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Fundamentals of Quality Control and Improvement. 3rd Edition

  • ID: 2173786
  • August 2008
  • 722 Pages
  • John Wiley and Sons Ltd
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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, Third 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, this timely new edition bridges the gap between statistical quality control and quality management.

The book promotes a unique "do it right the first time" approach and 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. Further management–oriented topics of discussion include total quality management; quality function deployment; activity–basedcosting; balanced scorecard; benchmarking; failure mode and effects criticality analysis; quality auditing; vendor selection and certification; and the Six Sigma quality philosophy.

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PREFACE xix

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, 11

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, 17

1–10 Quality Improvement, 18

1–11 Product and Service Costing, 19

1–12 Quality Costs, 22

1–13 Measuring Quality Costs, 26

1–14 Management of Quality, 30

1–15 Quality and Productivity, 33

1–16 Total Quality Environmental Management, 36

1–17 Profile of a Company: The Bama Companies, Inc., 37

2 Some Philosophies and Their Impact on Quality 47

2–1 Introduction and Chapter Objectives, 47

2–2 Service Industries and Their Characteristics, 48

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

3 Quality Management: Practices, Tools, and Standards 93

3–1 Introduction and Chapter Objectives, 93

3–2 Management Practices, 94

3–3 Quality Function Deployment, 103

3–4 Benchmarking and Performance Evaluation, 110

3–5 Tools for Continuous Quality Improvement, 120

3–6 International Standards ISO 9000 and

3–7 Malcolm Baldrige National Quality Award, 135

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, 149

4–2 Population and Sample, 150

4–3 Parameter and Statistic, 150

4–4 Probability, 150

4–5 Descriptive Statistics: Describing Product or Process Characteristics, 156

4–6 Probability Distributions, 173

4–7 Inferential Statistics: Drawing Conclusions on

5 Data Analyses and Sampling 229

5–1 Introduction and Chapter Objectives, 229

5–2 Empirical Distribution Plots, 229

5–3 Randomness of a Sequence, 234

5–4 Validating Distributional Assumptions, 236

5–5 Transformations to Achieve Normality, 239

5–6 Analysis of Count Data, 244

5–7 Concepts in Sampling, 247

PART III STATISTICAL PROCESS CONTROL 263

6 Statistical Process Control Using Control Charts 265

6–1 Introduction and Chapter Objectives, 265

6–2 Causes of Variation, 267

6–3 Statistical Basis for Control Charts, 267

6–4 Selection of Rational Samples, 279

6–5 Analysis of Patterns in Control Charts, 280

6–6 Maintenance of Control Charts, 284

7 Control Charts for Variables 289

7–1 Introduction and Chapter Objectives, 289

7–2 Selection of Characteristics for Investigation, 290

7–3 Preliminary Decisions, 292

7–4 Control Charts for the Mean and Range, 293

7–5 Control Charts for the Mean and Standard Deviation, 310

7–6 Control Charts for Individual Units, 315

7–7 Control Charts for Short Production Runs, 318

7–8 Other Control Charts, 321

7–9 Multivariate Control Charts, 343

8 Control Charts for Attributes 369

8–1 Introduction and Chapter Objectives, 369

8–2 Advantages and Disadvantages of Attribute Charts, 370

8–3 Preliminary Decisions, 371

8–4 Chart for Proportion Nonconforming: p–Chart, 372

8–5 Chart for Number of Nonconforming Items: np–Chart, 384

8–6 Chart for the Number of Nonconformities: c–Chart, 387

8–7 Chart for Number of Nonconformities Per Unit: u–Chart, 390

8–8 Chart for Demerits Per Unit: U–Chart, 393

8–9 Charts for Highly Conforming Processes, 396

8–10 Operating Characteristic Curves for Attribute Control Charts, 400

9 Process Capability Analysis 415

9–1 Introduction and Chapter Objectives, 415

9–2 Specification Limits and Control Limits, 416

9–3 Process Capability Analysis, 417

9–4 Natural Tolerance Limits, 419

9–5 Specifications and Process Capability, 420

9–6 Process Capability Indices, 423

9–7 Process Capability Analysis Procedures, 441

9–8 Capability Analysis for Nonnormal Distributions, 443

9–9 Setting Tolerances on Assemblies and Components, 445

9–10 Estimating Statistical Tolerance Limits of a Process, 453

PART IV ACCEPTANCE SAMPLING 465

10 Acceptance Sampling Plans for Attributes and Variables 467

10–1 Introduction and Chapter Objectives, 467

10–2 Advantages and Disadvantages of Sampling, 468

10–3 Producer and Consumer Risks, 468

10–4 Operating Characteristic Curve, 469

10–5 Types of Sampling Plans, 473

10–6 Evaluating Sampling Plans, 475

10–7 Bayes Rule and Decision Making Based on Samples, 480

10–8 Lot–by–Lot Attribute Sampling Plans, 483

10–9 Other Attribute Sampling Plans, 501

10–10 Deming s kp Rule, 504

10–11 Sampling Plans for Variables, 507

10–12 Variable Sampling Plans for a Process Parameter, 508

10–13 Variable Sampling Plans for Estimating the Lot Proportion

PART V PRODUCT AND PROCESS DESIGN 527

11 Reliability 529

11–1 Introduction and Chapter Objectives, 529

11–2 Reliability, 529

11–3 Life–Cycle Curve and Probability Distributions in Modeling Reliability, 530

11–4 System Reliability, 534

11–5 Operating Characteristic Curves, 542

11–6 Reliability and Life Testing Plans, 544

12 Experimental Design and the Taguchi Method 559

12–1 Introduction and Chapter Objectives, 559

12–2 Experimental Design Fundamentals, 560

12–3 Some Experimental Designs, 565

12–4 Factorial Experiments, 585

12–5 The Taguchi Method, 613

12–6 The Taguchi Philosophy, 614

12–7 Loss Functions, 617

12–8 Signal–to–Noise Ratio and Performance Measures, 624

12–9 Critique of S/N Ratios, 627

12–10 Experimental Design in the Taguchi Method, 628

12–11 Parameter Design in the Taguchi Method, 644

12–12 Critique of Experimental Design and the Taguchi Method, 648

Appendixes 665

A–1 Cumulative Binomial Distribution, 665

A–2 Cumulative Poisson Distribution, 670

A–3 Cumulative Standard Normal Distribution, 672

A–4 Values of t for a Specified Right–Tail Area, 675

A–5 Chi–Squared Values for a Specified Right–Tail Area, 677

A–6 Values of F for a Specified Right–Tail Area, 679

A–7 Factors for Computing Center line and Three–Sigma Control Limits, 685

A–8 Uniform Random Numbers, 686

Index 687

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?Experimental design and Taguchi are will explained in the book and reliability analysis is introduced in a brief, but useful section.? (
Quality World, November 2009)

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Note: Product cover images may vary from those shown

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