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Fundamentals of Quality Control and Improvement

Autor Amitava Mitra
en Limba Engleză Hardback – 28 iun 2021
The newest edition of an insightful and practical statistical approach to quality control and management In the newly revised and thoroughly updated Fifth Edition of Fundamentals of Quality Control and Improvement, accomplished academic, consultant, and author Dr. Amitava Mitra delivers a comprehensive and quantitative approach to quality management techniques. The book demonstrates how to integrate statistical concepts with quality assurance methods, incorporating modern ideas, strategies, and philosophies of quality management. You'll discover experimental design concepts and the use of the Taguchi method to incorporate customer needs, improve lead time, and reduce costs. The new edition also includes brand-new case studies at the end of several chapters, references to the statistical software Minitab 19, and chapter updates that add discussions of trending and exciting topics in quality control. The book includes access to supplementary material for instructors consisting of a new instructor's solutions manual and PowerPoint slides, as well as access to data sets for all readers. Readers will also benefit from the inclusion of: * A thorough introduction to the evolution of quality and definitions of quality, quality control, quality assurance, quality circles, and quality improvement teams * An exploration of customer needs and market share, as well as the benefits of quality control and the total quality system * Practical discussions of quality and reliability, quality improvement, product and service costing, and quality costs * A concise treatment of how to measure quality costs, the management of quality, and the interrelationship between quality and productivity Perfect for upper-level undergraduate and graduate students in quality control and improvement, the Fifth Edition of Fundamentals of Quality Control and Improvement will also earn a place in the libraries of business students and those undertaking training programs in Six Sigma.
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Specificații

ISBN-13: 9781119692331
ISBN-10: 1119692334
Pagini: 800
Dimensiuni: 178 x 254 x 45 mm
Greutate: 1.58 kg
Ediția:5th Edition
Editura: Wiley
Locul publicării:Hoboken, United States

Cuprins

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 Quality Characteristics 8 Variables and Attributes 8 Defects 9 Standard or Specification 9 Quality of Design 10 Quality of Conformance 10 Quality of Performance 11 1-4 Quality Control 12 Off-Line Quality Control 12 Statistical Process Control 12 Acceptance Sampling Plans 13 1-5 Quality Assurance 13 1-6 Quality Circles and Quality Improvement Teams 14 1-7 Customer Needs and Market Share 15 Kano Model 15 1-8 Benefits of Quality Control and the Total Quality System 16 Total Quality System 17 1-9 Quality and Reliability 18 1-10 Quality Improvement 18 1-11 Product and Service Costing 19 Activity-Based Costing 20 1-12 Quality Costs 23 Prevention Costs 23 Appraisal Costs 23 Internal Failure Costs 24 External Failure Costs 24 Hidden Failure Costs 24 Quality Costs Data Requirements 24 Process Cost Approach 26 1-13 Measuring Quality Costs 27 Impact of Quality Improvement on Quality Costs 29 1-14 Management of Quality 31 1-15 Quality and Productivity 34 Effect on Cost 34 Effect on Market 34 1-16 Total Quality Environmental Management 37 Green Supply Chain 39 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 Differences in the Manufacturing and Service Sectors 49 Service Quality Characteristics 50 Measuring Service Quality 52 Techniques for Evaluating Service Quality 52 2-3 Model for Service Quality 53 2-4 W. Edwards Deming's Philosophy 56 Extended Process 57 Deming's 14 Points for Management 58 Deming's Deadly Diseases 72 2-5 Philip B. Crosby's Philosophy 75 Four Absolutes of Quality Management 76 14-Step Plan for Quality Improvement 76 2-6 Joseph M. Juran's Philosophy 78 Quality Trilogy Process 79 Quality Planning 79 Quality Control 80 Quality Improvement 81 2-7 The Three Philosophies Compared 82 Definition of Quality 82 Management Commitment 82 Strategic Approach to a Quality System 83 Measurement of Quality 83 Never-Ending Process of Improvement 83 Education and Training 83 Eliminating the Causes of Problems 84 Goal Setting 84 Structural Plan 84 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 Total Quality Management 90 Vision and Quality Policy 92 Balanced Scorecard 94 Performance Standards 96 3-3 Quality Function Deployment 99 QFD Process 100 3-4 Benchmarking and Performance Evaluation 106 Benchmarking 107 Quality Auditing 110 Vendor Selection and Certification Programs 112 Vendor Rating and Selection 112 3-5 Health Care Analytics 115 Health Care Analytics and Big Data 116 Uniqueness of Health Care 116 Challenges in Health Care Quality 121 3-6 Tools for Continuous Quality Improvement 124 Pareto Diagrams 124 Flowcharts 124 Cause-and-Effect Diagrams 126 Scatterplots 126 Multivariable Charts 127 Matrix and Three-Dimensional Plots 129 Failure Mode and Effects Criticality Analysis 131 3-7 International Standards ISO 9000 and Other Derivatives 137 Features of ISO 9000 137 Other Industry Standards 138 Case Study 139 Summary 143 Key Terms 144 Exercises 145 References 149 PART II STATISTICAL FOUNDATIONS AND METHODS OF QUALITY IMPROVEMENT 151 4 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement 153 4-1 Introduction and Chapter Objectives 154 4-2 Population and Sample 154 4-3 Parameter and Statistic 154 4-4 Probability 155 Relative Frequency Definition of Probability 155 Simple and Compound Events 155 Complementary Events 156 Additive Law 157 Multiplicative Law 158 Independence and Mutually Exclusive Events 158 4-5 Descriptive Statistics: Describing Product or Process Characteristics 160 Data Collection 160 Measurement Scales 162 Measures of Central Tendency 163 Measures of Dispersion 165 Measures of Skewness and Kurtosis 170 Measures of Association 173 4-6 Probability Distributions 177 Cumulative Distribution Function 179 Expected Value 179 Discrete Distributions 180 Continuous Distributions 184 4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality 193 Sampling Distributions 193 Estimation of Product and Process Parameters 194 Hypothesis Testing 203 Summary 216 Appendix: Approximations to Some Probability Distributions 216 Binomial Approximation to the Hypergeometric 216 Poisson Approximation to the Binomial 216 Normal Approximation to the Binomial 217 Normal Approximation to the Poisson 218 Key Terms 219 Exercises 220 References 232 5 Data Analyses and Sampling 233 5-1 Introduction and Chapter Objectives 233 5-2 Empirical Distribution Plots 234 Histograms 234 Stem-and-Leaf Plots 235 Box Plots 236 Variations of the Basic Box Plot 238 5-3 Randomness of a Sequence 239 Run Chart 239 5-4 Validating Distributional Assumptions 241 Probability Plotting 241 5-5 Transformations to Achieve Normality 244 Some Common Transformations 244 Power Transformations 244 Johnson Transformation 245 5-6 Analysis of Count Data 248 Hypothesis Test on Cell Probabilities 248 Contingency Tables 249 Measures of Association 251 5-7 Analysis of Customer Satisfaction Data 252 Customer Needs and Their Level of Satisfaction 252 Displaying Survey Results 257 Analysis of Survey Results 259 5-8 Concepts in Sampling 261 Sampling Designs and Schemes 262 Sample Size Determination 264 Bound on the Error of Estimation and Associated Confidence Level 264 Estimating the Difference of Two Population Means 266 Estimating the Difference of Two Population Proportions 266 Controlling the Type I Error Type II Error and Associated Parameter Shift 267 5-9 Bayes Rule and Decision Making Based on Samples 268 5-10 Deming's kp rule 272 Summary 274 Key Terms 275 Exercises 276 References 283 PART III STATISTICAL PROCESS CONTROL 285 6 Statistical Process Control Using Control Charts 287 6-1 Introduction and Chapter Objectives 287 6-2 Causes of Variation 289 Special Causes 289 Common Causes 289 6-3 Statistical Basis for Control Charts 289 Basic Principles 289 Selection of Control Limits 291 Errors in Making Inferences from Control Charts 293 Effect of Control Limits on Errors in Inference Making 297 Warning Limits 298 Effect of Sample Size on Control Limits 298 Average Run Length 299 6-4 Selection of Rational Samples 301 Sample Size 301 Frequency of Sampling 301 6-5 Analysis of Patterns in Control Charts 302 Some Rules for Identifying an Out-of-Control Process 302 Interpretation of Plots 304 Determination of Causes of Out-of-Control Points 306 6-6 Maintenance of Control Charts 306 Summary 307 Key Terms 307 Exercises 307 References 310 7 Control Charts for Variables 311 7-1 Introduction and Chapter Objectives 312 7-2 Selection of Characteristics for Investigation 313 7-3 Preliminary Decisions 314 Selection of Rational Samples 314 Sample Size 315 Frequency of Sampling 315 Choice of Measuring Instruments 315 Design of Data Recording Forms 315 7-4 Control Charts for the Mean and Range 315 Development of the Charts 315 Variable Sample Size 321 Standardized Control Charts 321 Control Limits for a Given Target or Standard 322 Interpretation and Inferences from the Charts 325 Control Chart Patterns and Corrective Actions 327 7-5 Control Charts for the Mean and Standard Deviation 333 No Given Standards 334 Given Standard 335 7-6 Control Charts for Individual Units 338 No Given Standards 339 Given Standard 340 7-7 Control Charts for Short Production Runs 342 _X- and R-Charts for Short Production Runs 342 Z-MR Chart 342 7-8 Other Control Charts 344 Cumulative Sum Control Chart for the Process Mean 344 Tabular Method 345 V-Mask Method 348 Cumulative Sum for Monitoring Process Variability 351 Moving-Average Control Chart 351 Exponentially Weighted Moving-Average or Geometric Moving-Average Control Chart 354 Modified Control Chart 357 Acceptance Control Chart 361 7-9 Risk-Adjusted Control Charts 363 Risk-Adjusted Cumulative Sum (RACUSUM) Chart 364 Risk-Adjusted Sequential Probability Ratio Test (RASPRT) 365 Risk-Adjusted Exponentially Weighted Moving-Average (RAEWMA) Chart 366 Variable Life-Adjusted Display (VLAD) Chart 367 7-10 Multivariate Control Charts 370 Controlling Several Related Quality Characteristics 370 Hotelling's T2 Control Chart and Its Variations 373 Phase 1 and Phase 2 Charts 374 Usage and Interpretations 376 Individual Observations with Unknown Process Parameters 377 Generalized Variance Chart 378 Case Study 384 Summary 388 Key Terms 389 Exercises 390 References 403 8 Control Charts for Attributes 405 8-1 Introduction and Chapter Objectives 406 8-2 Advantages and Disadvantages of Attribute Charts 406 Advantages 406 Disadvantages 407 8-3 Preliminary Decisions 408 8-4 Chart for Proportion Nonconforming: p-Chart 408 Construction and Interpretation 409 Variable Sample Size 416 Risk-Adjusted p-Charts in Health Care 420 Special Considerations for p-Charts 424 8-5 Chart for Number of Nonconforming Items: np-Chart 425 No Standard Given 425 Standard Given 426 8-6 Chart for Number of Nonconformities: c-Chart 427 No Standard Given 428 Standard Given 428 Probability Limits 430 Applications in Health Care When Nonoccurence of Nonconformities Are Not Observable 431 8-7 Chart for Number of Nonconformities Per Unit: u-Chart 433 Variable Sample Size and No Specified Standard 433 Risk-Adjusted u-Charts in Health Care 436 8-8 Chart for Demerits Per Unit: u-Chart 439 Classification of Nonconformities 439 Construction of a U-Chart 439 8-9 Charts for Highly Conforming Processes 442 Transformation to Normality 442 Use of Exponential Distribution for Continuous Variables 442 Use of Geometric Distribution for Discrete Variables 443 Probability Limits 443 Applications in Health Care of Low-Occurrence Nonconformities 445 8-10 Operating Characteristic Curves for Attribute Control Charts 447 Case Study 450 Summary 455 Key Terms 455 Exercises 456 References 469 9 Process Capability Analysis 471 9-1 Introduction and Chapter Objectives 471 9-2 Specification Limits and Control Limits 472 9-3 Process Capability Analysis 473 Process Capability 474 9-4 Natural Tolerance Limits 475 Statistical Tolerance Limits 476 9-5 Specifications and Process Capability 476 9-6 Process Capability Indices 479 Cp Index 479 Upper and Lower Capability Indices 480 Cpk Index 481 Capability Ratio 483 Taguchi Capability Index Cpm 484 Cpmk Index 484 Confidence Intervals and Hypothesis Testing on Capability Indices 485 Comparison of Capability Indices 486 Effect of Measurement Error on Capability Indices 490 Gage Repeatability and Reproducibility 492 Evaluation of Measurement Systems 493 Metrics for Evaluation of Measurement Systems 493 Preparation for a Gage Repeatability and Reproducibility Study 494 Cp Index and the Nonconformance Rate 497 9-7 Process Capability Analysis Procedures 498 Estimating Process Mean and Standard Deviation 498 9-8 Capability Analysis for Nonnormal Distributions 500 Identification of Appropriate Distribution 500 Box-Cox Transformation 500 Using Attribute Charts 500 Using a Nonparametric Approach 501 9-9 Setting Tolerances on Assemblies and Components 502 Tolerances on Assemblies and Subassemblies 502 Tolerance Limits on Individual Components 504 Tolerance on Mating Parts 505 Nonlinear Combinations of Random Variables 508 9-10 Estimating Statistical Tolerance Limits of a Process 509 Statistical Tolerance Limits Based on Normal Distribution 509 Nonparametric Statistical Tolerance Limits 510 Case Study 511 Summary 515 Key Terms 516 Exercises 516 References 525 PART IV PRODUCT AND PROCESS DESIGN 527 10 Reliability 529 10-1 Introduction and Chapter Objectives 529 10-2 Reliability 530 10-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability 530 Probability Distributions to Model Failure Rate 531 Availability 534 10-4 System Reliability 534 Systems with Components in Series 535 Systems with Components in Parallel 537 Systems with Components in Series and in Parallel 539 Systems with Standby Components 540 10-5 Operating Characteristic Curves 542 10-6 Reliability and Life Testing Plans 544 Types of Tests 544 Life Testing Plans Using the Exponential Distribution 546 Standard Life Testing Plans Using Handbook H-108 548 10-7 Survival Analysis 552 Estimation of the Survival Function 552 Confidence Intervals for the Survival Function 557 Comparion of Survival Functions of Two Groups 559 Summary 563 Key Terms 563 Exercises 564 References 567 11 Experimental Design and the Taguchi Method 569 11-1 Introduction and Chapter Objectives 570 11-2 Experimental Design Fundamentals 570 Features of Experimentation 574 11-3 Some Experimental Designs 575 Completely Randomized Design 576 Randomized Block Design 582 Latin Square Design 587 11-4 Factorial Experiments 595 Two-Factor Factorial Experiment Using a Completely Randomized Design 596 Two-Factor Factorial Experiment Using a Randomized Block Design 600 Role of Contrasts 606 The 2k Factorial Experiment 612 Confounding in 2k Factorial Experiments 616 Fractional Replication in 2k Experiments 617 11-5 The Taguchi Method 623 11-6 The Taguchi Philosophy 624 11-7 Loss Functions 627 Target Is Best 628 Smaller Is Better 631 Larger Is Better 632 11-8 Signal-to-Noise Ratio and Performance Measures 634 Target Is Best 634 Smaller Is Better 637 Larger Is Better 637 11-9 Critique of S/N Ratios 637 11-10 Experimental Design in the Taguchi Method 638 Orthogonal Arrays and Linear Graphs 639 Estimation of Effects 649 11-11 Parameter Design in the Taguchi Method 654 Application to Attribute Data 656 11-12 Critique of Experimental Design and the Taguchi Method 658 Summary 660 Key Terms 661 Exercises 662 References 672 12 Process Modeling Through Regression Analysis 675 12-1 Introduction and Chapter Objectives 675 12-2 Deterministic and Probabilistic Models 676 12-3 Model Assumptions 678 12-4 Least Squares Method for Parameter Estimation 680 Performance Measures of a Regression Model 683 12-5 Model Validation and Remedial Measures 686 Linearity of Regression Function 686 Constancy of Error Variance 687 Normality of Error Component 689 Independence of Error Components 689 12-6 Estimation and Inferences from a Regression Model 690 Inferences on Individual ßi Parameters 691 Inferences on All ßi i= 1 2 . . . p . 1 Parameters 691 Simultaneous Inferences on Some ßi i= 1 2 . . . p . 1 691 Hypothesis Tests on a Subset of ßi Parameters 692 Estimation of Mean Response 692 Simultaneous Confidence Intervals for Several Mean Responses 693 Prediction of Individual Observations 693 Simultaneous Prediction Intervals for Several New Observations 693 12-7 Qualitative Independent Variables 696 Additive Model 696 Interaction Model 697 12-8 Issues in Multiple Regression 702 Data from a Retrospective Versus Designed Experiment 702 Outliers in the Space of the Independent Variables 703 Outliers for the Dependent Variable 704 Influential Observations 705 Multicollinearity 706 Detection of Multicollinearity 706 Effects of Multicollinearity 707 12-9 Logistic Regression 707 Binary Response Variable 708 Assumptions in Regression 709 Nominal Polytomous Response Variable 712 Ordinal Polytomous Response Variable 715 12-10 Classification Problems 719 Performance Measures in Classification Problems 720 Tests of Association in 2 × 2 Contingency Tables 722 Receiver Operating Characteristic Curve 723 Summary 725 Key Terms 725 Exercises 726 References 732 Appendixes 733 A-1 Cumulative Binomial Distribution 733 A-2 Cumulative Poisson Distribution 738 A-3 Cumulative Standard Normal Distribution 740 A-4 Values of t for a Specified Right-Tail Area 743 A-5 Chi-Squared Values for a Specified Right-Tail Area 745 A-6 Values of F for a Specified Right-Tail Area 747 A-7 Factors for Computing Centerline and Three-Sigma Control Limits 753 A-8 Uniform Random Numbers 754 Index 000