. Virtually,

Mastering Lean Six Sigma fuels top talent players with powerful ideas to create a breakthrough

performance by arriving at solutions for unsolved problems.

1.1 LEAN SIX SIGMA: THEORY AND CONSTRAINTS

1.1.1 WHAT IS LEAN SIX SIGMA AND WHAT LEAN SIX SIGMA CAN DO FOR YOU?

If you want to know what is Lean Six Sigma? and what it can do for you? then you might

ask yourself the following questions:

Are you ready for world-class performance?

Are you prepared to overtake your competition?

Are you ready to experience the ultimate in process accuracy and speed?

Do you want to improve your return on capital investment?

Do you want to increase your market share?

What about just Lean and what it can do for you? Lets review some of the questions

related to Lean as follows:

Do you have a cost disadvantage against your competition?

Is your process affected when an employee is absent or products are out of stock?


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4 MASTERING LEAN SIX SIGMA

Are you meeting the timelines for customer orders or request?

Are people below par in productivity or resources underutilized?

Do you have reinspection or perform lots of rework?

These are just a very few of the many questions related to Lean Six Sigma (LSS) process

improvements. Now lets start reviewing the Six Sigma science of continuous improvement.

Six Sigma simply means a measure of quality that strives for near perfection. It is a disciplined,

data-driven approach and methodology for eliminating defects (driving toward six standard

deviationsbetweenthemeanandthenearestspecicationlimit)inanygivenprocess,beit

manufacturing or transactional, product or services.

As the Sigma level increases, quality improves and therefore costs go down. Customers

becomemoresatised asa result.Furthermore,workingsmarternotharder,withfewermis-

takesatdifferentstagessuchasmanufacturing,llingoutapurchaseorder,nancialreporting,

and employee turnover improve overall performance . In short, it brings world-class perfor-

mance to a company and helps it overtake the competition by bringing in the ultimate in pro-

cess accuracy and speed. It also improves the return on invested capital and increases market

value.

There are four LSS success factors:

1. Selecting the right project: Six Sigma is all about selecting the right project that sup-

ports the business/engineering strategies and is linked to the goals of the organiza-

tion. This should be the key issue that must be solved if the organization wants to be

successful.

2. Right people:SixSigmaisallaboutselectingandtrainingtherightpeopletollthekey

roles.SuccessfulorganizationsselecttheirbestpeopletollthekeySixSigmapositionsas sponsors, champions, black belts, and green belts.

3. Project management and gate reviews:Six Sigma is all about effectiveness. Manage-

ment and steering committee for gate reviews are critical to the success of the company.

Lack of management review reduces the impact of the Six Sigma effort.

4. Sustaining the gain and improvement: Any technique for maintaining the gains is an

integral part of the Six Sigma approach. At a tactical level, this technique maintains

the individual projects.At a strategic level, it is the continual identication ofnew

projects for continuous improvements. The Six Sigma breakthrough model is shown

inFigure1.1withthreeobjectives:higherprots,maximizedvalues,andminimized

variation.

Figure 1.1. Six Sigma performance.

Six Sigma

Performance

Stepup

- Process management

- Customer driven

- Statistical analysisDeliverresults

- Higher profits

- Maximum values

- Minimized variation


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MASTERING LEAN SIX SIGMA PRINCIPLES 5

1.1.2 STATISTICALLY WHAT IS SIX SIGMA?

Sigma:Bydenition,Sigma(),aGreekletter,isthestatisticalqualitymeasurementofstan -

dard deviation from the mean. Six Sigma describes how a process performs quantitatively. Inother words, it measures the variation of performance.

Normal distribution curve: Normal distributions are probability curves that have the same sym-

metricconguration.Theyaremirrorimageswithrespecttothetargetsuchthatsampledataare

more concentrated at the center of the curve than in the tails. The term bell-shaped curve is often

used to describe normal distribution. The area under the distribution curve is unity. The height

of a normal distribution can be expressed mathematically in two parameters: mean (m) and stan-

darddeviation().Themeanisameasureofthecenterofthecurveorthemeanistheaverage

of all the points on the curve, and the standard deviation is a measure of spread from the mean.

Themeancanbeanyvaluefromminusinnitytoplusinnity(inbetween),andthestan-

dard deviation must be positive. Thus, the probability off(x) (Equation 1.1) is equal to 1.

+

= =

f x x( )d Area under th ormal distribution curve1 e n (Eq. 1.1)

Suppose thatx has a continuous distribution, then for any given value ofx, the function

must meet the following criteria:

f(x) 0 for any eventx in the domain off.Since the normal distribution curve (symmetric from the mean) meets thex-axisatinnity

asshowninFigure1.2,theareaunderthedistributioncurveandabovethe x-axis is assumed

to be 1.This can be calculated by integrating the probability density on a continuous interval

fromminusinnitytoplusinnity.

So, Six Sigma is a statistical measurement of process history (in the past as well as current).

Its focus is on how good the companys product and service really is. Or, how far ahead or

behind the company is from the industry standard. It allows the company to benchmark quality,

and determine which direction should be taken to achieve the desired quality and how it can

Figure 1.2. Normal distribution curve

(symmetric) area equal unity.

m

+


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benallyachieved.Inaperfectworldaprocessproduces99.9999998%defect-freeworkper

million opportunities (or 0.002 defects per million). However, in the real world, the processes

uctuateandshiftby1.5Sigma.Thistranslatesinto99.99967%defect-freeworkpermillion

partsor3.4defectspermillionopportunities(DPMO).Thisisvisualizedin Figure1.3. For

detailsrefertoChapters711thatdiscussSixSigmaapplicationandtools.

1.1.3 WHAT IS LEAN CONCEPT?

The core concept is to maximize the customer value while eliminating the waste to near zero

as possible. So Lean is a technique of reducing the cycle time and non-value-added work,

resources,steps,andothers.Furthermore,itisabusinessorengineeringstrategythathelps

organizations to gain competitive advantage over the other players. An organization with a

Lean culture establishes the ultimate goal of providing perfect value to the customer through

a process that generates zero waste. One of the misconceptions is that Lean is applied only in

the manufacturing environment. However, Lean applies to every process of a businesses or an

organization. Some of the Lean goals are as follows:

1. Minimize lead time, process time (cycle time), and add value by removing waste (the

non-value-added work). Simply, it is a strategy of removing waste from any process.

The waste could be result of overdoing, delay, excess steps, unutilized talent, defects,variation, or quality issues. Anything that doesnt add value to the end user or customer

is considered to be waste.

2. Apply value stream mappings with multiple process steps that run the process from start

tonish.Inotherwords,mapouttheboundariesoftheend-to-endprocess.Itprovidesa

high level of extremely effective process view to ascertain the roadblocks and assists one

to focus on improvement opportunities.

3. Continuously apply Kaizen process improvement. Kaizen is a Japanese term that

stands for improvement or change for the better. It refers to continuous process

improvement.

4. Implement best practices and build in quality.

5. Put to use the talent of employees.

Figure 1.3. Normal distribution curve shifted by 1.5totherightorleftofthe

target.

6 5 4 3 2 1 +1 +2 +3 +4 +5 +6

UPPER

SPECIFICATION

LIMIT

LOWER

SPECIFICATION

LIMIT

X

+1.51.5


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Figure1.4isaLeanprocessmappingowchart.Thechartillustratestheautomationopera-

tion change from product A to product B. It includes the steps that add value, that are

essential with no value added, and that are non-value-added.

SeealsoChapters7and8foradetaileddiscussionofLeanapplicationtools.

1.2 LEAN SIX SIGMA MASTER BLACK BELT

Master Black Belts (MBB) is one of the foundational building blocks of any successful LSS

organization. The development of MBBs is a critical success factor in the deployment of Six

Sigma process improvement strategy. The tools in this book have been developed to design

a successful LSS program. This will provide certiedMBBs with the necessary prepara-

tion to meet the challenge of managing multiple projects and leading company-wide LSS

initiatives.

Becoming an MBB involves a great deal more than just learning advanced statistical

techniques. It provides the students of MBB with the comprehensive LSS leadership tools,

methodologies, and road maps to drive successful implementation of LSS and other process

improvement methodologies within the organization. The curriculum takes students beyond

the tools and techniques that they practiced and mastered during the Black Belt project. Ittrains students with the techniques to manage and lead an overall LSS program. Various LSS

case studies are included in Chapter 15 and they are analyzed to propose what makes a suc-

cessful LSS program, the pitfalls to avoid, and how these can be translated into organizational

success.

1.3 LEAN SIX SIGMA BLACK BELT OVERVIEW

An MBB program focuses on advanced LSS statistical methods used in LSS project phases, which

aredene,measure,analyze,improve,andcontrol(DMAIC).InadditiontoBlackBelttools,

we cover new tools in areas such as study of variation, multivariate experiments, nonparametric

Figure 1.4. A Lean process with value-added and non-value-added steps.

No

YesQuality

inspection Pass

Change-over

requested

Operators prepares

for change

Machine is

changed

Call

engineering

Start

production

Find root

cause

Fix problem

EE

E

Value-added operation

Essential non-value-

added

Non-value-added

operation


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analysis, destructive testing, handling attribute responses (beyondFreeman-Tukey), practi-

cal experimentation, optimization experiments, handling multiresponse experiments, dis-

tributional analysis, advanced regression methods, advanced Statistical Process Control

(SPC)methods, andmuchmore.Abrief reviewof theclassication,goals, andobjectivesof the LSS in DMAIC follows. The detailed phases with practical examples are explained in

Chapters712.

1.3.1 DEFINE

There is no destination without a starting point. Every road or project has a beginning and

anendingpoint.Denephase is the stepone, the startingpoint oftheprojectwithstrate-

gic planning objectives. It is a road map to get to the destination and to achieve the deliv-

erable results that is envisioned at the startingpoint. The elementsofdenephaseare as

follows:

1. Project charter (to include business case)

2. Project plans, boundaries, and timeline

3. List of deliverables

4. Stakeholder analysis

5. Voice-of-customer (VOC), critical-to-quality (CTQ)

6. Kano model analysis

Denealsoidentiesthetypeofprojectthatrelatestoeitheranexistingprocessimprove-

ment in production or a new product/service development through the use of two Six Sigmasubmethodologies: DMAIC and DMADV.

Existing product or

services

Define the project

Measure the current process in production or services

Analyze the existing measurement using statistical tool

Improve the process under study by deployment of world class benchmark and tools

Control the improved process and continue to monitor

Process characterization and optimization

New product or

services

Define the goals and objectives of the project

Measure the identical process for selected criteria

Analyze the measurement criteria

Design the new process or product

Verify the developed process or product

Process characterization, development and verification


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A model of process improvement using Six Sigma tools and techniques for processes in the

productioncycleisshowninFigure1.5.

A model of process improvement using Six Sigma tools and techniques for a new product

orserviceisshowninFigure1.6.

1.3.2 MEASURE

Measure phase is step two of the DMAIC or DMADV process. It focuses on numerical research

and root cause analysis. The objective of this phase is to get as much information as possible

Figure 1.5. Six Sigma improvement model for an existing product or service.

Objective

Define

Identify business drivers

Identify critical-to-quality

Define customers needs

Measure

Develop key process inputs/

outputs

Identify the vital few with greatest

impact

Collect and analyze data

Estimate process capability

Analyze

Apply cause and effect

Create multivari analysis

Determine variance components

Assess correlation

Improve

Develop and evaluate solutions

Implement variation reduction

Standardize process Assess risk factor

Control

Establish process control

Develop control charts for key

variables

Apply mistake proof processes

Continously evaluate results

Tools and techniques

Define

Affinity diagram

Interrelationship diagram

Quality functin deployment

SIPOC process map

Project charter

Measure

Data collection plan

Check/data sheet

Pareto chart

Gage R&R/voice of process

Histogram/process capability

Analyze

Cause & effect

Multivari chart

Scatter diagram

Apply statistical tools

Apply regression analysis

Improve

Experimental design

Deployment flow chart

Tree diagram Failure mode effect analysis

Control

Process control plan

Cotrol chart

Poka-Yoke

Pareto chart (on-going)

Process capability (on-going)


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Figure 1.6. Six Sigma improvement model for a new product or service.

Objective

Define Define project charter

Identify business drivers

Identify critical-to-quality

Define customers needs

Process mapping

Define stakholders

Measure

Develop process variables

Identify the vital few

Collect and analyze data

Estimate process capability

Analyze

Apply cause and effect

Create multivari analysis

Determine variance components

Assess correlation

Design

Develop and evaluate solutions

Implement variation reduction Standardize process

Assess risk factor

Kaizen techniques

Pull system/cellular concept

Verify

Establish process control

Develop control charts

Apply mistake proof processes

Continously evaluate results

Lean metrics

Tools and techniques

Define

Affinity diagram

Interrelationship diagram

Quality functin deployment

SIPOC process map

Project charter

Value stream maaping

Measure

Data collection plan

Check/data sheet

Pareto chart

Gage R&R

Histogram/process capability Existing process control chart

Analyze

Cause & effect

Multivari chart

Scatter diagram

Apply statistical tools

Apply regression analysis

Design

Define critical-to-process

Desingof experiment Response surface methodology

Process simullation/

Risk analysis

Pilot test plan

Verify

Process control plan

Cotrolchart

Poka-Yoke

Pareto chart (on-going)

Process capability (on-going)

on the existing process or service so as to fully understand how well it operates. This entails the

following key deliverable factors:

Creating a detailed process map

Establishing the baseline data (current six-sigma level)

Summarizing and examining the collected data

Identifying key measurment variables and communicate

Measure

deliverables


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1.3.3 ANALYZE

The Analyze phase is the third step and the longest phase in the LSS methodology. This phase

applies all the statistical analysis tools available for use. Almost all the essential measurementanalysis is carried out in this step. The root cause inputs that affect the key outputs of the pro-

cessorthesystemunderinvestigationareidentiedandmeasurestoeliminatethemarepro -

posed.Thus,thesignicanceofinputsontheoutputsisdetermined.Someofthedeliverables

in this phase are given below:

Analyzing the collected data

Applying root cause analysis-relationship between input and output

Determining the gap variations and improvement opportunities

Analysis

deliverables

1.3.4 IMPROVE

The Improve phase is the fourth step that requires knowledge of identifying and reducing the

keyprocessinputsthatcausetheeffects(output).Thus,inthisphase,thesolutionisidentied,

implemented, and the process variations reduced substantially. The return on invested time,

planning, testing, optimization, and execution are achieved. The key deliverables in this phase

are as follows:

Optimize and test the improved process

Identify the best possible process

Design implementation and standardization plan

Wastes removed, just-in-time flow established

Improve

deliverables

1.3.5 CONTROL AND SUSTAIN

TheControlphaseisthenalstepanditconcludesaswellassustainsthegainsmadeinthe

process. The process performance and capability are determined and documented.

Control and sustaining plan/ record process capability

Operating procedures and document

Transfer of ownership to production (project completion)

Control

deliverables

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