Statistical Process Control

by Oakland, John S.; Followell, Roy F.

Edition: 2nd

ISBN13: 9780434914845

ISBN10: 0434914843

Format: Hardcover

Pub. Date: 1990-06-01

Publisher(s): Butterworth-Heinemann

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Summary

The book features user-friendly presentation and reflects the latest thinking in the field. It will serve as a textbook for self or group instruction for both student and practicing engineers, scientists, technologists and managers and will prove invaluable to all.
Statistical process control is a tool, which enables both manufacturers and suppliers to achieve control of product quality by means of the application of statistical methods in the controlling process. This book gives the foundations of good quality management and process control, including an explanation of what quality is, and control of conformance and consistency during production. The text offers clear guidance and help to those unfamiliar with either quality control or statistical applications and coves all the necessary theory and techniques in a practical and non-mathematical manner. This book will be essential reading for anyone wishing to understand or implement modern statistical process control techniques.

Author Biography

John Oakland is the Executive Chairman of Oakland Consulting plc and Professor of Business Excellence and Quality Management at the University of Leeds Business School

Preface	p. xi
Process Understanding
Quality, processes and control	p. 3
Objectives	p. 3
The basic concepts	p. 3
Design, conformance and costs	p. 8
TQM, processes and the SPC system	p. 14
Some basic tools	p. 17
Chapter highlights	p. 18
References	p. 20
Discussion questions	p. 21
Understanding the process	p. 23
Objectives	p. 23
Improving customer satisfaction through process management	p. 23
Information about the process	p. 26
Process mapping and flowcharting	p. 29
Process analysis	p. 35
Statistical process control and process understanding	p. 37
Chapter highlights	p. 40
References	p. 41
Discussion questions	p. 41
Process data collection and presentation	p. 42
Objectives	p. 42
The systematic approach	p. 42
Data collection	p. 44
Bar charts and histograms	p. 46
Graphs, run charts and other pictures	p. 54
Conclusions	p. 57
Chapter highlights	p. 57
References	p. 58
Discussion questions	p. 58
Process Variability
Variation and its management	p. 63
Objectives	p. 63
The way managers look at data	p. 63
Interpretation of data	p. 64
Causes of variation	p. 68
Accuracy and precision	p. 72
Variation and management	p. 77
Chapter highlights	p. 80
References	p. 81
Discussion questions	p. 81
Variables and process variation	p. 82
Objectives	p. 82
Measures of accuracy or centring	p. 82
Measures of precision or spread	p. 85
The normal distribution	p. 88
Sampling and averages	p. 89
Chapter highlights	p. 95
References	p. 96
Discussion questions	p. 96
Worked examples using the normal distribution	p. 98
Process Control
Process control using variables	p. 105
Objectives	p. 105
Means, ranges and charts	p. 105
Are we in control?	p. 118
Do we continue to be in control?	p. 120
Choice of sample size and frequency, and control limits	p. 123
Short-, medium- and long-term variation--a change in the standard practice	p. 126
Summary of SPC for variables using X and R charts	p. 130
Chapter highlights	p. 131
References	p. 132
Discussion questions	p. 133
Worked examples	p. 141
Other types of control charts for variables	p. 153
Objectives	p. 153
Life beyond the mean and range chart	p. 153
Charts for individuals or run charts	p. 155
Median, mid-range and multi-vari charts	p. 161
Moving mean, moving range, and exponentially weighted moving average (EWMA) charts	p. 165
Control charts for standard deviation ([sigma])	p. 176
Techniques for short run SPC	p. 182
Summarizing control charts for variables	p. 184
Chapter highlights	p. 184
References	p. 186
Discussion questions	p. 186
Worked example	p. 193
Process control by attributes	p. 195
Objectives	p. 195
Underlying concepts	p. 195
np-charts for number of defectives or non-conforming units	p. 198
p-charts for proportion defective or non-conforming units	p. 206
c-charts for number of defects/non-conformities	p. 210
u-charts for number of defects/non-conformities per unit	p. 214
Attribute data in non-manufacturing	p. 215
Chapter highlights	p. 219
References	p. 220
Discussion questions	p. 221
Worked examples	p. 224
Cumulative sum (cusum) charts	p. 227
Objectives	p. 227
Introduction to cusum charts	p. 227
Interpretation of simple cusum charts	p. 231
Product screening and pre-selection	p. 236
Cusum decision procedures	p. 237
Chapter highlights	p. 242
References	p. 243
Discussion questions	p. 244
Worked examples	p. 251
Process Capability
Process capability for variables and its measurement	p. 259
Objectives	p. 259
Will it meet the requirements?	p. 259
Process capability indices	p. 261
Interpreting capability indices	p. 266
The use of control chart and process capability data	p. 267
A service industry example--process capability analysis in a bank	p. 270
Chapter highlights	p. 271
References	p. 272
Discussion questions	p. 273
Worked examples	p. 273
Process Improvement
Process problem solving and improvement	p. 277
Objectives	p. 277
Introduction	p. 277
Pareto analysis	p. 280
Cause and effect analysis	p. 289
Scatter diagrams	p. 296
Stratification	p. 298
Summarizing problem solving and improvement	p. 300
Chapter highlights	p. 301
References	p. 302
Discussion questions	p. 303
Worked examples	p. 307
Managing out-of-control processes	p. 315
Objectives	p. 315
Introduction	p. 315
Process improvement strategy	p. 316
Use of control charts for trouble-shooting	p. 318
Assignable or special causes of variation	p. 329
Chapter highlights	p. 331
References	p. 332
Discussion questions	p. 332
Designing the statistical process control system	p. 334
Objectives	p. 334
SPC and the management system	p. 334
Teamwork and process control/improvement	p. 338
Improvements in the process	p. 340
Taguchi methods	p. 347
Summarizing improvement	p. 353
Chapter highlights	p. 353
References	p. 354
Discussion questions	p. 355
Six-sigma process quality	p. 356
Objectives	p. 356
Introduction	p. 356
The six-sigma improvement model	p. 359
Six-sigma and the role of Design of Experiments	p. 360
Building a six-sigma organization and culture	p. 364
Ensuring the financial success of six-sigma projects	p. 366
Concluding observations and links with Excellence	p. 373
Chapter highlights	p. 375
References	p. 376
Discussion questions	p. 376
The implementation of statistical process control	p. 378
Objectives	p. 378
Introduction	p. 378
Successful users of SPC and the benefits derived	p. 379
The implementation of SPC	p. 380
A final comment	p. 384
Chapter highlights	p. 385
Appendices
The normal distribution and non-normality	p. 386
Constants used in the design of control charts for mean	p. 396
Constants used in the design of control charts for range	p. 397
Constants used in the design of control charts for median and range	p. 398
Constants used in the design of control charts for standard deviation	p. 399
Cumulative Poisson probability tables	p. 400
Confidence limits and tests of significance	p. 411
OC curves and ARL curves for X and R charts	p. 421
Autocorrelation	p. 426
Approximations to assist in process control of attributes	p. 428
Glossary of terms and symbols	p. 433
Index	p. 441
Table of Contents provided by Rittenhouse. All Rights Reserved.