Preface xix
About the Companion Website xxiii
Part I Philosophy and Fundamentals 1
1 Introduction to Quality Control and the Total Quality System 3
1-1 Introduction and Chapter Objectives 3
1-2 Evolution of Quality Control 4
1-3 Quality 7
1-4 Quality Control 12
1-5 Quality Assurance 13
1-6 Quality Circles and Quality Improvement Teams 14
1-7 Customer Needs and Market Share 15
1-8 Benefits of Quality Control and the Total Quality System 16
1-9 Quality and Reliability 18
1-10 Quality Improvement 18
1-11 Product and Service Costing 19
1-12 Quality Costs 23
1-13 Measuring Quality Costs 27
1-14 Management of Quality 31
1-15 Quality and Productivity 34
1-16 Total Quality Environmental Management 37
Summary 40
Key Terms 41
Exercises 41
References 46
2 Some Philosophies and Their Impact on Quality 47
2-1 Introduction and Chapter Objectives 47
2-2 Service Industries and Their Characteristics 47
2-3 Model for Service Quality 53
2-4 W. Edwards Deming's Philosophy 56
2-5 Philip B. Crosby's Philosophy 75
2-6 Joseph M. Juran's Philosophy 78
2-7 The Three Philosophies Compared 82
Summary 85
Key Terms 85
Exercises 86
References 88
3 Quality Management: Practices, Tools, and Standards 89
3-1 Introduction and Chapter Objectives 89
3-2 Management Practices 90
3-3 Quality Function Deployment 99
3-4 Benchmarking and Performance Evaluation 106
3-5 Health Care Analytics 115
3-6 Tools for Continuous Quality Improvement 124
3-7 International Standards ISO 9000 and Other Derivatives 137
Part II Statistical Foundations and Methods of Quality Improvement 147
4 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement 149
4-1 Introduction and Chapter Objectives 150
4-2 Population and Sample 150
4-3 Parameter and Statistic 150
4-4 Probability 151
4-5 Descriptive Statistics: Describing Product or Process Characteristics 156
4-6 Probability Distributions 173
4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality 189
Summary 212
Appendix: Approximations to Some Probability Distributions 212
Key Terms 215
Exercises 216
References 228
5 Data Analyses and Sampling 229
5-1 Introduction and Chapter Objectives 229
5-2 Empirical Distribution Plots 230
5-3 Randomness of a Sequence 235
5-4 Validating Distributional Assumptions 237
5-5 Transformations to Achieve Normality 240
5-6 Analysis of Count Data 244
5-7 Analysis of Customer Satisfaction Data 248
5-8 Concepts in Sampling 257
Summary 264
Key Terms 265
Exercises 266
References 272
Part III Statistical Process Control 273
6 Statistical Process Control Using Control Charts 275
6-1 Introduction and Chapter Objectives 275
6-2 Causes of Variation 277
6-3 Statistical Basis for Control Charts 277
6-4 Selection of Rational Samples 289
6-5 Analysis of Patterns in Control Charts 290
6-6 Maintenance of Control Charts 294
Summary 295
Key Terms 295
Exercises 295
References 298
7 Control Charts for Variables 299
7-1 Introduction and Chapter Objectives 300
7-2 Selection of Characteristics for Investigation 301
7-3 Preliminary Decisions 302
7-4 Control Charts for the Mean and Range 303
7-5 Control Charts for the Mean and Standard Deviation 321
7-6 Control Charts for Individual Units 326
7-7 Control Charts for Short Production Runs 330
7-8 Other Control Charts 332
7-9 Risk-Adjusted Control Charts 352
7-10 Multivariate Control Charts 359
Summary 372
Key Terms 373
Exercises 374
References 387
8 Control Charts for Attributes 389
8-1 Introduction and Chapter Objectives 390
8-2 Advantages and Disadvantages of Attribute Charts 390
8-3 Preliminary Decisions 392
8-4 Chart for Proportion Nonconforming: p-Chart 392
8-5 Chart for Number of Nonconforming Items: np-Chart 409
8-6 Chart for Number of Nonconformities: c-Chart 411
8-7 Chart for Number of Nonconformities Per Unit: u-Chart 417
8-8 Chart for Demerits Per Unit: u-Chart 423
8-9 Charts for Highly Conforming Processes 426
8-10 Operating Characteristic Curves for Attribute Control Charts 431
Summary 434
Key Terms 435
Exercises 435
References 448
9 Process Capability Analysis 449
9-1 Introduction and Chapter Objectives 449
9-2 Specification Limits and Control Limits 450
9-3 Process Capability Analysis 451
9-4 Natural Tolerance Limits 453
9-5 Specifications and Process Capability 454
9-6 Process Capability Indices 457
9-7 Process Capability Analysis Procedures 476
9-8 Capability Analysis for Nonnormal Distributions 478
9-9 Setting Tolerances on Assemblies and Components 480
9-10 Estimating Statistical Tolerance Limits of a Process 487
Summary 489
Key Terms 490
Exercises 490
References 499
Part IV Acceptance Sampling 501
10 Acceptance Sampling Plans for Attributes and Variables 503
10-1 Introduction and Chapter Objectives 504
10-2 Advantages and Disadvantages of Sampling 504
10-3 Producer and Consumer Risks 505
10-4 Operating Characteristic Curve 505
10-5 Types of Sampling Plans 509
10-6 Evaluating Sampling Plans 511
10-7 Bayes Rule and Decision Making Based on Samples 516
10-8 Lot-by-Lot Attribute Sampling Plans 519
10-9 Other Attribute Sampling Plans 537
10-10 Deming's kp Rule 540
10-11 Sampling Plans for Variables 543
10-12 Variable Sampling Plans for a Process Parameter 544
10-13 Variable Sampling Plans for Estimating the Lot Proportion Nonconforming 550
Summary 555
Key Terms 556
Exercises 556
References 562
Part V Product and Process Design 563
11 Reliability 565
11-1 Introduction and Chapter Objectives 565
11-2 Reliability 566
11-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability 566
11-4 System Reliability 570
11-5 Operating Characteristic Curves 578
11-6 Reliability and Life Testing Plans 580
11-7 Survival Analysis 588
Summary 599
Key Terms 599
Exercises 600
References 603
12 Experimental Design and the Taguchi Method 605
12-1 Introduction and Chapter Objectives 606
12-2 Experimental Design Fundamentals 606
12-3 Some Experimental Designs 611
12-4 Factorial Experiments 631
12-5 The Taguchi Method 659
12-6 The Taguchi Philosophy 660
12-7 Loss Functions 663
12-8 Signal-to-Noise Ratio and Performance Measures 670
12-9 Critique of S/N Ratios 673
12-10 Experimental Design in the Taguchi Method 674
12-11 Parameter Design in the Taguchi Method 690
12-12 Critique of Experimental Design and the Taguchi Method 694
Summary 696
Key Terms 697
Exercises 698
References 708
13 Process Modeling Through Regression Analysis 711
13-1 Introduction and Chapter Objectives 711
13-2 Deterministic and Probabilistic Models 712
13-3 Model Assumptions 714
13-4 Least Squares Method for Parameter Estimation 716
13-5 Model Validation and Remedial Measures 722
13-6 Estimation and Inferences from a Regression Model 726
13-7 Qualitative Independent Variables 732
13-9 Logistic Regression 742
Summary 746
Key Terms 747
Exercises 748
References 752
Appendixes 753
A-1 Cumulative Binomial Distribution 753
A-2 Cumulative Poisson Distribution 758
A-3 Cumulative Standard Normal Distribution 760
A-4 Values of t for a Specified Right-Tail Area 763
A-5 Chi-Squared Values for a Specified Right-Tail Area 765
A-6 Values of F for a Specified Right-Tail Area 767
A-7 Factors for Computing Centerline and Three-Sigma Control Limits 773
A-8 Uniform Random Numbers 774
Index 775
