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Fundamentals of Quality Control and Improvement
Amitava Mitra (Author)
9781118705148, Wiley
Hardback, published 21 June 2016
816 pages
25.9 x 18.5 x 4.8 cm, 1.565 kg
A statistical approach to the principles of quality control and management Incorporating modern ideas, methods, and philosophies of quality management, Fundamentals of Quality Control and Improvement, Fourth Edition presents a quantitative approach to management-oriented techniques and enforces the integration of statistical concepts into quality assurance methods. Utilizing a sound theoretical foundation and illustrating procedural techniques through real-world examples, the timely new edition bridges the gap between statistical quality control and quality management. Promoting a unique approach, the book focuses on the use of experimental design concepts as well as the Taguchi method for creating product/process designs that successfully incorporate customer needs, improve lead time, and reduce costs. The Fourth Edition of Fundamentals of Quality Control and Improvement also includes: Fundamentals of Quality Control and Improvement, Fourth Edition is an ideal book for undergraduate and graduate-level courses in management, technology, and engineering. The book also serves as a valuable reference for practitioners and professionals interested in expanding their knowledge of statistical quality control, quality assurance, product/process design, total quality management, and/or Six Sigma training in quality improvement.
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
Subject Areas: Mathematics [PB]
