Contents

Cover

Series

Title Page

Copyright

Preface

Preface to the Second Edition

Preface to the First Edition

Part I: Fundamental Quality Improvement and Statistical Concepts

Chapter 1: Introduction

1.1 QUALITY AND PRODUCTIVITY

1.2 QUALITY COSTS (OR DOES IT?)

1.3 THE NEED FOR STATISTICAL METHODS

1.4 EARLY USE OF STATISTICAL METHODS FOR IMPROVING QUALITY

1.5 INFLUENTIAL QUALITY EXPERTS

1.6 SUMMARY

REFERENCES

Chapter 2: Basic Tools for Improving Quality

2.1 HISTOGRAM

2.2 PARETO CHARTS

2.3 SCATTER PLOTS

2.4 CONTROL CHART

2.5 CHECK SHEET

2.6 CAUSE-AND-EFFECT DIAGRAM

2.7 DEFECT CONCENTRATION DIAGRAM

2.8 THE SEVEN NEWER TOOLS

2.9 SOFTWARE

2.10 SUMMARY

REFERENCES

EXERCISES

Chapter 3: Basic Concepts in Statistics and Probability

3.1 PROBABILITY

3.2 SAMPLE VERSUS POPULATION

3.3 LOCATION

3.4 VARIATION

3.5 DISCRETE DISTRIBUTIONS

3.6 CONTINUOUS DISTRIBUTIONS

3.7 CHOICE OF STATISTICAL DISTRIBUTION

3.8 STATISTICAL INFERENCE

3.9 ENUMERATIVE STUDIES VERSUS ANALYTIC STUDIES

REFERENCES

EXERCISES

Part II: Control Charts and Process Capability

Chapter 4: Control Charts for Measurements With Subgrouping (for One Variable)

4.1 BASIC CONTROL CHART PRINCIPLES

4.2 REAL-TIME CONTROL CHARTING VERSUS ANALYSIS OF PAST DATA

4.3 CONTROL CHARTS: WHEN TO USE, WHERE TO USE, HOW MANY TO USE

4.4 BENEFITS FROM THE USE OF CONTROL CHARTS

4.5 RATIONAL SUBGROUPS

4.6 BASIC STATISTICAL ASPECTS OF CONTROL CHARTS

4.7 ILLUSTRATIVE EXAMPLE

4.8 ILLUSTRATIVE EXAMPLE WITH REAL DATA

4.9 DETERMINING THE POINT OF A PARAMETER CHANGE

4.10 ACCEPTANCE SAMPLING AND ACCEPTANCE CONTROL CHART

4.11 MODIFIED LIMITS

4.12 DIFFERENCE CONTROL CHARTS

4.13 OTHER CHARTS

4.14 AVERAGE RUN LENGTH (ARL)

4.15 DETERMINING THE SUBGROUP SIZE

4.16 OUT-OF-CONTROL ACTION PLANS

4.17 ASSUMPTIONS FOR THE CHARTS IN THIS CHAPTER

4.18 MEASUREMENT ERROR

4.19 SOFTWARE

4.20 SUMMARY

APPENDIX

REFERENCES

EXERCISES

Chapter 5: Control Charts for Measurements Without Subgrouping (for One Variable)

5.1 INDIVIDUAL OBSERVATIONS CHART

5.2 TRANSFORM THE DATA OR FIT A DISTRIBUTION?

5.3 MOVING AVERAGE CHART

5.4 CONTROLLING VARIABILITY WITH INDIVIDUAL OBSERVATIONS

5.5 SUMMARY

5.6 APPENDIX

REFERENCES

EXERCISES

Chapter 6: Control Charts for Attributes

6.1 CHARTS FOR NONCONFORMING UNITS

EXAMPLE 6.1

6.2 CHARTS FOR NONCONFORMITIES

EXAMPLE 6.2

6.3 SUMMARY

REFERENCES

EXERCISES

Chapter 7: Process Capability

7.1 DATA ACQUISITION FOR CAPABILITY INDICES

7.2 PROCESS CAPABILITY INDICES

7.3 ESTIMATING THE PARAMETERS IN PROCESS CAPABILITY INDICES

7.4 DISTRIBUTIONAL ASSUMPTION FOR CAPABILITY INDICES

7.5 CONFIDENCE INTERVALS FOR PROCESS CAPABILITY INDICES

7.6 ASYMMETRIC BILATERAL TOLERANCES

7.7 CAPABILITY INDICES THAT ARE A FUNCTION OF PERCENT NONCONFORMING

7.8 MODIFIED k INDEX

7.9 OTHER APPROACHES

7.10 PROCESS CAPABILITY PLOTS

7.11 PROCESS CAPABILITY INDICES VERSUS PROCESS PERFORMANCE INDICES

7.12 PROCESS CAPABILITY INDICES WITH AUTOCORRELATED DATA

7.13 SOFTWARE FOR PROCESS CAPABILITY INDICES

7.14 SUMMARY

REFERENCES

EXERCISES

Chapter 8: Alternatives to Shewhart Charts

8.1 INTRODUCTION

8.2 CUMULATIVE SUM PROCEDURES: PRINCIPLES AND HISTORICAL DEVELOPMENT

8.3 CUSUM PROCEDURES FOR CONTROLLING PROCESS VARIABILITY

8.4 APPLICATIONS OF CUSUM PROCEDURES

8.5 GENERALIZED LIKELIHOOD RATIO CHARTS: COMPETITIVE ALTERNATIVE TO CUSUM CHARTS

8.6 CUSUM PROCEDURES FOR NONCONFORMING UNITS

8.7 CUSUM PROCEDURES FOR NONCONFORMITY DATA

8.8 EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS

8.9 SOFTWARE

8.10 SUMMARY

REFERENCES

EXERCISES

Chapter 9: Multivariate Control Charts for Measurement and Attribute Data

9.1 HOTELLING’S T2 DISTRIBUTION

9.2 A T2 CONTROL CHART

9.3 MULTIVARIATE CHART VERSUS INDIVIDUAL -CHARTS

9.4 CHARTS FOR DETECTING VARIABILITY AND CORRELATION SHIFTS

9.5 CHARTS CONSTRUCTED USING INDIVIDUAL OBSERVATIONS

9.6 WHEN TO USE EACH CHART

9.7 ACTUAL ALPHA LEVELS FOR MULTIPLE POINTS

9.8 REQUISITE ASSUMPTIONS

9.9 EFFECTS OF PARAMETER ESTIMATION ON ARL

9.10 DIMENSION-REDUCTION AND VARIABLE SELECTION TECHNIQUES

9.11 MULTIVARIATE CUSUM CHARTS

9.12 MULTIVARIATE EWMA CHARTS

9.13 EFFECT OF MEASUREMENT ERROR

9.14 APPLICATIONS OF MULTIVARIATE CHARTS

9.15 MULTIVARIATE PROCESS CAPABILITY INDICES

9.16 SUMMARY

APPENDIX

REFERENCES

EXERCISES

Chapter 10: Miscellaneous Control Chart Topics

10.1 PRE-CONTROL

10.2 SHORT-RUN SPC

10.3 CHARTS FOR AUTOCORRELATED DATA

10.4 CHARTS FOR BATCH PROCESSES

10.5 CHARTS FOR MULTIPLE-STREAM PROCESSES

10.6 NONPARAMETRIC CONTROL CHARTS

10.7 BAYESIAN CONTROL CHART METHODS

10.8 CONTROL CHARTS FOR VARIANCE COMPONENTS

10.9 CONTROL CHARTS FOR HIGHLY CENSORED DATA

10.10 NEURAL NETWORKS

10.11 ECONOMIC DESIGN OF CONTROL CHARTS

10.12 CHARTS WITH VARIABLE SAMPLE SIZE AND/OR VARIABLE SAMPLING INTERVAL

10.13 USERS OF CONTROL CHARTS

10.14 SOFTWARE FOR CONTROL CHARTING

BIBLIOGRAPHY

EXERCISES

Part III: Beyond Control Charts: Graphical and Statistical Methods

Chapter 11: Graphical Methods

11.1 HISTOGRAM

11.2 STEM-AND-LEAF DISPLAY

11.3 DOT DIAGRAMS

11.4 BOXPLOT

11.5 NORMAL PROBABILITY PLOT

11.6 PLOTTING THREE VARIABLES

11.7 DISPLAYING MORE THAN THREE VARIABLES

11.8 PLOTS TO AID IN TRANSFORMING DATA

11.9 SUMMARY

REFERENCES

EXERCISES

Chapter 12: Linear Regression

12.1 SIMPLE LINEAR REGRESSION

12.2 WORTH OF THE PREDICTION EQUATION

12.3 ASSUMPTIONS

12.4 CHECKING ASSUMPTIONS THROUGH RESIDUAL PLOTS

12.5 CONFIDENCE INTERVALS AND HYPOTHESIS TEST

12.6 PREDICTION INTERVAL FOR Y

12.7 REGRESSION CONTROL CHART

12.8 CAUSE-SELECTING CONTROL CHARTS

12.9 LINEAR, NONLINEAR, AND NONPARAMETRIC PROFILES

12.10 INVERSE REGRESSION

12.11 MULTIPLE LINEAR REGRESSION

12.12 ISSUES IN MULTIPLE REGRESSION

12.13 SOFTWARE FOR REGRESSION

12.14 SUMMARY

REFERENCES

EXERCISES

Chapter 13: Design of Experiments

13.1 A SIMPLE EXAMPLE OF EXPERIMENTAL DESIGN PRINCIPLES

13.2 PRINCIPLES OF EXPERIMENTAL DESIGN

13.3 STATISTICAL CONCEPTS IN EXPERIMENTAL DESIGN

13.4 t-TESTS

13.5 ANALYSIS OF VARIANCE FOR ONE FACTOR

13.6 REGRESSION ANALYSIS OF DATA FROM DESIGNED EXPERIMENTS

13.7 ANOVA FOR TWO FACTORS

13.8 THE 23 DESIGN

13.9 ASSESSMENT OF EFFECTS WITHOUT A RESIDUAL TERM

13.10 RESIDUAL PLOT

13.11 SEPARATE ANALYSES USING DESIGN UNITS AND UNCODED UNITS

13.12 TWO-LEVEL DESIGNS WITH MORE THAN THREE FACTORS

13.13 THREE-LEVEL FACTORIAL DESIGNS

13.14 MIXED FACTORIALS

13.15 FRACTIONAL FACTORIALS

13.16 OTHER TOPICS IN EXPERIMENTAL DESIGN AND THEIR APPLICATIONS

13.17 SUMMARY

REFERENCES

EXERCISES

Chapter 14: Contributions of Genichi Taguchi and Alternative Approaches

14.1 “TAGUCHI METHODS”

14.2 QUALITY ENGINEERING

14.3 LOSS FUNCTIONS

14.4 DISTRIBUTION NOT CENTERED AT THE TARGET

14.5 LOSS FUNCTIONS AND SPECIFICATION LIMITS

14.6 ASYMMETRIC LOSS FUNCTIONS

14.7 SIGNAL-TO-NOISE RATIOS AND ALTERNATIVES

14.8 EXPERIMENTAL DESIGNS FOR STAGE ONE

14.9 TAGUCHI METHODS OF DESIGN

14.10 DETERMINING OPTIMUM CONDITIONS

14.11 SUMMARY

REFERENCES

EXERCISES

Chapter 15: Evolutionary Operation

15.1 EVOP ILLUSTRATIONS

15.2 THREE VARIABLES

15.3 SIMPLEX EVOP

15.4 OTHER EVOP PROCEDURES

15.5 MISCELLANEOUS USES OF EVOP

15.6 SUMMARY

APPENDIX

EXERCISES

REFERENCES

Chapter 16: Analysis of Means

16.1 ANOM FOR ONE-WAY CLASSIFICATIONS

16.2 ANOM FOR ATTRIBUTE DATA

16.3 ANOM WHEN STANDARDS ARE GIVEN

16.4 ANOM FOR FACTORIAL DESIGNS

16.5 ANOM WHEN AT LEAST ONE FACTOR HAS MORE THAN TWO LEVELS

16.6 USE OF ANOM WITH OTHER DESIGNS

16.7 NONPARAMETRIC ANOM

16.8 SUMMARY

APPENDIX

REFERENCES

EXERCISES

Chapter 17: Using Combinations of Quality Improvement Tools

17.1 CONTROL CHARTS AND DESIGN OF EXPERIMENTS

17.2 CONTROL CHARTS AND CALIBRATION EXPERIMENTS

17.3 SIX SIGMA PROGRAMS

17.4 STATISTICAL PROCESS CONTROL AND ENGINEERING PROCESS CONTROL

REFERENCES

Answers to Selected Exercises

Appendix: Statistical Tables

Author Index

Subject Index