Statistical Models and Control Charts for High-Quality Processes - Min Xie

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Statistical Models and Control Charts for High-Quality Processes

By: Min Xie, Thong Ngee Goh, Vellaisamy Kuralmani

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Hardcover | 30 June 2002

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Hardcover
300 Pages

Dimensions(cm)
23.5 x 15.88 x 2.54

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Control charts are widely used in industry to monitor processes that are far from Zero-Defect (ZD), and their use in a near Zero-Defect manufacturing environment poses many problems. This book presents techniques of using control charts for high-quality processes, and some recent findings and applications of statistical control chart techniques for ZD processes are presented.

A powerful technique based on counting of the cumulative conforming (CCC) items between two nonconforming ones is discussed in detail. Extensions of the CCC chart are described, as well as applications of cumulative sum and exponentially weighted moving average techniques to CCC-related data, multivariate methods, economic design of control chart procedures, and modeling and analysis of trended but regularly adjusted processes.

Many examples, charts, and procedures, are presented throughout the book, and references are provided for those interested in exploring the details. A number of questions and issues are posed for further investigations. Researchers and students may find many ideas in this book useful in their academic work, as a foundation is laid for the exploration of many further theoretical and practical issues.

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Preface	p. xi
Acknowledgements	p. xv
Introduction	p. 1
Basics of statistical process control	p. 2
Inadequacies of traditional attribute charts	p. 9
Need for quality improvement	p. 14
Common probability distributions in SPC	p. 17
Control Charts with Probability Limits	p. 21
Use of probability limits	p. 21
Setting up a control chart based on probability limits	p. 24
Probability limits for improvement detection	p. 32
Limitations with probability limits	p. 36
Cumulative Count of Conforming (CCC) chart	p. 39
The basic idea	p. 39
Setting up the CCC chart	p. 41
Decision-making related to CCC chart	p. 42
CCC chart for grouped measurement	p. 50
Some comparisons with 3-sigma limits	p. 58
Cumulative quantity control (CQC) chart	p. 63
Process Improvement Detection	p. 67
Potential for process improvement	p. 67
Using CCC chart for process improvement	p. 73
Modified Implementation of Geometric Chart	p. 77
Optimum limits for maximum average run length	p. 78
Chart based on transformations	p. 84
A conditional decision procedure	p. 93
Effects of inspection errors	p. 100
Effects of estimated control limits	p. 106
Some Extensions to the Geometric Model	p. 111
Negative binomial control chart	p. 112
Modified Poisson model	p. 118
A Markov model for dependent counts	p. 130
A model for correlated attribute processes	p. 136
Some issues for further research	p. 142
CUSUM and EWMA Procedures	p. 145
General CUSUM procedure	p. 146
CUSUM with CCC data	p. 155
Basics of EWMA charts	p. 166
EWMA with CCC data	p. 170
Monitoring of Multiple Process Characteristics	p. 177
Need and approaches for multiple characteristics	p. 178
Multivariate np (Mnp) by weighted average	p. 181
A chart with multinomial distribution	p. 191
Some issues for further research	p. 203
Economic Design of Geometric Chart	p. 205
The Lorenzen and Vance model for economic design	p. 206
Economic design of CCC chart	p. 208
Economic-statistical design of CCC chart	p. 220
Some further extensions	p. 225
Monitoring and Adjustment of Trended Processes	p. 237
Adjustment for process improvement	p. 238
Interpretation of traditional Shewhart chart	p. 240
Modification of process capability indices	p. 248
Cost consideration and decision making	p. 254
References	p. 263
Subject Index	p. 275
Table of Contents provided by Syndetics. All Rights Reserved.

Statistical Models and Control Charts for High-Quality Processes

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Hardcover

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