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Table of Contents Dedication Figures Tables Acknowledgments Common abbreviations used in six sigma Preface Introduction Chapter 1 - Overview of six sigma References Selected bibliography Chapter 2 - Customer satisfaction Chapter 3 - The DMAIC Model Define Measure Analyze Improve Control Selected bibliography Chapter 4 - Common methodologies (tools) used in the DMAIC model benchmarking Benchmarking types Benchmarking model Benchmarking project partners Statistical process control (SPC) Process control versus product control SPC strategy Example Frequency distribution - grouped data Frequency histogram Interpretation How should one assess process behavior? Behavior of the process - process control charts Process variation Steps and phases of implementation Initiating control charts - variable data (pursuit of common cause characterization) Key elements of the strategy of SPC Management responsibilities Statistics used in control charting How do you compute an average? Control limits for X and R charts Control limits for p charts General formulae Formulae for calculating control chart limits X-bar and R chart Individual (X) and moving range chart X-bar and s chart Median chart p-chart np-chart Standardized-value p-chart c-chart u-chart Capability Process capability Capability ratio Capability index Target ratio percent Control chart construction guide - variable data Control chart construction guide - attribute data Testing for normality and exponentiality Measurement system analysis (MSA) Measurement Poka-yoke - mistake-proofing What is poka-yoke? The need for poka-yoke What is the current use of poka-yoke? Error proofing benefits Definitions Generic 5-step process for a poka-yoke Generic mistake proofing implementation process Examples of poka-yoke elements Lean manufacturing process Failure mode and effect analysis (FMEA) Why do we do FMEAs? Vocabulary of FMEA Relationship between FMEA and other tools Fault tree analysis (FTA) Failure mode analysis (FMA) Failure mode and critical analysis (FMCA) Block diagrams and process flow diagrams Design of experiments (DOE) Control plan Mechanics of FMEA Forms Guidelines Risk priority number (RPN) Recommended action The "process" of doing an FMEA Conclusion Project management Why project management principles are essential to six sigma methodology Factors leading to project failure Factors determining the success of a project Cost of quality Avoidance costs Total failure costs Teams Team structure Effective team building Conflict resolution Managing conflicts Win/lose Negotiating Problem-solving Statistics Tools References Selected bibliography Chapter 5 - Design for six sigma Overview Define Characterize Optimize Verify Special comments on the verify stage: Tool requirements Security What's in it for me? Defining program requirements Classification and categories of requirements New requirement - mandatory items of concern Modifying requirements Adding requirements Deleting requirements Releasing requirements Cascading requirements Requirement reports Minimum feature configurations Creating a minimum feature configuration Entering target values Reviewing the application process Typical tools used Deliverables Selected bibliography Chapter 6 - Common methodologies and tools used in the DCOV model Methodologies Systems thinking Advanced product quality planning (APQP) When do we use AQP? What is the difference between AQP and APQP? How do we make AQP work Are there pitfalls in planning Do we really need another qualitative tool to gage quality? How do we use the qualitative methodology in an advanced quality planning setting APQP Initiative and relationship to DFSS Production part approval process (PPAP) What's in the "basic requirements -packet?" Kano model Ideation Quality function deployment (QFD) Stage 1: Establish targets. Stage 2: Finalize design timetables and prototype plans. Stage 3: Establish conditions of production. Stage 4: Mass production start-up. Statistics/modeling/simulation Reliability Robustness and reliability I. Program input II. Design architecture III. Product/process design IV. Design/manufacturing confirmation V. Launch/mass production confirmation VI. For all activities Maintainability (M) Supportability Serviceability Maintenance Maintenance level Maintenance concept Maintenance plan System effectiveness Life cycle cost (LCC) Cost-effectiveness (CE) Reliability factors The reliability function Function structures Axiomatic designs Statistical tolerancing Developing model for tolerancing Survey Types of surveys The methodology for a valid survey Audit Tools References Chapter 7 - Roles and responsibilities Executives Champions Master Black _ - Black is part of the name@@This does not belong here@@ - belt (Shogun) Black belt Green belt Chapter 8 - Six sigma applied in non-manufacturing Chapter 9 - Training and certification Certification General comments on certification as it relates to six sigma Conclusion References Chapter 10 - Implementing six sigma The role of the consultant Epilogue Appendices Appendix A - Core competencies for six sigma methodology Customer focus Business metrics Six sigma fundamentals Appendix B - Traditional sigma (abridged) conversion table Appendix C - The process of QFD Phase 1 / Innovation targets Phase 2 / Generate innovation ideas Phase 3 / Innovation engineering Phase 4 / Manufacturing controls Appendix D - Example of using the quality charts in the QFD process for each of the stages Design Stage 1 / Advanced engineering Phase 1 / Innovation targets for systems Phase 2 / Innovation ideas for systems Phase 3 / Innovation engineering for systems Stage 2 Project definition (QFD and new product development) Phase 1 / Innovation targets for subsystems Phase 2 / Innovation ideas for subsystems Phase 3 / Innovation engineering for subsystems Stage 3 Detailed design (QFD and new product development) Phase 1 / Innovation targets for parts and components Phase 2 / Innovation ideas for parts and components Phase 3 / Innovation engineering for parts and components Phase 4 / Manufacturing controls for parts and components Stage 4 Prototype/test (QFD and new product development) Revise manufacturing controls Appendix E - Using binomial and Poisson / Binomial distribution Poisson distribution Conclusion Appendix F - Development flow for an automotive organization. Enter points for six sigma applications Appendix G - Risk assessment for black belts' training Glossary Selected bibliography About the author Figures Figure 2.1 Links of metrics and goals Figure 4.1 A typical process Figure 4.2 The classical control cycle: a) product control; b) process control; c) combination of product and process control Figure 4.3 A typical control chart Figure 4.4 Control chart selection matrix Figure 4.5 Process versus product control improvement Figure 4.6 Levels of involvement Figure 6.1 The traditional approach of QFD Figure 6.2 The generic approach of QFD with the adaptation of individual matrices. Figure 6.3 The flow of a typical robustness approach to reduce complexity Figure 6.4 A typical process audit Figure 9.1 Sample training program for green belts Figure 9.2 Sample training program for black belts Figure C.1 Phase 1 / Innovation targets for "a pencil" example Figure C.2 Generate innovation ideas for "a pencil example" Figure C.3 Innovation engineering for "a pencil example" Figure C.4 Manufacturing controls for "a pencil example" Figure D.1 K-J and tree 2 levels Figure D.2 Cost/benefit analysis Figure D.3 Dendogra Tables Table 3.1 Typical tools/methodologies and deliverables for the DMAIC model Table 4.1 Deliverables of the five phase benchmarking model Table 4.2 Major differences between product and process control Table 4.3 Guide for determining the number of class intervalsTable 4.4 Typical characteristics of variation Table 4.5 A guide for constructing variable control charts Table 4.6 A guide for constructing attribute control charts Table 4.7 A guide for testing normality and exponentiality Table 4.8 Generic five steps for poka-yoke Table 4.9 Generic mistake proofing implementation process Table 4.10 A typical cost of quality report Table 4.11 Typical tools used in the six sigma DMAIC model Table 5.1 Typical tools/methodologies and deliverables for the DCOV model Table 6.1. The flow of the matrices Table 6.2 An alternate sequence of the quality charts Table 6.3 A typical project status values Table 6.4 Typical tools used in implementing DFSS Table 7.1 Different "role" names used in the six sigma methodology Table 8.1 Comparison between PSM, DMAIC and DCOV models Table 8.2 Summary of six sigma and EMS combined stages Table B.1 Traditional sigma (abridged) conversion table Table E.1 Poisson probability distribution Table E.2 Binomial probability distribution
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