Fundamentals of Quality Control and Improvement

ISBN-13: 9781119692331 / Angielski / Twarda / 2021 / 800 str.

Amitava Mitra

Spis treści

PREFACE xixABOUT THE COMPANION WEBSITE xxiiiPART I PHILOSOPHY AND FUNDAMENTALS 11 Introduction to Quality Control and the Total Quality System 31-1 Introduction and Chapter Objectives 31-2 Evolution of Quality Control 41-3 Quality 7Quality Characteristics 8Variables and Attributes 8Defects 9Standard or Specification 9Quality of Design 10Quality of Conformance 10Quality of Performance 111-4 Quality Control 12Off-Line Quality Control 12Statistical Process Control 12Acceptance Sampling Plans 131-5 Quality Assurance 131-6 Quality Circles and Quality Improvement Teams 141-7 Customer Needs and Market Share 15Kano Model 151-8 Benefits of Quality Control and the Total Quality System 16Total Quality System 171-9 Quality and Reliability 181-10 Quality Improvement 181-11 Product and Service Costing 19Activity-Based Costing 201-12 Quality Costs 23Prevention Costs 23Appraisal Costs 23Internal Failure Costs 24External Failure Costs 24Hidden Failure Costs 24Quality Costs Data Requirements 24Process Cost Approach 261-13 Measuring Quality Costs 27Impact of Quality Improvement on Quality Costs 291-14 Management of Quality 311-15 Quality and Productivity 34Effect on Cost 34Effect on Market 341-16 Total Quality Environmental Management 37Green Supply Chain 39Summary 40Key Terms 41Exercises 41References 462 Some Philosophies and Their Impact on Quality 472-1 Introduction and Chapter Objectives 472-2 Service Industries and Their Characteristics 47Differences in the Manufacturing and Service Sectors 49Service Quality Characteristics 50Measuring Service Quality 52Techniques for Evaluating Service Quality 522-3 Model for Service Quality 532-4 W. Edwards Deming's Philosophy 56Extended Process 57Deming's 14 Points for Management 58Deming's Deadly Diseases 722-5 Philip B. Crosby's Philosophy 75Four Absolutes of Quality Management 7614-Step Plan for Quality Improvement 762-6 Joseph M. Juran's Philosophy 78Quality Trilogy Process 79Quality Planning 79Quality Control 80Quality Improvement 812-7 The Three Philosophies Compared 82Definition of Quality 82Management Commitment 82Strategic Approach to a Quality System 83Measurement of Quality 83Never-Ending Process of Improvement 83Education and Training 83Eliminating the Causes of Problems 84Goal Setting 84Structural Plan 84Summary 85Key Terms 85Exercises 86References 883 Quality Management: Practices Tools and Standards 893-1 Introduction and Chapter Objectives 893-2 Management Practices 90Total Quality Management 90Vision and Quality Policy 92Balanced Scorecard 94Performance Standards 963-3 Quality Function Deployment 99QFD Process 1003-4 Benchmarking and Performance Evaluation 106Benchmarking 107Quality Auditing 110Vendor Selection and Certification Programs 112Vendor Rating and Selection 1123-5 Health Care Analytics 115Health Care Analytics and Big Data 116Uniqueness of Health Care 116Challenges in Health Care Quality 1213-6 Tools for Continuous Quality Improvement 124Pareto Diagrams 124Flowcharts 124Cause-and-Effect Diagrams 126Scatterplots 126Multivariable Charts 127Matrix and Three-Dimensional Plots 129Failure Mode and Effects Criticality Analysis 1313-7 International Standards ISO 9000 and Other Derivatives 137Features of ISO 9000 137Other Industry Standards 138Case Study 139Summary 143Key Terms 144Exercises 145References 149PART II STATISTICAL FOUNDATIONS AND METHODS OF QUALITY IMPROVEMENT 1514 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement 1534-1 Introduction and Chapter Objectives 1544-2 Population and Sample 1544-3 Parameter and Statistic 1544-4 Probability 155Relative Frequency Definition of Probability 155Simple and Compound Events 155Complementary Events 156Additive Law 157Multiplicative Law 158Independence and Mutually Exclusive Events 1584-5 Descriptive Statistics: Describing Product or Process Characteristics 160Data Collection 160Measurement Scales 162Measures of Central Tendency 163Measures of Dispersion 165Measures of Skewness and Kurtosis 170Measures of Association 1734-6 Probability Distributions 177Cumulative Distribution Function 179Expected Value 179Discrete Distributions 180Continuous Distributions 1844-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality 193Sampling Distributions 193Estimation of Product and Process Parameters 194Hypothesis Testing 203Summary 216Appendix: Approximations to Some Probability Distributions 216Binomial Approximation to the Hypergeometric 216Poisson Approximation to the Binomial 216Normal Approximation to the Binomial 217Normal Approximation to the Poisson 218Key Terms 219Exercises 220References 2325 Data Analyses and Sampling 2335-1 Introduction and Chapter Objectives 2335-2 Empirical Distribution Plots 234Histograms 234Stem-and-Leaf Plots 235Box Plots 236Variations of the Basic Box Plot 2385-3 Randomness of a Sequence 239Run Chart 2395-4 Validating Distributional Assumptions 241Probability Plotting 2415-5 Transformations to Achieve Normality 244Some Common Transformations 244Power Transformations 244Johnson Transformation 2455-6 Analysis of Count Data 248Hypothesis Test on Cell Probabilities 248Contingency Tables 249Measures of Association 2515-7 Analysis of Customer Satisfaction Data 252Customer Needs and Their Level of Satisfaction 252Displaying Survey Results 257Analysis of Survey Results 2595-8 Concepts in Sampling 261Sampling Designs and Schemes 262Sample Size Determination 264Bound on the Error of Estimation and Associated Confidence Level 264Estimating the Difference of Two Population Means 266Estimating the Difference of Two Population Proportions 266Controlling the Type I Error Type II Error and Associated Parameter Shift 2675-9 Bayes Rule and Decision Making Based on Samples 2685-10 Deming's kp rule 272Summary 274Key Terms 275Exercises 276References 283PART III STATISTICAL PROCESS CONTROL 2856 Statistical Process Control Using Control Charts 2876-1 Introduction and Chapter Objectives 2876-2 Causes of Variation 289Special Causes 289Common Causes 2896-3 Statistical Basis for Control Charts 289Basic Principles 289Selection of Control Limits 291Errors in Making Inferences from Control Charts 293Effect of Control Limits on Errors in Inference Making 297Warning Limits 298Effect of Sample Size on Control Limits 298Average Run Length 2996-4 Selection of Rational Samples 301Sample Size 301Frequency of Sampling 3016-5 Analysis of Patterns in Control Charts 302Some Rules for Identifying an Out-of-Control Process 302Interpretation of Plots 304Determination of Causes of Out-of-Control Points 3066-6 Maintenance of Control Charts 306Summary 307Key Terms 307Exercises 307References 3107 Control Charts for Variables 3117-1 Introduction and Chapter Objectives 3127-2 Selection of Characteristics for Investigation 3137-3 Preliminary Decisions 314Selection of Rational Samples 314Sample Size 315Frequency of Sampling 315Choice of Measuring Instruments 315Design of Data Recording Forms 3157-4 Control Charts for the Mean and Range 315Development of the Charts 315Variable Sample Size 321Standardized Control Charts 321Control Limits for a Given Target or Standard 322Interpretation and Inferences from the Charts 325Control Chart Patterns and Corrective Actions 3277-5 Control Charts for the Mean and Standard Deviation 333No Given Standards 334Given Standard 3357-6 Control Charts for Individual Units 338No Given Standards 339Given Standard 3407-7 Control Charts for Short Production Runs 342_X- and R-Charts for Short Production Runs 342Z-MR Chart 3427-8 Other Control Charts 344Cumulative Sum Control Chart for the Process Mean 344Tabular Method 345V-Mask Method 348Cumulative Sum for Monitoring Process Variability 351Moving-Average Control Chart 351Exponentially Weighted Moving-Average or Geometric Moving-Average Control Chart 354Modified Control Chart 357Acceptance Control Chart 3617-9 Risk-Adjusted Control Charts 363Risk-Adjusted Cumulative Sum (RACUSUM) Chart 364Risk-Adjusted Sequential Probability Ratio Test (RASPRT) 365Risk-Adjusted Exponentially Weighted Moving-Average (RAEWMA) Chart 366Variable Life-Adjusted Display (VLAD) Chart 3677-10 Multivariate Control Charts 370Controlling Several Related Quality Characteristics 370Hotelling's T2 Control Chart and Its Variations 373Phase 1 and Phase 2 Charts 374Usage and Interpretations 376Individual Observations with Unknown Process Parameters 377Generalized Variance Chart 378Case Study 384Summary 388Key Terms 389Exercises 390References 4038 Control Charts for Attributes 4058-1 Introduction and Chapter Objectives 4068-2 Advantages and Disadvantages of Attribute Charts 406Advantages 406Disadvantages 4078-3 Preliminary Decisions 4088-4 Chart for Proportion Nonconforming: p-Chart 408Construction and Interpretation 409Variable Sample Size 416Risk-Adjusted p-Charts in Health Care 420Special Considerations for p-Charts 4248-5 Chart for Number of Nonconforming Items: np-Chart 425No Standard Given 425Standard Given 4268-6 Chart for Number of Nonconformities: c-Chart 427No Standard Given 428Standard Given 428Probability Limits 430Applications in Health Care When Nonoccurence of Nonconformities Are Not Observable 4318-7 Chart for Number of Nonconformities Per Unit: u-Chart 433Variable Sample Size and No Specified Standard 433Risk-Adjusted u-Charts in Health Care 4368-8 Chart for Demerits Per Unit: u-Chart 439Classification of Nonconformities 439Construction of a U-Chart 4398-9 Charts for Highly Conforming Processes 442Transformation to Normality 442Use of Exponential Distribution for Continuous Variables 442Use of Geometric Distribution for Discrete Variables 443Probability Limits 443Applications in Health Care of Low-Occurrence Nonconformities 4458-10 Operating Characteristic Curves for Attribute Control Charts 447Case Study 450Summary 455Key Terms 455Exercises 456References 4699 Process Capability Analysis 4719-1 Introduction and Chapter Objectives 4719-2 Specification Limits and Control Limits 4729-3 Process Capability Analysis 473Process Capability 4749-4 Natural Tolerance Limits 475Statistical Tolerance Limits 4769-5 Specifications and Process Capability 4769-6 Process Capability Indices 479Cp Index 479Upper and Lower Capability Indices 480Cpk Index 481Capability Ratio 483Taguchi Capability Index Cpm 484Cpmk Index 484Confidence Intervals and Hypothesis Testing on Capability Indices 485Comparison of Capability Indices 486Effect of Measurement Error on Capability Indices 490Gage Repeatability and Reproducibility 492Evaluation of Measurement Systems 493Metrics for Evaluation of Measurement Systems 493Preparation for a Gage Repeatability and Reproducibility Study 494Cp Index and the Nonconformance Rate 4979-7 Process Capability Analysis Procedures 498Estimating Process Mean and Standard Deviation 4989-8 Capability Analysis for Nonnormal Distributions 500Identification of Appropriate Distribution 500Box-Cox Transformation 500Using Attribute Charts 500Using a Nonparametric Approach 5019-9 Setting Tolerances on Assemblies and Components 502Tolerances on Assemblies and Subassemblies 502Tolerance Limits on Individual Components 504Tolerance on Mating Parts 505Nonlinear Combinations of Random Variables 5089-10 Estimating Statistical Tolerance Limits of a Process 509Statistical Tolerance Limits Based on Normal Distribution 509Nonparametric Statistical Tolerance Limits 510Case Study 511Summary 515Key Terms 516Exercises 516References 525PART IV PRODUCT AND PROCESS DESIGN 52710 Reliability 52910-1 Introduction and Chapter Objectives 52910-2 Reliability 53010-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability 530Probability Distributions to Model Failure Rate 531Availability 53410-4 System Reliability 534Systems with Components in Series 535Systems with Components in Parallel 537Systems with Components in Series and in Parallel 539Systems with Standby Components 54010-5 Operating Characteristic Curves 54210-6 Reliability and Life Testing Plans 544Types of Tests 544Life Testing Plans Using the Exponential Distribution 546Standard Life Testing Plans Using Handbook H-108 54810-7 Survival Analysis 552Estimation of the Survival Function 552Confidence Intervals for the Survival Function 557Comparion of Survival Functions of Two Groups 559Summary 563Key Terms 563Exercises 564References 56711 Experimental Design and the Taguchi Method 56911-1 Introduction and Chapter Objectives 57011-2 Experimental Design Fundamentals 570Features of Experimentation 57411-3 Some Experimental Designs 575Completely Randomized Design 576Randomized Block Design 582Latin Square Design 58711-4 Factorial Experiments 595Two-Factor Factorial Experiment Using a Completely Randomized Design 596Two-Factor Factorial Experiment Using a Randomized Block Design 600Role of Contrasts 606The 2k Factorial Experiment 612Confounding in 2k Factorial Experiments 616Fractional Replication in 2k Experiments 61711-5 The Taguchi Method 62311-6 The Taguchi Philosophy 62411-7 Loss Functions 627Target Is Best 628Smaller Is Better 631Larger Is Better 63211-8 Signal-to-Noise Ratio and Performance Measures 634Target Is Best 634Smaller Is Better 637Larger Is Better 63711-9 Critique of S/N Ratios 63711-10 Experimental Design in the Taguchi Method 638Orthogonal Arrays and Linear Graphs 639Estimation of Effects 64911-11 Parameter Design in the Taguchi Method 654Application to Attribute Data 65611-12 Critique of Experimental Design and the Taguchi Method 658Summary 660Key Terms 661Exercises 662References 67212 Process Modeling Through Regression Analysis 67512-1 Introduction and Chapter Objectives 67512-2 Deterministic and Probabilistic Models 67612-3 Model Assumptions 67812-4 Least Squares Method for Parameter Estimation 680Performance Measures of a Regression Model 68312-5 Model Validation and Remedial Measures 686Linearity of Regression Function 686Constancy of Error Variance 687Normality of Error Component 689Independence of Error Components 68912-6 Estimation and Inferences from a Regression Model 690Inferences on Individual ßi Parameters 691Inferences on All ßi i= 1 2 . . . p . 1 Parameters 691Simultaneous Inferences on Some ßi i= 1 2 . . . p . 1 691Hypothesis Tests on a Subset of ßi Parameters 692Estimation of Mean Response 692Simultaneous Confidence Intervals for Several Mean Responses 693Prediction of Individual Observations 693Simultaneous Prediction Intervals for Several New Observations 69312-7 Qualitative Independent Variables 696Additive Model 696Interaction Model 69712-8 Issues in Multiple Regression 702Data from a Retrospective Versus Designed Experiment 702Outliers in the Space of the Independent Variables 703Outliers for the Dependent Variable 704Influential Observations 705Multicollinearity 706Detection of Multicollinearity 706Effects of Multicollinearity 70712-9 Logistic Regression 707Binary Response Variable 708Assumptions in Regression 709Nominal Polytomous Response Variable 712Ordinal Polytomous Response Variable 71512-10 Classification Problems 719Performance Measures in Classification Problems 720Tests of Association in 2 × 2 Contingency Tables 722Receiver Operating Characteristic Curve 723Summary 725Key Terms 725Exercises 726References 732Appendixes 733A-1 Cumulative Binomial Distribution 733A-2 Cumulative Poisson Distribution 738A-3 Cumulative Standard Normal Distribution 740A-4 Values of t for a Specified Right-Tail Area 743A-5 Chi-Squared Values for a Specified Right-Tail Area 745A-6 Values of F for a Specified Right-Tail Area 747A-7 Factors for Computing Centerline and Three-Sigma Control Limits 753A-8 Uniform Random Numbers 754Index 000

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Amitava Mitra, PhD, is Professor in the Department of Systems and Technology and the former Associate Dean in the College of Business at Auburn University, Alabama. He has published over 70 journal articles and teaches quality assurance and improvement.