Statistical Process Control - 5th Ed - by John S. Oakland

Statistical Process Control - 5th Ed - by John S. Oakland

Butterworth-Heinemann
An imprint of Elsevier Science
Linacre House, Jordan Hill, Oxford OX2 8DP
200 Wheeler Road, Burlington MA 01803
First published 1986
Reprinted 1986, 1987, 1989
Second edition 1990
Reprinted 1992, 1994, 1995
Third edition 1996
Fourth edition (paperback) 1999
Fifth edition 2003

Contents

Part 1 Process Understanding
1 Quality, processes and control 3
Objectives 3
1.1 The basic concepts 3
1.2 Design, conformance and costs 8
1.3 TQM, processes and the SPC system 14
1.4 Some basic tools 17
Chapter highlights 18
References 20
Discussion questions 21
2 Understanding the process 23
Objectives 23
2.1 Improving customer satisfaction through
process management 23
2.2 Information about the process 26
2.3 Process mapping and flowcharting 29
2.4 Process analysis 35
2.5 Statistical process control and process understanding 37
Chapter highlights 40
References 41
Discussion questions 41
3 Process data collection and presentation 42
Objectives 42
3.1 The systematic approach 42
3.2 Data collection 44
3.3 Bar charts and histograms 46
vi Contents
3.4 Graphs, run charts and other pictures 54
3.5 Conclusions 57
Chapter highlights 57
References 58
Discussion questions 58
Part 2 Process Variability
4 Variation and its management 63
Objectives 63
4.1 The way managers look at data 63
4.2 Interpretation of data 64
4.3 Causes of variation 68
4.4 Accuracy and precision 72
4.5 Variation and management 77
Chapter highlights 80
References 81
Discussion questions 81
5 Variables and process variation 82
Objectives 82
5.1 Measures of accuracy or centring 82
5.2 Measures of precision or spread 85
5.3 The normal distribution 88
5.4 Sampling and averages 89
Chapter highlights 95
References 96
Discussion questions 96
Worked examples using the normal distribution 98
Part 3 Process Control
6 Process control using variables 105
Objectives 105
6.1 Means, ranges and charts 105
6.2 Are we in control? 118
6.3 Do we continue to be in control? 120
6.4 Choice of sample size and frequency, and control limits 123
6.5 Short-, medium- and long-term variation – a change in the
standard practice 126
6.6 Summary of SPC for variables using X and R charts 130
Chapter highlights 131
Contents vii
References 132
Discussion questions 133
Worked examples 141
7 Other types of control charts for variables 153
Objectives 153
7.1 Life beyond the mean and range chart 153
7.2 Charts for individuals or run charts 155
7.3 Median, mid-range and multi-vari charts 161
7.4 Moving mean, moving range, and exponentially weighted
moving average (EWMA) charts 165
7.5 Control charts for standard deviation () 176
7.6 Techniques for short run SPC 182
7.7 Summarizing control charts for variables 184
Chapter highlights 184
References 186
Discussion questions 186
Worked example 193
8 Process control by attributes 195
Objectives 195
8.1 Underlying concepts 195
8.2 np-charts for number of defectives or non-conforming units 198
8.3 p-charts for proportion defective or non-conforming units 206
8.4 c-charts for number of defects/non-conformities 210
8.5 u-charts for number of defects/non-conformities per unit 214
8.6 Attribute data in non-manufacturing 215
Chapter highlights 219
References 220
Discussion questions 221
Worked examples 224
9 Cumulative sum (cusum) charts 227
Objectives 227
9.1 Introduction to cusum charts 227
9.2 Interpretation of simple cusum charts 231
9.3 Product screening and pre-selection 236
9.4 Cusum decision procedures 237
Chapter highlights 242
References 243
Discussion questions 244
Worked examples 251
viii Contents
Part 4 Process Capability
10 Process capability for variables and its measurement 259
Objectives 259
10.1 Will it meet the requirements? 259
10.2 Process capability indices 261
10.3 Interpreting capability indices 266
10.4 The use of control chart and process capability data 267
10.5 A service industry example – process capability analysis
in a bank 270
Chapter highlights 271
References 272
Discussion questions 273
Worked examples 273
Part 5 Process Improvement
11 Process problem solving and improvement 277
Objectives 277
11.1 Introduction 277
11.2 Pareto analysis 280
11.3 Cause and effect analysis 289
11.4 Scatter diagrams 296
11.5 Stratification 298
11.6 Summarizing problem solving and improvement 300
Chapter highlights 301
References 302
Discussion questions 303
Worked examples 307
12 Managing out-of-control processes 315
Objectives 315
12.1 Introduction 315
12.2 Process improvement strategy 316
12.3 Use of control charts for trouble-shooting 318
12.4 Assignable or special causes of variation 329
Chapter highlights 331
References 332
Discussion questions 332
Contents ix
13 Designing the statistical process control system 334
Objectives 334
13.1 SPC and the management system 334
13.2 Teamwork and process control/improvement 338
13.3 Improvements in the process 340
13.4 Taguchi methods 347
13.5 Summarizing improvement 353
Chapter highlights 353
References 354
Discussion questions 355
14 Six-sigma process quality 356
Objectives 356
14.1 Introduction 356
14.2 The six-sigma improvement model 359
14.3 Six-sigma and the role of Design of Experiments 360
14.4 Building a six-sigma organization and culture 364
14.5 Ensuring the financial success of six-sigma projects 366
14.6 Concluding observations and links with Excellence 373
Chapter highlights 375
References 376
Discussion questions 376
15 The implementation of statistical process control 378
Objectives 378
15.1 Introduction 378
15.2 Successful users of SPC and the benefits derived 379
15.3 The implementation of SPC 380
A final comment 384
Chapter highlights 385
Appendices
A The normal distribution and non-normality 386
B Constants used in the design of control charts for mean 396
C Constants used in the design of control charts for range 397
D Constants used in the design of control charts for median
and range 398
E Constants used in the design of control charts for standard
deviation 399
F Cumulative Poisson probability tables 400
G Confidence limits and tests of significance 411
H OC curves and ARL curves for X and R charts 421
I Autocorrelation 426
J Approximations to assist in process control of attributes 428
K Glossary of terms and symbols 433
Index 441