Quality Management for Organization Using Lean … Management for Organization Using Lean Six ... perspective on quality 10 1.4 Total quality management and ... 2 Six Sigma-IE interface

Quality Management

for Organization Using

Lean Six Sigma

Techniques

Erick C. Jones

CRC Press Taylor & Francis Group Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Croup, an Informa business

Contents

Preface xxvii Acknowledgments xxix Introduction xxxi Author xxxv

Section I: Modern quality and Lean Six Sigma overview

Chapter 1 Overview of modern quality 3 1.1 Introduction 3 1.2 What is quality? 3

1.2.1 How is quality defined? 3 1.2.1.1 Global approach 3 1.2.1.2 Product-based approach 3 1.2.1.3 User-based approach 4 1.2.1.4 Manufacturing-based approach 4 1.2.1.5 Value-based approach 4

1.3 What do organizational departments or functions think about quality? 6 1.3.1 Functional perspectives on quality 6

1.3.1.1 Engineering perspective on quality 6 1.3.1.2 Operations perspective on quality 6 1.3.1.3 Systems perspective on quality 6 1.3.1.4 Executive management perspective on quality 7 1.3.1.5 Marketing perspective on quality 8 1.3.1.6 Financial perspective on quality 8 1.3.1.7 Human resources perspective on quality 10

1.4 Total quality management and quality overview 10 1.5 Who is taught and trained to attain quality by an Organization? 11

1.5.1 The Implementation of quality 11 1.5.1.1 The integrated approach 11 1.5.1.2 Three spheres of quality 11

1.6 What if quality is too expensive to justify? 12 1.6.1 "As-needed" Implementation of quality 12

1.7 Limitation of quality measures 12 1.8 How can the COQ be justified? 13

1.8.1 Cost of quality 13 1.8.2 Traditional COQ 13

v

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1.9 Who started quality and what ideas did they contribute? 14 1.9.1 Quality philosophers, gurus, and contributors 14

1.9.1.1 William E. Deining 14 1.9.1.2 Joseph M. Juran 14 1.9.1.3 Philip B. Crosby 15 1.9.1.4 Armand V. Feigenbaum 15 1.9.1.5 Garvin 15 1.9.1.6 Ishikawa 15 1.9.1.7 Taguchi 15 1.9.1.8 Japanese contributions to quality 15

1.10 How is quality rewarded and enforced globally? 16 1.10.1 Quality awards 16

1.10.1.1 The Deining Prize 16 1.10.1.2 Malcolm Baldrige National Quality Award 16 1.10.1.3 European Quality Award 17

1.11 Quality Standards 18 1.11.1 ISO 9000 18 1.11.2 ISO 14000 and 14001 18

1.12 Integrating QM with LSS techniques 19 1.13 Will LSS really work? 19 1.14 How can I integrate LSS into the Operations throughout my supply chain? 20 References 20 Further Reading 21

Chapter 2 Quality gurus and philosophies 23 2.1 Introduction 23 2.2 William E. Deming 23 2.3 Joseph M. Juran 24 2.4 Philip B. Crosby 24 2.5 Armand V. Feigenbaum 24 2.6 Garvin 25 2.7 Ishikawa 25 2.8 Taguchi 25 2.9 Japanese contributions to quality 25

References 26 Further Readings 26

Chapter 3 Quality awards and Standards 27 3.1 The Deming Prize 27

3.1.1 Categories 28 3.1.2 Deming Prize and TQM 28 3.1.3 Deming Prize in detail 29

3.2 The Malcolm Baldrige Award 30 3.2.1 Baldrige model for quality 30 3.2.2 Six Sigma method 31 3.2.3 Baldrige model and Six Sigma 31

3.2.3.1 Implementing Six Sigma within the Baldrige model 32 3.2.3.2 Füll Integration 33

Contents vii

3.2.4 A quality alliance 34 3.3 ISO 9000 34

3.3.1 Purpose 35 3.3.2 ISO 9000—Performance 36

3.4 Other quality awards and Standards 36 3.4.1 Strategie quality planning 36 3.4.2 European Quality Award 37 3.4.3 Quality Systems 38

References 38 Further Reading 39 Appendix 3A: A relationship between Six Sigma and Malcolm Baldrige

Quality Award 40 3A.1 Introduction 40 3A.2 The Baldrige model for quality 40 3A.3 Six Sigma methodology 41 3A.4 The Baldrige model and Six Sigma 42

3A.4.1 Implementing Six Sigma within the Baldrige model 43 3A.5 Integrating Six Sigma with the Baldrige model 44

3A.5.1 The case for Motorola 45 3A.5.2 Leadership and Six Sigma 46 3A.5.3 Human resource management and Six Sigma 46 3A.5.4 Strategie planning and Six Sigma 46

3A.6 Conclusion 47 References 47 Further Readings 48 Appendix 3B: Comparing quality management practices between the United States

and Mexico 48 3B.1 Introduction 48 3B.2 Literature review 49 3B.3 Theoretical framework: Comparative management 50 3B.4 Hypotheses 51 3B.5 Research methodology 51

3B.5.1 Survey Instrument 51 3B.5.2 Data collection 53


Chapter 4 Six Sigma without Lean 57 4.1 Introduction 57

4.1.1 The Six Sigma thinking in this text 57 4.2 Background 58

4.2.1 Which Six Sigma points are retained from TQM? 59 4.2.2 Which Six Sigma point changed from TQM? 59 4.2.3 Six Sigma roots 59

4.2.3.1 From produet quality program to firm-wide decision-making strategy 59

4.3 Corporates support Six Sigma popularity 60 4.3.1 Industries other than manufacturing 60

4.4 Challenges of Six Sigma 61

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4.5 Six Sigma and engineers 62 4.5.1 Six Sigma and Engineering education 62 4.5.2 Controversy between engineers education and green/black belts 62

4.6 The statistics of Six Sigma 63 4.7 The 3.4 defects per million or long-term shift confusion 64 4.8 Methodologies 65

4.8.1 The Juran Six Sigma approach 65 4.8.2 Different methodologies 65 4.8.3 Six Sigma Statistical tools 66

4.9 Conclusion 66 References 66 Further Readings 67

Chapter 5 Lean 71 5.1 Introduction 71 5.2 Lean enterprise 71 5.3 Ohno seven sources of waste 72 5.4 Lean elements of manufacturing 72 5.5 Lean tools 73 5.6 Value stream mapping 73 5.7 Lean success 74 5.8 Conclusion 75


Chapter 6 Lean Six Sigma 79 6.1 Introduction 79

6.1.1 History of Lean Six Sigma 79 6.1.2 What is the real difference? 79


Section II: Deciding on firm qualities and Lean Six Sigma initiatives

Chapter 7 The cost approaches and engineering economics of Six Sigma projects 87 7.1 Introduction 87 7.2 Costapproach 88 7.3 Value approach 88 7.4 Application approach 89 7.5 LSS/Quality decision matrix 91 7.6 Determining economic justification of engineering projects 91 7.7 Previous economic studies 92

7.7.1 Impact of Six Sigma on performance of a Company 92 7.8 Critical factors in Six Sigma Implementation 93 7.9 Methodology 94

7.9.1 Baseline 94 7.9.2 Identifying engineering economics metric 94

Contents ix

7.9.3 Comparison 94 7.9.4 Evaluation 96 7.9.5 Sensitivity 96

7.10 Gase study 96 7.10.1 Sample calculation 96

7.11 Results and discussions 98 7.11.1 Decision comparison based on EBIT growth rate and IRR 98

7.12 Conclusion 98 References 98

Chapter 8 Lean Six Sigma and firm performance: A managerial perspective 101 8.1 Introduction 101 8.2 What is special about Six Sigma? 102 8.3 Process management 103

8.3.1 Understanding organizational processes 104 8.3.2 Process management and firm performance 105 8.3.3 Process management and Innovation 106

8.4 Final notes 108 References 108 Further Readings 110

Chapter 9 Benchmarking high-performing Six Sigma companies 113 9.1 Introduction 113

9.1.1 Lean Six Sigma criteria testing model 113 9.1.1.1 Identification of Six Sigma companies 114

9.2 Lean Six Sigma priority evaluation models 117 9.2.1 Estimation of M ARR 118 9.2.2 Discount for Inflation 118 9.2.3 Calculate performance of each Company 118

9.3 Non-LSS projects in the LSS Organization—How do we manage non-LSS projects? Evaluation and comparison of practices between high- and low-performing companies 119 9.3.1 Study factors critical for Six Sigma Implementation 119 9.3.2 Examine and compare failure factors for companies under our study.... 122 9.3.3 Difference between traditional and high performance Organization.... 125

9.4 Lean Six Sigma/no Lean Six Sigma management Integration strategy 128 References 128 Appendix 9A: Developing an Instrument for measuring Six Sigma implementation 129 9A.1 Introduction 129 9A.2 Background and literature review 130

9A.2.1 Six Sigma methodology 130 9A.2.2 Literature review 130

9A.3 Construct development 131 9A.4 Methodology 132 9A.5 Analysis 132

9A.5.1 Black belt roles 132 9A.5.2 DMAIC versus DMADV 133 9A.5.3 Plan 134

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9A.5.4 Do 134 9A.5.5 Check 135 9A.5.6 Act 136 9A.5.7 Financial responsibility 136 9A.5.8 Executive support 137 9A.5.9 Final reduced questionnaire 137

9A.6 Summary and conclusions 137 9A.6.1 General findings 139 9A.6.2 Limitations 140 9A.6.3 Future research 140 9A.6.4 Implications for managers 140

References 140 Further Readings 141 Appendix 9B: Six Sigma deployment success according to shareholder value 141 9B.1 Introduction 141

9B.1.1 Good to Great 142 9B.1.2 Six Sigma 142 9B.1.3 Lean Six Sigma 143 9B.1.4 Use of Lean Six Sigma for Company growth and compliance 143 9B.1.5 Previous study 144

9B.2 Study methodology 144 9B.2.1 Population sample (representative companies) 144 9B.2.2 Measurement criteria 145 9B.2.3 Criteria for success 147 9B.2.4 Identify characteristics 147

9B.3 Conclusion 147 References 148

Chapter 10 Six Sigma and HR: Getting the right talent and industrial engineers in key Six Sigma roles 149

10.1 Introduction 149 10.2 LSS in education (graduate and undergraduate) 150

10.2.1 Six Sigma and engineers 150 10.2.1.1 Six Sigma and engineering education 150 10.2.1.2 Controversy between engineers education and green/

black belts 150 10.2.2 Aspects of Lean Six Sigma 150 10.2.3 Roles of Lean Six Sigma 151

10.2.3.1 Industrial roles 151 10.2.3.2 Six Sigma-IE interface framework 151

10.3 LSS Integration into the Malcolm Baldrige Award 153 10.3.1 Baldrige model for quality and Six Sigma method 153 10.3.2 Six Sigma within Baldrige model 154 10.3.3 Füll Integration 155 10.3.4 Leadership 155 10.3.5 Human resource/work force management 156 10.3.6 Strategie planning 156

10.4 LSS Integration into ISO 9000 156

Contents xi

10.5 LSS Integration into logistics 156 References 157 Appendix 10A: Quality control measurement of an engineering productivity index 157 10A.1 Introduction 157 10A.2 Background 159 10A.3 Application of quality control principles 160 10A.4 Use of control charts for cognitive turnover 160

10A.4.1 Chart run rules 161 10A.5 Chart development 161 10A.6 Results 162 10A.7 Conclusions 165 References 165 Further Readings 166 Appendix 10B: The value of industrial engineers in Lean Six Sigma organizations 166 10B.1 Introduction 166 10B.2 Background 166 10B.3 Aspects of Lean Six Sigma 167 10B.4 Roles in Lean Six Sigma 167 10B.5 Academic discipline 168

10B.5.1 Aspects of the Lean Six Sigma 168 10B.5.2 Roles in Lean Six Sigma 168

10B.6 Industrial roles 168 10B.7 Six Sigma-IE Interface framework 168 10B.8 Implementation of the framework 170 10B.9 Proposed study 171 10B.10 Conclusion 171 References 172

Section III: The science and engineering of Lean Six Sigma

Chapter 11 LSS process, steps, tools, and statistics 175 11.1 Introduction 176 11.2 Hypothetical statements 178 11.3 Define 179

11.3.1 Chartering a Six Sigma project 179 11.3.2 The assignments of the team 181 11.3.3 Methods to collate Information 182

11.4 Measure 182 11.4.1 Data collection and accuracy 183 11.4.2 Process description 183 11.4.3 Focus/prioritization tools 184 11.4.4 Quantifying and describing Variation 184 11.4.5 Generating and organizing ideas 185

11.5 Analyze 185 11.6 Improve 186 11.7 Control 188

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11.8 DFSS-R introduction 190 11.8.1 Define 190 11.8.2 Measure 190 11.8.3 Analyze 191 11.8.4 Design 191 11.8.5 Identify 191 11.8.6 Optimize 191 11.8.7 Verify 192

References 192

Chapter 12 Fundamental statistics and basic quality tools 193 12.1 Introduction 193 12.2 Basic definitions 193 12.3 Module 1—Empirical methods 194

12.3.1 Frequency distribution 194 12.3.2 Histogram 194 12.3.3 Other graphical methods 198

12.3.3.1 Scatter diagram 198 12.3.3.2 Stem and leaf diagram 199 12.3.3.3 Box and whisker plot 201

12.4 Module 2—Statistical models for describing populations 202 12.4.1 Binomial distribution 202 12.4.2 Poisson distribution 203 12.4.3 Normal distribution 204 12.4.4 Application of central limit theorem 205

12.4.4.1 Central limit theorem 205 12.4.5 Hypothesistesting 205

12.4.5.1 US legal system hypothesis tests 206 12.4.5.2 Why and when are hypothesis tests used? 206 12.4.5.3 Null hypothesis 206 12.4.5.4 Alternate hypothesis 206 12.4.5.5 Translation 207

12.4.6 Regression 208 12.4.6.1 Simple linear regression model 209 12.4.6.2 The method of least squares 209 12.4.6.3 Residuais 210 12.4.6.4 Multiple regression 211

12.4.7 Analysis of variance 212 12.4.7.1 P-value 212 12.4.7.2 Tukey's method 212 12.4.7.3 Fisher's least significant difference 212

12.5 Module 3—Quality tools 212 12.5.1 Flowcharting 212 12.5.2 Cause-and-effect diagram 213 12.5.3 Check sheets 213 12.5.4 Pareto diagrams 214 12.5.5 Control charts 215

12.5.5.1 Variable and attribute process control charts 215

Contents xiii

12.5.5.2 Understanding the process of implementing the chart 215 12.5.5.3 x and R charts 216 12.5.5.4 Median charts 216 12.5.5.5 x and s charts 217 12.5.5.6 Attribute process control charts 218


Chapter 13 Define: Identifying and organizing Six Sigma projects for success 221 13.1 Introduction 222 13.2 Project definition worksheet 224 13.3 Voice of the customer 228

13.3.1 Customer identification 228 13.3.2 Internal customers 229 13.3.3 External customers 232 13.3.4 Customer Service 232 13.3.5 Customer retention and loyalty 232 13.3.6 Customer metrics selection 233 13.3.7 Customer data collection 234 13.3.8 Customer surveys 234 13.3.9 Customer data analysis 235

13.3.9.1 Linegraph 235 13.3.9.2 Control charts 235 13.3.9.3 Matrix diagrams 236

13.3.10 Voice of customers 236 13.3.10.1 Methods of hearing the VOC 236 13.3.10.2 Process to understand VOC 236 13.3.10.3 Critical to quality 237

13.4 Project charter and teams 237 13.4.1 Setting project boundaries 238 13.4.2 Project charter 239

13.4.2.1 Content of the charter 239 13.4.2.2 Financial impact 240

13.4.3 Goal Statement 240 13.4.3.1 Step 1: Identify 240 13.4.3.2 Step 2: Exploit 241 13.4.3.3 Step 3: Subordinate 241 13.4.3.4 Step 4: Elevate 241 13.4.3.5 Step 5: Go back to Step 1 241

13.4.4 Milestones or deliverables 241 13.4.5 Charter negotiation 242 13.4.6 Project management and its benefits 242 13.4.7 Project measures 243 13.4.8 Teams 244

13.4.8.1 Team leader roles and responsibilities 244 13.4.8.2 Team formation and evolution 245 13.4.8.3 Types of teams 246 13.4.8.4 Implementing teams 247

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13.5 Project tracking 250 13.5.1 Work breakdown structure (WBS) 251

13.5.1.1 Advantages of manual methods 252 13.5.1.2 Advantages of Computer Software 252

13.5.2 Milestones reporting 252 13.5.3 Project report 253

13.5.3.1 Document archiving 253 13.6 Yellow belt 253

13.6.1 SMART objective 253 13.6.2 SIPOC 254 13.6.3 Voice of the customer in yellow belt 254

13.6.3.1 Critical to quality 256 13.7 Green belt 257

13.7.1 Pareto diagrams 257 13.7.2 Benchmarking 258 13.7.3 Thought process map 259

13.7.3.1 Value stream mapping 259 13.7.3.2 Process mapping 261

13.7.4 Brainstorming 262 13.8 Black Belt 262

13.8.1 Kano model 262 13.8.1.1 Dissatisfiers (basic requirements) 262 13.8.1.2 Beijing Olympics 262 13.8.1.3 Delighters 262

13.8.2 Quality function deployment 263 13.8.3 Affinity diagram 266 13.8.4 Interrelationship diagram 269

References 270

Chapter 14 Measure: Identifying obtainable data for realistic use 279 14.1 Introduction 280 14.2 Critical characteristics 281

14.2.1 Critical to satisfaction 282 14.2.2 Critical to quality 282 14.2.3 Critical to process 282

14.3 Flow down process 283 14.3.1 Construction of a flow down process 283 14.3.2 Characteristics of good "Little y" 284

14.4 Two dimensions 285 14.5 Determination of targets and specifications 285

14.5.1 The need for targets and specifications 286 14.6 Sponsorship level 287

14.6.1 Balanced scorecard 287 14.7 Yellow belt 287

14.7.1 Process mapping 288 14.7.2 Data collection 290

14.7.2.1 Control charts 291 14.7.2.2 Check sheets 291

Contents xv

14.7.3 Waste and Variation analysis 292 14.7.3.1 First S—Sort (Organization) 292 14.7.3.2 Second S—Stabilize (orderliness) 293 14.7.3.3 Third S—Shine (cleanliness) 293 14.7.3.4 Fourth S—Standardize (promote adherence) 293 14.7.3.5 Fifth S—Sustain (self-discipline) 293 14.7.3.6 Value analysis 293

14.8 Green belt 294 14.8.1 Pareto analysis 294 14.8.2 Data collection 295

14.8.2.1 Measurement scales 295 14.8.2.2 Types of sampling 296 14.8.2.3 Ensuring data accuracy 296

14.8.3 Data collection methods 296 14.8.3.1 Check sheets 297 14.8.3.2 Checklists 298

14.8.4 Types of data 298 14.8.5 Measurement methods 299

14.8.5.1 Measurement system analysis 299 14.8.5.2 Range method 300 14.8.5.3 Analysis of variance 301 14.8.5.4 Measurement correlation 303 14.8.5.5 Enterprise measurement systems 306 14.8.5.6 Calibration 307

14.8.6 Graphical methods 308 14.8.6.1 Boxplots 308 14.8.6.2 Scatter diagrams 308 14.8.6.3 Stem and leaf plots 310 14.8.6.4 Run (TREND) charts 310 14.8.6.5 Histograms 310

14.9 Black belt 311 14.9.1 Control charts 311

14.9.1.1 Understanding the process for implementing the chart 312 14.9.1.2 x and R charts 313 14.9.1.3 Median charts 315 14.9.1.4 x and s charts 315

14.9.2 Attribute process control charts 315 14.9.2.1 P-charts for proportion defective 316 14.9.2.2 np charts 316 14.9.2.3 C and u charts 317

References 317 Further Reading 318

Chapter 15 Analyze: Evaluating data to determine root causes 321 15.1 Introduction 322 15.2 Establishing baseline 322

15.2.1 Baseline performance metrics 324 15.2.1.1 Counting "defects" or "defectives" 324 15.2.1.2 Measuring characteristic or variable 324

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15.2.1.3 Baseline process metrics 324 15.2.2 Discrete Outputs 325

15.2.2.1 Process capability for binomial process Outputs 331 15.2.2.2 Process capability for Poisson process output 331

15.2.3 Continuous Outputs 332 15.2.3.1 Process capability analysis for normal process Outputs 333

15.2.4 Potential process capability 334 15.2.4.1 Short-term Variation 335

15.3 Yellow belt 337 15.3.1 Cause-and-effects diagram (fishbone diagram) 337 15.3.2 Fault tree analysis 338

15.3.2.1 Fault tree symbols 339 15.3.3 Root cause analysis 340

15.3.3.1 Subjective tools 341 15.3.3.2 Analytical tools 341 15.3.3.3 5 Whys 341 15.3.3.4 5 Ws and H 342

15.4 Green belt 342 15.4.1 Entitlement 342

15.4.1.1 Types of errors 342 15.4.2 Hypothesis testing 345

15.4.2.1 US legal system hypothesis tests 345 15.4.2.2 Why and when are hypothesis tests used? 345 15.4.2.3 Null hypothesis 346 15.4.2.4 Alternate hypothesis 346 15.4.2.5 Translation 346

15.4.3 Chi-squared test 349 15.4.4 Analysis of variance 349

15.4.4.1 P-value 349 15.4.4.2 Tukey's method 350 15.4.4.3 Fisher's least significant difference 350

15.4.5 X-Y process map 350 15.4.6 Failure mode and effect analysis 351

15.4.6.1 Failure mode and effect analysis process steps 353 15.4.6.2 Risk assessment and risk priority number 354 15.4.6.3 Types of FMEA 354

15.5 Black belt 356 15.5.1 Multi-vari studies 356

15.5.1.1 Advantages of multi-vari chart 357 15.5.1.2 Characteristics of multi-vari chart 357

15.5.2 Regression 357 15.5.2.1 Fitted line plot 360 15.5.2.2 Residuais 362 15.5.2.3 Multiple regression 362 15.5.2.4 Simple linear regression model 364 15.5.2.5 The method of least squares 365 15.5.2.6 Logistics regression 366

15.5.3 Process capability analysis 368 15.5.3.1 Process capability for normal distribution 369

Contents xvii

15.5.3.2 Process capability indices 370 15.5.3.3 Process performance 370 15.5.3.4 Process performance metrics 371 15.5.3.5 Roiled throughput yield 372 15.5.3.6 Chi-squared analysis of contingency tables 372

References 373

Chapter 16 Improve: Utilizing data to predict Implementation success 375 16.1 Introduction 376 16.2 New process architecture 376 16.3 Green belt 379

16.3.1 Benchmarking 379 16.3.1.1 Purpose of benchmarking 380 16.3.1.2 Types of benchmarking 380 16.3.1.3 Benefits of benchmarking 381 16.3.1.4 Different Standards for comparison 381 16.3.1.5 How is benchmarking done? 381

16.3.2 SWOT analysis 383 16.3.2.1 Strengths and weaknesses 383 16.3.2.2 Opportunities and threats 384

16.3.3 Theory of constraints 385 16.3.3.1 Methods for implementing theory of constraints 386 16.3.3.2 Drum buffer rope 386

16.4 Black belts 387 16.4.1 DOE terminology 387 16.4.2 Design selection guidelines 390 16.4.3 Various examples for performing DOE 391

16.4.3.1 One factor, multiple levels 391 16.4.3.2 Planning experiments 399


Chapter 17 Control: Using data to maintain success 403 17.1 Introduc tion 404 17.2 Validating the plan 405

17.2.1 Purpose 405 17.2.2 Objective 405 17.2.3 Deliverable 405

17.3 Control inputs and monitor Outputs 406 17.3.1 Purpose 406 17.3.2 Objective 406 17.3.3 Deliverable 406

17.4 Controlling x's 407 17.5 Green Belt 408

17.5.1 5S (workplace Organization) 408 17.5.1.1 Details of the 5S program 409

17.6 Kaizen 411 17.6.1 Kaizen blitz 411

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17.7 Total Productive Maintenance 412 17.7.1 Designing for maintainability and availability 413 17.7.2 TPM metrics 414 17.7.3 Benefits of TPM 414 17.7.4 Steps to implement TPM 415 17.7.5 Autonomous TPM small group activities 415

17.8 Black belts 415 17.8.1 Statistical process control 415

17.8.1.1 Selection of variables 416 17.8.1.2 Rational subgrouping 416

17.9 Control chart selection 417 17.9.1 Control chart analysis 417 17.9.2 Trends 418 17.9.3 Jump-in-process level 418 17.9.4 Recurring cycles 419 17.9.5 Points near or outside limits 419 17.9.6 Lack of variability 419

17.10 Poka-yoke (mistake proofing) 420 17.11 Kanban pull 422 References 424

Chapter 18 Lean Integration into DMAIC 425 18.1 Introduction 425 18.2 The marriage of Lean and Six Sigma 426 18.3 Enterprise-wide deployment 426

18.3.1 Challenges with deployment 426 18.4 Systems and processes 427 References 428

Chapter 19 Nontraditional tools for LSS: Work measurement and time studies 429 19.1 Introduction 429 19.2 Motion and time study in a Lean framework 429 19.3 History of time and motion study 430 19.4 Continuous improvement 431

19.4.1 Problem definition 432 19.4.2 Analysis of the problem 432 19.4.3 Search for possible solutions 432 19.4.4 Evaluation of alternative 432 19.4.5 Recommendation for action 432 19.4.6 Continuous monitoring of the action 433

19.5 Time study 433 19.5.1 Time study equipment 433 19.5.2 Important definitions 434 19.5.3 Making the time study 435

19.5.3.1 Recording Information about the Operation and the Operator 435

19.5.3.2 Dividing the operation into its elements 435

Contents xix

19.5.3.3 Recording the time 435 19.5.3.4 Number of cycles to be timed 437 19.5.3.5 Rating an Operator 437 19.5.3.6 Determining the allowances and Standard time 437

19.5.4 Types of time study 438 19.6 Methods-time measurement 438 19.7 Time studies and human factors 439 19.8 Challenges with time study 439 19.9 Economic tools 439 19.10 Evaluating quality costs 441

19.10.1 Cost of good quality 441 19.10.2 Cost of poor quality 441 19.10.3 Total quality costs 442

19.11 Conclusion 442 References 442 Further Readings 443

Chapter 20 DFSS methods and uses for product- and process-oriented research and development 445

20.1 Introduction 445 20.2 Background 445 20.3 Operational Six Sigma and design for Six Sigma 446

20.3.1 DMAIC: OSS 447 20.3.2 Design for Six Sigma 447 20.3.3 Design for Six Sigma research 449

References 451 Further Readings 451 Appendix 20A: Using Design for Six Sigma—To Develop Real-World Testing

Environments for RFID Systems 452 20 A. 1 Introduction 452

20A.1.1 RFID system details 452 20A.1.2 Six Sigma methodology 452

20A.2 3P's theoretical model 453 20A.3 Plan 453

20A.3.1 Define 453 20A.3.2 Measure 454

20A.4 Predict 454 20A.4.1 Analyze 454 20A.4.2 Design 455

20A.5 Perform 455 20A.5.1 Optimize 456

20A.5.1.1 Factors and levels 456 20A.5.2 Verify 457

20A.6 Conclusion 458 Further Readings 460 Appendix 20B: A framework for effective Six Sigma Implementation 460 20B.1 Introduction 460 20B.2 Six Sigma methodology 461

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20B.3 Literature review 462 20B.4 Development of constructs and their relationships 463 20B.5 The conceptual model for Six Sigma Implementation 465 20B.6 Summary 467 References 467

Section IV: Applying and using Lean Six Sigma

Chapter 21 Using Six Sigma to evaluate radio frequency technologies at NASA 471 21.1 Introduction 471 21.2 Methodology: Integrated DFSS for research 471

21.2.1 Plan 471 21.2.1.1 Define 471 21.2.1.2 Measure 472

21.2.2 Predict 472 21.2.2.1 Analyze 472 21.2.2.2 Design 472 21.2.2.3 Identify 472

21.2.3 Perform 472 21.2.3.1 Optimize 472 21.2.3.2 Verify 472

21.3 Define 473 21.3.1 Project charter 473

21.3.1.1 Problem Statement 473 21.3.1.2 Business case 473 21.3.1.3 Scope 473 21.3.1.4 Deliverable 473 21.3.1.5 Test requirements 474 21.3.1.6 Obstacles 474 21.3.1.7 Define acceptable hardware vendors 475 21.3.1.8 Application strategy 475

21.4 Measure 475 21.4.1 Read ränge testing 475

21.4.1.1 Read ränge experiment procedure 475 21.4.2 Orientation sensitivity testing 475

21.4.2.1 Orientation sensitivity experiment procedure 475 21.4.3 Read accuracy testing 476

21.4.3.1 Read accuracy experiment procedure 476 21.5 Analyze 476

21.5.1 Read ränge analysis 476 21.5.2 Orientation sensitivity analysis 477 21.5.3 Read accuracy analysis 477

21.6 Develop 478 21.6.1 Smart shelf 478 21.6.2 Door tracking 478 21.6.3 Waste tracking 478 21.6.4 Sensor active tag 479

Contents xxi

21.7 Optimize 480 21.7.1 Implementation 480 21.7.2 Cost analysis 480

21.7.2.1 Fixedcost 480 21.8 Conclusion 481 References 481

Chapter 22 Using Six Sigma to evaluate automatic Identification technologies to optimize broken case warehousing Operations 483

22.1 Introduction 483 22.1.1 RAID laboratory 483 22.1.2 The National Science Foundation-International Research

Experiences for Students 483 22.2 Background 484

22.2.1 Company background 484 22.2.2 Problem Statement 484

22.3 Research objective 484 22.3.1 Research question 484 22.3.2 Relationship to business problem 484 22.3.3 Research hypothesis 484

22.3.3.1 Test metrics 485 22.3.3.2 Null hypothesis 485 22.3.3.3 The rejection criteria 485

22.4 Research methodology 485 22.4.1 Research methodology 485 22.4.2 Research approach 486 22.4.3 DFSSR—Steps and description 486

22.4.3.1 Scenario 1 489 22.4.3.2 Scenario 2 490 22.4.3.3 Scenario 3 490

22.4.4 Summary 490 22.4.5 Identify 491

22.5 Results 491 22.6 Discussion 491

22.6.1 Rejection of hypothesis 491 22.7 Limitation 492 22.8 Conclusion 492 Further Readings 492

Chapter 23 Using Six Sigma to implement RFID automation at an automotive plant 493

23.1 Research problem and literature search 493 23.2 Research overview and objectives 494 23.3 Research method and approach 495

23.3.1 Measure 497 23.3.2 Design 499 23.3.3 Identify 501

xxii Contents

23.3.4 Results 501 23.3.4.1 Benefit assumptions of using RFID technologies 502 23.3.4.2 Final recommendation 502

23.4 Conclusion 502 23.5 Gantt chart and project timeline 502 Acknowledgment 503 References 503

Chapter 24 Using Six Sigma to evaluate using automated inventory tracking to reduce in processing food product shortages at an international food processing plant 505

24.1 Introduction 505 24.1.1 RAID laboratories 505 24.1.2 The NSF and the IRES 505

24.2 Background 506 24.2.1 Business problem Statement 506

24.3 Research objective 506 24.3.1 Research question 506 24.3.2 Relation to business problem 506 24.3.3 Research hypothesis 507

24.4 Research methodology 507 24.4.1 Research laboratory methodology with steps 507 24.4.2 Data collection techniques 508

24.4.2.1 Tools of DFSS-R 508 24.4.3 Research approach 508

24.4.3.1 DFSS-R steps and description 508 24.5 Results 511

24.5.1 DFSS-R approach 511 24.5.1.1 Define 511 24.5.1.2 Measure 512 24.5.1.3 Analyze 512 24.5.1.4 Design 514 24.5.1.5 Identify 514

24.5.2 Return-on-investment findings 514 24.6 Discussion 515

24.6.1 Rejection of hypothesis 515 24.6.2 Selection of options 515

24.7 Limitations 515 24.8 Conclusion 515 Acknowledgments 516 Further Readings 516

Chapter 25 Using Six Sigma to improve trucking 517 25.1 Introduction 517

25.1.1 Research problem and literature review 517 25.2 Research overview and objectives 518 25.3 Research method and approach 518

25.3.1 Task 1—Flowchart 518 25.3.2 Task 2—Web-based Software Solution 519

Contents xxiii

25.3.3 Task 3—Investigate RFID technologies for automating data capture.. 519 25.3.4 Define 519

25.3.4.1 Define—Results 519 25.3.5 Measure 519 25.3.6 Analyze 519 25.3.7 Design 520

25.3.7.1 Solution 1 520 25.3.7.2 Solution 2 520 25.3.7.3 Results 521

25.3.8 Benefits of RFID 521 25.4 Web order entry 521 25.5 Tracking and tracing 521 25.6 Carrier selection 521 25.7 Information exchange 521 25.8 Mapping 522 25.9 Automated paperless logs 522 25.10 Gantt chart and project timeline 522 25.11 Conclusion 523 Acknowledgments 523 Reference 523 Further Readings 524

Chapter 26 Using Six Sigma logistics to optimize a city's supply chain inventory supplies 525

26.1 Introduction 525 26.2 Background 526 26.3 Capacitated plant location model 527 26.4 Network modeling steps incorporated into a Six Sigma Service project 527

26.4.1 Define 528 26.4.2 Measure 528 26.4.3 Analyze 528 26.4.4 Improve 528 26.4.5 Control 529

26.5 Case description 529 26.5.1 Organizational description 529 26.5.2 Project description 529 26.5.3 Lessens learned 531

26.6 Implications for the technical manager 532 26.7 Conclusions 532 References 533 Further Readings 533

Section V: Nontraditional Lean Six Sigma and modern quality trends

Chapter 27 Lean Six Sigma certification and belt levels 537 27.1 Introduction 537 27.2 Executive level 537

xxiv Contents

27.2.1 Sponsorship Information 537 27.2.2 Belt Information 538

27.2.2.1 Master black belt 538 27.2.2.2 Yellow belt 539 27.2.2.3 Green belt 539 27.2.2.4 Black belt 539

27.3 ASQ certified Six Sigma black belt 539 27.4 HE BB certification 539

27.4.1 Institute of industrial engineers 540 27.5 Summary 542 27.6 Lesson learned 542 27.7 ISCEA LSS pathways to excellence 542

27.7.1 Executive LSS yellow belt—Invitation only 542 27.7.2 Certified LSS yellow belt 543 27.7.3 Certified LSS green belt certification program 543 27.7.4 Certified LSS black belt certification program 543

27.8 Company certifications 543 References 544

Chapter 28 Lean Six Sigma practitioners, Consultants, and vendors 545 28.1 Introduction 545 28.2 Champion 545 28.3 Black belt 545 28.4 Green belt 545 28.5 Current major vendors 546 28.6 Vendor selection model 546 28.7 Consultants and Integrators 547

28.7.1 Master black belt 547 References 547

Chapter 29 Six Sigma project management: What to do after the Six Sigma sponsorship phase 549

29.1 Introduction 550 29.2 Project definition worksheet 551 29.3 Voice of the customer 553

29.3.1 Customer Identification 553 29.3.2 Internal customers 556 29.3.3 External customers 557

29.4 Project charter and teams 559 29.4.1 Setting project boundaries 560 29.4.2 Project charter 561

29.4.2.1 Content of the charter 561 29.4.2.2 Negotiation of the charter 565 29.4.2.3 Project management and its benefits 565 29.4.2.4 Project measures 566

29.4.3 Teams 567 29.4.3.1 Team leader roles and responsibilities 567 29.4.3.2 Team formation and evolution 568 29.4.3.3 Team rules 569

Contents xxv

29.4.3.4 Types of teams 569 29.4.3.5 Implementing teams 570

29.4.4 Meeting management 571 29.4.5 Conflict resolution in teams 572

29.5 Project tracking 573 29.5.1 Work breakdown structure 574 29.5.2 Milestone reporting 575 29.5.3 Project report 576 29.5.4 Document archiving 576


Index 579

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Quality Management for Organization Using Lean … Management for Organization Using Lean Six ... perspective on quality 10 1.4 Total quality management and ... 2 Six Sigma-IE interface