Statistical process control

목차 (Table of Contents)

• CONTENTS
• Preface = xi
• 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 mapping and 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
• 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 $$\bar X$$ and R charts = 130
• Chapter highlights = 131
• References = 132
• Discussion questions = 141
• 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(σ) = 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-dharts 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
• 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
• 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 = 349
• 13.5 Summarizing improvement = 355
• Chapter highlights = 355
• References = 357
• Discussion questions = 357
• 14 The implementation of statistical process control = 358
• Objectives = 358
• 14.1 Introduction = 358
• 14.2 Successful users of SPC and the benefits derived = 359
• 14.3 The implementation of SPC = 360
• A final comment = 364
• Chapter highlights = 365
• Appendices
• A The normal distribution and non-normality = 366
• B Constant used in the design of control charts for mean = 376
• C Constant used in the design of control charts for range = 377
• D Constant used in the design of control charts for median and range = 378
• E Constant used in the design of control charts for standard deviation = 379
• F Cumulative Poisson probability tables = 380
• G Confidence limits and tests of significance = 391
• H OC curves and ARL curves for $$\bar χ$$ and R charts = 401
• I Autocorrelation = 406
• J Approximations to assist in process control of attributes = 408
• K Glossary of terms and symbols = 413
• Index = 421