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[eBook Code] Fundamentals of Quality Control and Improvement

[eBook Code] Fundamentals of Quality Control and Improvement (eBook Code, 4th)

Amitava Mitra (지은이)
Wiley
218,400원

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· 제목 : [eBook Code] Fundamentals of Quality Control and Improvement (eBook Code, 4th) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 품질관리
· ISBN : 9781118705445
· 쪽수 : 816쪽
· 출판일 : 2016-04-06

목차

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

1-4 Quality Control 12

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 18

1-10 Quality Improvement 18

1-11 Product and Service Costing 19

1-12 Quality Costs 23

1-13 Measuring Quality Costs 27

1-14 Management of Quality 31

1-15 Quality and Productivity 34

1-16 Total Quality Environmental Management 37

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

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

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

3-3 Quality Function Deployment 99

3-4 Benchmarking and Performance Evaluation 106

3-5 Health Care Analytics 115

3-6 Tools for Continuous Quality Improvement 124

3-7 International Standards ISO 9000 and Other Derivatives 137

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 150

4-2 Population and Sample 150

4-3 Parameter and Statistic 150

4-4 Probability 151

4-5 Descriptive Statistics: Describing Product or Process Characteristics 156

4-6 Probability Distributions 173

4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality 189

Summary 212

Appendix: Approximations to Some Probability Distributions 212

Key Terms 215

Exercises 216

References 228

5 Data Analyses and Sampling 229

5-1 Introduction and Chapter Objectives 229

5-2 Empirical Distribution Plots 230

5-3 Randomness of a Sequence 235

5-4 Validating Distributional Assumptions 237

5-5 Transformations to Achieve Normality 240

5-6 Analysis of Count Data 244

5-7 Analysis of Customer Satisfaction Data 248

5-8 Concepts in Sampling 257

Summary 264

Key Terms 265

Exercises 266

References 272

Part III Statistical Process Control 273

6 Statistical Process Control Using Control Charts 275

6-1 Introduction and Chapter Objectives 275

6-2 Causes of Variation 277

6-3 Statistical Basis for Control Charts 277

6-4 Selection of Rational Samples 289

6-5 Analysis of Patterns in Control Charts 290

6-6 Maintenance of Control Charts 294

Summary 295

Key Terms 295

Exercises 295

References 298

7 Control Charts for Variables 299

7-1 Introduction and Chapter Objectives 300

7-2 Selection of Characteristics for Investigation 301

7-3 Preliminary Decisions 302

7-4 Control Charts for the Mean and Range 303

7-5 Control Charts for the Mean and Standard Deviation 321

7-6 Control Charts for Individual Units 326

7-7 Control Charts for Short Production Runs 330

7-8 Other Control Charts 332

7-9 Risk-Adjusted Control Charts 352

7-10 Multivariate Control Charts 359

Summary 372

Key Terms 373

Exercises 374

References 387

8 Control Charts for Attributes 389

8-1 Introduction and Chapter Objectives 390

8-2 Advantages and Disadvantages of Attribute Charts 390

8-3 Preliminary Decisions 392

8-4 Chart for Proportion Nonconforming: p-Chart 392

8-5 Chart for Number of Nonconforming Items: np-Chart 409

8-6 Chart for Number of Nonconformities: c-Chart 411

8-7 Chart for Number of Nonconformities Per Unit: u-Chart 417

8-8 Chart for Demerits Per Unit: u-Chart 423

8-9 Charts for Highly Conforming Processes 426

8-10 Operating Characteristic Curves for Attribute Control Charts 431

Summary 434

Key Terms 435

Exercises 435

References 448

9 Process Capability Analysis 449

9-1 Introduction and Chapter Objectives 449

9-2 Specification Limits and Control Limits 450

9-3 Process Capability Analysis 451

9-4 Natural Tolerance Limits 453

9-5 Specifications and Process Capability 454

9-6 Process Capability Indices 457

9-7 Process Capability Analysis Procedures 476

9-8 Capability Analysis for Nonnormal Distributions 478

9-9 Setting Tolerances on Assemblies and Components 480

9-10 Estimating Statistical Tolerance Limits of a Process 487

Summary 489

Key Terms 490

Exercises 490

References 499

Part IV Acceptance Sampling 501

10 Acceptance Sampling Plans for Attributes and Variables 503

10-1 Introduction and Chapter Objectives 504

10-2 Advantages and Disadvantages of Sampling 504

10-3 Producer and Consumer Risks 505

10-4 Operating Characteristic Curve 505

10-5 Types of Sampling Plans 509

10-6 Evaluating Sampling Plans 511

10-7 Bayes Rule and Decision Making Based on Samples 516

10-8 Lot-by-Lot Attribute Sampling Plans 519

10-9 Other Attribute Sampling Plans 537

10-10 Deming’s kp Rule 540

10-11 Sampling Plans for Variables 543

10-12 Variable Sampling Plans for a Process Parameter 544

10-13 Variable Sampling Plans for Estimating the Lot Proportion Nonconforming 550

Summary 555

Key Terms 556

Exercises 556

References 562

Part V Product and Process Design 563

11 Reliability 565

11-1 Introduction and Chapter Objectives 565

11-2 Reliability 566

11-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability 566

11-4 System Reliability 570

11-5 Operating Characteristic Curves 578

11-6 Reliability and Life Testing Plans 580

11-7 Survival Analysis 588

Summary 599

Key Terms 599

Exercises 600

References 603

12 Experimental Design and the Taguchi Method 605

12-1 Introduction and Chapter Objectives 606

12-2 Experimental Design Fundamentals 606

12-3 Some Experimental Designs 611

12-4 Factorial Experiments 631

12-5 The Taguchi Method 659

12-6 The Taguchi Philosophy 660

12-7 Loss Functions 663

12-8 Signal-to-Noise Ratio and Performance Measures 670

12-9 Critique of S/N Ratios 673

12-10 Experimental Design in the Taguchi Method 674

12-11 Parameter Design in the Taguchi Method 690

12-12 Critique of Experimental Design and the Taguchi Method 694

Summary 696

Key Terms 697

Exercises 698

References 708

13 Process Modeling Through Regression Analysis 711

13-1 Introduction and Chapter Objectives 711

13-2 Deterministic and Probabilistic Models 712

13-3 Model Assumptions 714

13-4 Least Squares Method for Parameter Estimation 716

13-5 Model Validation and Remedial Measures 722

13-6 Estimation and Inferences from a Regression Model 726

13-7 Qualitative Independent Variables 732

13-9 Logistic Regression 742

Summary 746

Key Terms 747

Exercises 748

References 752

Appendixes 753

A-1 Cumulative Binomial Distribution 753

A-2 Cumulative Poisson Distribution 758

A-3 Cumulative Standard Normal Distribution 760

A-4 Values of t for a Specified Right-Tail Area 763

A-5 Chi-Squared Values for a Specified Right-Tail Area 765

A-6 Values of F for a Specified Right-Tail Area 767

A-7 Factors for Computing Centerline and Three-Sigma Control Limits 773

A-8 Uniform Random Numbers 774

Index 775

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