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. The Third Edition also features:* Presentation of acceptance sampling and reliability principles* Coverage of ISO 9000 standards* Profiles of past Malcolm Baldrige National Quality Award winners, which illustrate examples of best business practices* Strong emphasis on process control and identification of remedial actions* Integration of service sector examples* The implementation of MINITAB software in applications found throughout the book as well as in the additional data sets that are available via the related Web site* New and revised exercises at the end of most chapters Complete with discussion questions and a summary of key terms in each chapter, Fundamentals of Quality Control and Improvement, Third Edition is an ideal book for courses in management, technology, and engineering at the undergraduate and graduate levels. It also serves as a valuable reference for practitioners and professionals who would like to extend their knowledge of the subject.

Table of Contents:
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