{"product_id":"fundamentals-of-quality-control-and-improvement-isbn-9781118705148","title":"Fundamentals of Quality Control and Improvement","description":"\u003cp\u003e\u003cb\u003eA statistical approach to the principles of quality control and management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIncorporating modern ideas, methods, and philosophies of quality management, \u003ci\u003eFundamentals of Quality Control and Improvement, Fourth Edition\u003c\/i\u003e 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. \u003c\/p\u003e \u003cp\u003ePromoting 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 \u003ci\u003eFourth Edition\u003c\/i\u003e of \u003ci\u003eFundamentals of Quality Control and Improvement\u003c\/i\u003e also includes:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eNew topical coverage on risk-adjustment, capability indices, model building using regression, and survival analysis \u003c\/li\u003e \u003cli\u003eUpdated examples and exercises that enhance the readers’ understanding of the concepts\u003c\/li\u003e \u003cli\u003eDiscussions on the integration of statistical concepts to decision making in the realm of quality assurance \u003c\/li\u003e \u003cli\u003eAdditional concepts, tools, techniques, and issues in the field of health care and health care quality \u003c\/li\u003e \u003cli\u003eA unique display and analysis of customer satisfaction data through surveys with strategic implications on decision making, based on the degree of satisfaction and the degree of importance of survey items\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eFundamentals of Quality Control and Improvement, Fourth Edition\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003eAbout the Companion Website xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Philosophy and Fundamentals 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction to Quality Control and the Total Quality System 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1-1 Introduction and Chapter Objectives 3\u003c\/p\u003e \u003cp\u003e1-2 Evolution of Quality Control 4\u003c\/p\u003e \u003cp\u003e1-3 Quality 7\u003c\/p\u003e \u003cp\u003e1-4 Quality Control 12\u003c\/p\u003e \u003cp\u003e1-5 Quality Assurance 13\u003c\/p\u003e \u003cp\u003e1-6 Quality Circles and Quality Improvement Teams 14\u003c\/p\u003e \u003cp\u003e1-7 Customer Needs and Market Share 15\u003c\/p\u003e \u003cp\u003e1-8 Benefits of Quality Control and the Total Quality System 16\u003c\/p\u003e \u003cp\u003e1-9 Quality and Reliability 18\u003c\/p\u003e \u003cp\u003e1-10 Quality Improvement 18\u003c\/p\u003e \u003cp\u003e1-11 Product and Service Costing 19\u003c\/p\u003e \u003cp\u003e1-12 Quality Costs 23\u003c\/p\u003e \u003cp\u003e1-13 Measuring Quality Costs 27\u003c\/p\u003e \u003cp\u003e1-14 Management of Quality 31\u003c\/p\u003e \u003cp\u003e1-15 Quality and Productivity 34\u003c\/p\u003e \u003cp\u003e1-16 Total Quality Environmental Management 37\u003c\/p\u003e \u003cp\u003eSummary 40\u003c\/p\u003e \u003cp\u003eKey Terms 41\u003c\/p\u003e \u003cp\u003eExercises 41\u003c\/p\u003e \u003cp\u003eReferences 46\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Some Philosophies and Their Impact on Quality 47\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2-1 Introduction and Chapter Objectives 47\u003c\/p\u003e \u003cp\u003e2-2 Service Industries and Their Characteristics 47\u003c\/p\u003e \u003cp\u003e2-3 Model for Service Quality 53\u003c\/p\u003e \u003cp\u003e2-4 W. Edwards Deming’s Philosophy 56\u003c\/p\u003e \u003cp\u003e2-5 Philip B. Crosby’s Philosophy 75\u003c\/p\u003e \u003cp\u003e2-6 Joseph M. Juran’s Philosophy 78\u003c\/p\u003e \u003cp\u003e2-7 The Three Philosophies Compared 82\u003c\/p\u003e \u003cp\u003eSummary 85\u003c\/p\u003e \u003cp\u003eKey Terms 85\u003c\/p\u003e \u003cp\u003eExercises 86\u003c\/p\u003e \u003cp\u003eReferences 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Quality Management: Practices, Tools, and Standards 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3-1 Introduction and Chapter Objectives 89\u003c\/p\u003e \u003cp\u003e3-2 Management Practices 90\u003c\/p\u003e \u003cp\u003e3-3 Quality Function Deployment 99\u003c\/p\u003e \u003cp\u003e3-4 Benchmarking and Performance Evaluation 106\u003c\/p\u003e \u003cp\u003e3-5 Health Care Analytics 115\u003c\/p\u003e \u003cp\u003e3-6 Tools for Continuous Quality Improvement 124\u003c\/p\u003e \u003cp\u003e3-7 International Standards ISO 9000 and Other Derivatives 137\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Statistical Foundations and Methods of Quality Improvement 147\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement 149\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4-1 Introduction and Chapter Objectives 150\u003c\/p\u003e \u003cp\u003e4-2 Population and Sample 150\u003c\/p\u003e \u003cp\u003e4-3 Parameter and Statistic 150\u003c\/p\u003e \u003cp\u003e4-4 Probability 151\u003c\/p\u003e \u003cp\u003e4-5 Descriptive Statistics: Describing Product or Process Characteristics 156\u003c\/p\u003e \u003cp\u003e4-6 Probability Distributions 173\u003c\/p\u003e \u003cp\u003e4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality 189\u003c\/p\u003e \u003cp\u003eSummary 212\u003c\/p\u003e \u003cp\u003eAppendix: Approximations to Some Probability Distributions 212\u003c\/p\u003e \u003cp\u003eKey Terms 215\u003c\/p\u003e \u003cp\u003eExercises 216\u003c\/p\u003e \u003cp\u003eReferences 228\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Data Analyses and Sampling 229\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5-1 Introduction and Chapter Objectives 229\u003c\/p\u003e \u003cp\u003e5-2 Empirical Distribution Plots 230\u003c\/p\u003e \u003cp\u003e5-3 Randomness of a Sequence 235\u003c\/p\u003e \u003cp\u003e5-4 Validating Distributional Assumptions 237\u003c\/p\u003e \u003cp\u003e5-5 Transformations to Achieve Normality 240\u003c\/p\u003e \u003cp\u003e5-6 Analysis of Count Data 244\u003c\/p\u003e \u003cp\u003e5-7 Analysis of Customer Satisfaction Data 248\u003c\/p\u003e \u003cp\u003e5-8 Concepts in Sampling 257\u003c\/p\u003e \u003cp\u003eSummary 264\u003c\/p\u003e \u003cp\u003eKey Terms 265\u003c\/p\u003e \u003cp\u003eExercises 266\u003c\/p\u003e \u003cp\u003eReferences 272\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Statistical Process Control 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Statistical Process Control Using Control Charts 275\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6-1 Introduction and Chapter Objectives 275\u003c\/p\u003e \u003cp\u003e6-2 Causes of Variation 277\u003c\/p\u003e \u003cp\u003e6-3 Statistical Basis for Control Charts 277\u003c\/p\u003e \u003cp\u003e6-4 Selection of Rational Samples 289\u003c\/p\u003e \u003cp\u003e6-5 Analysis of Patterns in Control Charts 290\u003c\/p\u003e \u003cp\u003e6-6 Maintenance of Control Charts 294\u003c\/p\u003e \u003cp\u003eSummary 295\u003c\/p\u003e \u003cp\u003eKey Terms 295\u003c\/p\u003e \u003cp\u003eExercises 295\u003c\/p\u003e \u003cp\u003eReferences 298\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Control Charts for Variables 299\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7-1 Introduction and Chapter Objectives 300\u003c\/p\u003e \u003cp\u003e7-2 Selection of Characteristics for Investigation 301\u003c\/p\u003e \u003cp\u003e7-3 Preliminary Decisions 302\u003c\/p\u003e \u003cp\u003e7-4 Control Charts for the Mean and Range 303\u003c\/p\u003e \u003cp\u003e7-5 Control Charts for the Mean and Standard Deviation 321\u003c\/p\u003e \u003cp\u003e7-6 Control Charts for Individual Units 326\u003c\/p\u003e \u003cp\u003e7-7 Control Charts for Short Production Runs 330\u003c\/p\u003e \u003cp\u003e7-8 Other Control Charts 332\u003c\/p\u003e \u003cp\u003e7-9 Risk-Adjusted Control Charts 352\u003c\/p\u003e \u003cp\u003e7-10 Multivariate Control Charts 359\u003c\/p\u003e \u003cp\u003eSummary 372\u003c\/p\u003e \u003cp\u003eKey Terms 373\u003c\/p\u003e \u003cp\u003eExercises 374\u003c\/p\u003e \u003cp\u003eReferences 387\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Control Charts for Attributes 389\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8-1 Introduction and Chapter Objectives 390\u003c\/p\u003e \u003cp\u003e8-2 Advantages and Disadvantages of Attribute Charts 390\u003c\/p\u003e \u003cp\u003e8-3 Preliminary Decisions 392\u003c\/p\u003e \u003cp\u003e8-4 Chart for Proportion Nonconforming: \u003ci\u003ep\u003c\/i\u003e-Chart 392\u003c\/p\u003e \u003cp\u003e8-5 Chart for Number of Nonconforming Items: \u003ci\u003enp\u003c\/i\u003e-Chart 409\u003c\/p\u003e \u003cp\u003e8-6 Chart for Number of Nonconformities: \u003ci\u003ec\u003c\/i\u003e-Chart 411\u003c\/p\u003e \u003cp\u003e8-7 Chart for Number of Nonconformities Per Unit: \u003ci\u003eu\u003c\/i\u003e-Chart 417\u003c\/p\u003e \u003cp\u003e8-8 Chart for Demerits Per Unit: \u003ci\u003eu\u003c\/i\u003e-Chart 423\u003c\/p\u003e \u003cp\u003e8-9 Charts for Highly Conforming Processes 426\u003c\/p\u003e \u003cp\u003e8-10 Operating Characteristic Curves for Attribute Control Charts 431\u003c\/p\u003e \u003cp\u003eSummary 434\u003c\/p\u003e \u003cp\u003eKey Terms 435\u003c\/p\u003e \u003cp\u003eExercises 435\u003c\/p\u003e \u003cp\u003eReferences 448\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Process Capability Analysis 449\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9-1 Introduction and Chapter Objectives 449\u003c\/p\u003e \u003cp\u003e9-2 Specification Limits and Control Limits 450\u003c\/p\u003e \u003cp\u003e9-3 Process Capability Analysis 451\u003c\/p\u003e \u003cp\u003e9-4 Natural Tolerance Limits 453\u003c\/p\u003e \u003cp\u003e9-5 Specifications and Process Capability 454\u003c\/p\u003e \u003cp\u003e9-6 Process Capability Indices 457\u003c\/p\u003e \u003cp\u003e9-7 Process Capability Analysis Procedures 476\u003c\/p\u003e \u003cp\u003e9-8 Capability Analysis for Nonnormal Distributions 478\u003c\/p\u003e \u003cp\u003e9-9 Setting Tolerances on Assemblies and Components 480\u003c\/p\u003e \u003cp\u003e9-10 Estimating Statistical Tolerance Limits of a Process 487\u003c\/p\u003e \u003cp\u003eSummary 489\u003c\/p\u003e \u003cp\u003eKey Terms 490\u003c\/p\u003e \u003cp\u003eExercises 490\u003c\/p\u003e \u003cp\u003eReferences 499\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Acceptance Sampling 501\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Acceptance Sampling Plans for Attributes and Variables 503\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10-1 Introduction and Chapter Objectives 504\u003c\/p\u003e \u003cp\u003e10-2 Advantages and Disadvantages of Sampling 504\u003c\/p\u003e \u003cp\u003e10-3 Producer and Consumer Risks 505\u003c\/p\u003e \u003cp\u003e10-4 Operating Characteristic Curve 505\u003c\/p\u003e \u003cp\u003e10-5 Types of Sampling Plans 509\u003c\/p\u003e \u003cp\u003e10-6 Evaluating Sampling Plans 511\u003c\/p\u003e \u003cp\u003e10-7 Bayes Rule and Decision Making Based on Samples 516\u003c\/p\u003e \u003cp\u003e10-8 Lot-by-Lot Attribute Sampling Plans 519\u003c\/p\u003e \u003cp\u003e10-9 Other Attribute Sampling Plans 537\u003c\/p\u003e \u003cp\u003e10-10 Deming’s \u003ci\u003ekp \u003c\/i\u003eRule 540\u003c\/p\u003e \u003cp\u003e10-11 Sampling Plans for Variables 543\u003c\/p\u003e \u003cp\u003e10-12 Variable Sampling Plans for a Process Parameter 544\u003c\/p\u003e \u003cp\u003e10-13 Variable Sampling Plans for Estimating the Lot Proportion Nonconforming 550\u003c\/p\u003e \u003cp\u003eSummary 555\u003c\/p\u003e \u003cp\u003eKey Terms 556\u003c\/p\u003e \u003cp\u003eExercises 556\u003c\/p\u003e \u003cp\u003eReferences 562\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart V Product and Process Design 563\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Reliability 565\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11-1 Introduction and Chapter Objectives 565\u003c\/p\u003e \u003cp\u003e11-2 Reliability 566\u003c\/p\u003e \u003cp\u003e11-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability 566\u003c\/p\u003e \u003cp\u003e11-4 System Reliability 570\u003c\/p\u003e \u003cp\u003e11-5 Operating Characteristic Curves 578\u003c\/p\u003e \u003cp\u003e11-6 Reliability and Life Testing Plans 580\u003c\/p\u003e \u003cp\u003e11-7 Survival Analysis 588\u003c\/p\u003e \u003cp\u003eSummary 599\u003c\/p\u003e \u003cp\u003eKey Terms 599\u003c\/p\u003e \u003cp\u003eExercises 600\u003c\/p\u003e \u003cp\u003eReferences 603\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Experimental Design and the Taguchi Method 605\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12-1 Introduction and Chapter Objectives 606\u003c\/p\u003e \u003cp\u003e12-2 Experimental Design Fundamentals 606\u003c\/p\u003e \u003cp\u003e12-3 Some Experimental Designs 611\u003c\/p\u003e \u003cp\u003e12-4 Factorial Experiments 631\u003c\/p\u003e \u003cp\u003e12-5 The Taguchi Method 659\u003c\/p\u003e \u003cp\u003e12-6 The Taguchi Philosophy 660\u003c\/p\u003e \u003cp\u003e12-7 Loss Functions 663\u003c\/p\u003e \u003cp\u003e12-8 Signal-to-Noise Ratio and Performance Measures 670\u003c\/p\u003e \u003cp\u003e12-9 Critique of S\/N Ratios 673\u003c\/p\u003e \u003cp\u003e12-10 Experimental Design in the Taguchi Method 674\u003c\/p\u003e \u003cp\u003e12-11 Parameter Design in the Taguchi Method 690\u003c\/p\u003e \u003cp\u003e12-12 Critique of Experimental Design and the Taguchi Method 694\u003c\/p\u003e \u003cp\u003eSummary 696\u003c\/p\u003e \u003cp\u003eKey Terms 697\u003c\/p\u003e \u003cp\u003eExercises 698\u003c\/p\u003e \u003cp\u003eReferences 708\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Process Modeling Through Regression Analysis 711\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13-1 Introduction and Chapter Objectives 711\u003c\/p\u003e \u003cp\u003e13-2 Deterministic and Probabilistic Models 712\u003c\/p\u003e \u003cp\u003e13-3 Model Assumptions 714\u003c\/p\u003e \u003cp\u003e13-4 Least Squares Method for Parameter Estimation 716\u003c\/p\u003e \u003cp\u003e13-5 Model Validation and Remedial Measures 722\u003c\/p\u003e \u003cp\u003e13-6 Estimation and Inferences from a Regression Model 726\u003c\/p\u003e \u003cp\u003e13-7 Qualitative Independent Variables 732\u003c\/p\u003e \u003cp\u003e13-9 Logistic Regression 742\u003c\/p\u003e \u003cp\u003eSummary 746\u003c\/p\u003e \u003cp\u003eKey Terms 747\u003c\/p\u003e \u003cp\u003eExercises 748\u003c\/p\u003e \u003cp\u003eReferences 752\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendixes 753\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA-1 Cumulative Binomial Distribution 753\u003c\/p\u003e \u003cp\u003eA-2 Cumulative Poisson Distribution 758\u003c\/p\u003e \u003cp\u003eA-3 Cumulative Standard Normal Distribution 760\u003c\/p\u003e \u003cp\u003eA-4 Values of \u003ci\u003et \u003c\/i\u003efor a Specified Right-Tail Area 763\u003c\/p\u003e \u003cp\u003eA-5 Chi-Squared Values for a Specified Right-Tail Area 765\u003c\/p\u003e \u003cp\u003eA-6 Values of \u003ci\u003eF \u003c\/i\u003efor a Specified Right-Tail Area 767\u003c\/p\u003e \u003cp\u003eA-7 Factors for Computing Centerline and Three-Sigma Control Limits 773\u003c\/p\u003e \u003cp\u003eA-8 Uniform Random Numbers 774\u003c\/p\u003e \u003cp\u003eIndex 775\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAmitava Mitra, PhD,\u003c\/b\u003e is Professor in the Department of Systems and Technology and former associate dean in the College of Business at Auburn University, Alabama. He has published over seventy journal articles and currently teaches in the areas of quality assurance and improvement. Dr. Mitra has over thirty years of academic and professional experience, and has conducted courses for professionals in total quality management, quality assurance and statistical process control, design of experiments, and Six Sigma Black Belt training.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA statistical approach to the principles of quality control and management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIncorporating modern ideas, methods, and philosophies of quality management, \u003ci\u003eFundamentals of Quality Control and Improvement, Fourth Edition\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003ePromoting 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 \u003ci\u003eFourth Edition\u003c\/i\u003e of \u003ci\u003eFundamentals of Quality Control and Improvement\u003c\/i\u003e also includes:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eNew topical coverage on risk-adjustment, capability indices, model building using regression, and survival analysis\u003c\/li\u003e \u003cli\u003eUpdated examples and exercises that enhance the readers’ understanding of the concepts\u003c\/li\u003e \u003cli\u003eDiscussions on the integration of statistical concepts to decision making in the realm of quality assurance\u003c\/li\u003e \u003cli\u003eAdditional concepts, tools, techniques, and issues in the field of health care and health care quality\u003c\/li\u003e \u003cli\u003eA unique display and analysis of customer satisfaction data through surveys with strategic implications on decision making, based on the degree of satisfaction and the degree of importance of survey items\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eFundamentals of Quality Control and Improvement, Fourth Edition\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAmitava Mitra, PhD,\u003c\/b\u003e is Professor in the Department of Systems and Technology and former associate dean in the College of Business at Auburn University, Alabama. He has published over seventy journal articles and currently teaches in the areas of quality assurance and improvement. Dr. Mitra has over thirty years of academic and professional experience, and has conducted courses for professionals in total quality management, quality assurance and statistical process control, design of experiments, and Six Sigma Black Belt training.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989263270117,"sku":"NP9781118705148","price":128.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118705148.jpg?v=1761783429","url":"https:\/\/k12savings.com\/products\/fundamentals-of-quality-control-and-improvement-isbn-9781118705148","provider":"K12savings","version":"1.0","type":"link"}