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1 Quality Assurance In the Modern Business Environment1

1-1 THE MEANING OF QUALITY1

1-2 QUALITY ASSURANCE，TECHNOLOGY，AND PRODUCTIVITY3

1-3 QUALITY COSTS5

1-4 METHODS OF QUALITY ASSURANCE11

1-5 THE RESPONSIBILITY FOR QUALITY15

1-6 LEGAL ASPECTS17

1-7 SUMMARY19

PART Ⅰ STATISTICAL METHODS USEFUL IN QUALITY ASSURANCE21

2 Modeling Process Quality23

2-1 DESCRIBING VARIATION23

2-1.1 The Frequency Distribution and Histogram23

2-1.2 Numerical Summary of Data26

2-1.3 Probability Distributions28

2-2 IMPORTANT DISCRETE DISTRIBUTIONS33

2-2.1 The Hypergeometric Distribution33

2-2.2 The Binomial Distribution34

2-2.3 The Poisson Distribution36

2-2.4 The Pascal and Related Distributions37

2-3 IMPORTANT CONTINUOUS DISTRIBUTIONS38

2-3.1 The Normal Distribution38

2-3.2 The Exponential Distribution44

2-3.3 The Gamma Distribution46

2-3.4 The Weibull Distribution47

2-4 SOME USEFUL APPROXIMATIONS49

2-4.1 The Binomial Approximation to the Hypergeometric49

2-4.2 The Poisson Approximation to the Binomial50

2-4.3 The Normal Approximation to the Binomial50

2-4.4 Comments on Approximations51

2-5 EXERCISES52

3 Inferences About Process Quality57

3-1 STATISTICS AND SAMPLING DISTRIBUTIONS58

3-1.1 Sampling from a Normal Distribution59

3-1.2 Sampling from a Bernoulli Distribution62

3-1.3 Sampling from a Poisson Distribution63

3-2 ESTIMATING PROCESS PARAMETERS64

3-2.1 Point Estimation65

3-2.2 Interval Estimation66

3-3 HYPOTHESIS TESTING ON PROCESS PARAMETERS75

3-3.1 Tests on Means,Variance Known77

3-3.2 Tests on Means of Normal Distributions,Variance Unknown79

3-3.3 Tests on Vsriances of Normal Distributions83

3-3.4 Tests on Binomial Parameters85

3-3.5 Tests on Poisson Parsmeters87

3-3.6 The Probability of Type Ⅱ Error89

3-4 EXERCISES92

PART Ⅱ STATISTICAL PROCESS CONTROL99

4 How the Control Chart Works101

4-1 CHANCE AND ASSIGNABLE CAUSES OF QUALITY VARIATION101

4-2 STATISTICAL BASIS OF THE CONTROL CHART102

4-2.1 Basic Principles102

4-2.2 Choice of Control Limits108

4-2.3 Sample Size and Sampling Frequency110

4-3 RATIONAL SUBGROUPS111

4-4 ANALYSIS OF PATTERNS ON CONTROL CHARTS112

4-5 NONMANUFACTURING APPLICATIONS OF CONTROL CHARTS115

4-6 EXERCISES116

5 Control Charts for Attributes119

5-1 INTRODUCTION119

5-2 THE CONTROL CHAR r FOR FRACTION NONCONFORMING119

5-2.1 Development and Operation of the Control Chart121

5-2.2 Variable Sample Size133

5-2.3 The Operating-Characteristic Function139

5-3 CONTROL CHARTS FOR NONCONFORMITIES （DEFECTS）141

5-3.1 Procedures with Constant Sample Size142

5-3.2 Procedures with Variable Sample Size153

5-3.3 Demerit Systems155

5-3.4 The Operating-Characteristic Function156

5-4 EXERCISES158

6 Control Charts for Variables171

6-1 INTRODUCTION171

6-2 CONTROL CHARTS FOR -x AND R173

6-2.1 Statistical Basis of the Charts173

6-2.2 Development and Use of -x and R Charts176

6-2.3 Charts Based on Standard Values188

6-2.4 Interpretation of -x and R Charts189

6-2.5 The Effect of Nonnormality on -x and R Charts192

6-2.6 The Operating-Characteristic Function193

6-3 OTHER CONTROL CHARTS FOR VARIABLES197

6-3.1 -x and S Control Charts197

6-3.2 The S2Control Chart199

6-3.3 Control Charts for Individual Units200

6-3.4 Control Limits Based on a Small Number of Samples202

6-4 CHOICE BETWEEN ATTRIBUTES AND VARIABLES CONTROL CHARTS203

6-5 SUMMARY OF PROCEDURES FOR -x，R，AND S CHARTS205

6-6 GUIDELINES FOR IMPLEMENTING CONTROL CHART PROGRAMS206

6-7 EXERCISES209

7 Other Statistical Process-Control Techniques221

7-1 MODIFIED CONTROL CHARTS221

7-1.1 Basic Principles221

7-1.2 Alternative Designs for the Modified Control Chart224

7-2 THE CUMULATIVE-SUM CONTROL CHART225

7-2.1 Basic Principles225

7-2.2 Designing a Cumulative-Sum Control Chart229

7-2.3 Related Procedures230

7-3 CONTROL CHARTS BASED ON WEIGHTED AVERAGES235

7-3.1 The Moving-Average Control Chart235

7-3.2 The Geometric Moving-Average （GMA）Control Chart239

7-4 PRE-CONTROL243

7-5 METHODS FOR CONTROLLING SEVERAL RELATED QUALITY CHARACTERISTICS245

7-6 STATISTICAL ALTERNATIVES TO CONTROL CHARTS252

7-7 EVOLUTIONARY OPERATION253

7-8 OVERVIEW OF OTHER PROCEDURES260

7-9 EXERCISES265

8 Process-Capability Analysis273

8-1 INTRODUCTION273

8-2 PROCESS-CAPABILITY ANALYSIS USING A HISTOGRAM OR A PROBABILITY PLOT275

8-2.1 Using the Histogram275

8-2.2 Probability Plotting280

8-3 PROCESS-CAPABILITY ANALYSIS USING A CONTROL CHART285

8-4 PROCESS-CAPABILITY ANALYSIS USING DESIGNED EXPERIMENTS288

8-5 SETTING SPECIFICATION LIMITS ON DISCRETE COMPONENTS293

8-5.1 Linear Combinations293

8-5.2 Nonlinear Combinations297

8-6 ESTIMATING THE NATURAL TOLERANCE LIMITS OF A PROCESS300

8-6.1 Tolerance Limits Based on the Normal Distribution300

8-6.2 Nonparametric Tolerance Limits301

8-7 EXERCISES302

9 Economic Design of Control Charts307

9-1 INTRODUCTION307

9-1.1 Process Characteristics308

9-1.2 Cost Parameters309

9-1.3 Early Work and Semieconomic Designs310

9-2 ECONOMIC DESIGN OF THE -x CONTROL CHART312

9-2.1 Single Assignable-Cause Models312

9-2.2 Multiple Assignable-Cause Models324

9-2.3 Joint Economic Design of -x and R Control Charts332

9-3 ECONOMIC DESIGN OF THE CONTROL CHART FOR FRACTION NONCONFORMING333

9-4 ECONOMIC DESIGN OF OTHER CONTROL CHARTS336

9-5 SUMMARY338

APPENDIX 9A A COMPUTER PROGRAM FOR THE ECONOMIC DESIGN OF THE -x CONTROL CHART341

9-6 EXERCISES343

PART Ⅲ ACCEPTANCE SAMPLING349

10 Lot-By-Lot Acceptance sampling for Attrioutes351

10-1 THE ACCEPTANCE-SAMPLING PROBLEM351

10-1.1 Advantages and Disadvantages of Sampling353

10-1.2 Types of Sampling Plans354

10-1.3 Lot Formation354

10-1.4 Random Sampling355

10-1.5 Guidelines for Using Acceptance Sampling356

10-2 SINGLE-SAMPLING PLANS FOR ATTRIBUTES358

10-2.1 Definition of a Single-Sampling Plan358

10-2.2 The OC Curve359

10-2.3 Designing a Single-Samoping Plan With a Specified OC cirve366

10-2.4 Rectifying Inspection367

10-3 DOUBLE,MULTIPLE,AND SEQUENTIAL SAMPLING373

10-3.1 Double-Sampling Plans373

10-3.2 Meltiple-Sampling Plans382

10-3.3 Sequentral-Samping Plans383

10-4 A LOT-SENSITIVE COMPLIANCE(I TPD)SAMPLING PLAN387

10-5 MILITARY STANDARD 105D （ANSI/ASQC Z1.4）389

10-5.1 Description of the Standard389

10-5.2 Procedure392

10-5.3 Discussion408

10-6 DODGE-ROMIG SAMPLING PLANS413

10-6.1 LTPD Plans414

10-6.2 AOQL Plans420

10-6.3 Estimation of Process Average426

10-7 EXERCISES426

11 Acceptance Sampling by Variables431

11-1 INTRODUCTION TO VARIABLES SAMPLING431

11-1.1 Advantages and Disadvantages of Variables Sampling431

11-1.2 Types of Sampling Plans Available432

11-1.3 Caution in the Use of Variables Sampling434

11-2 DESIGNING A VARIABLES SAMPLING PLAN WITH A SPECIFIED OC CURVE435

11-3 MIL STD 414 （ANSI/ASQC Z1.9）439

11-3.1 General Description of the Standard439

11-3.2 Use of the Tsblrs440

11-3.3 Discussion of MIL STD 414 and ANSI/ASQC Z1.9453

11-4 OTHER VARIABLES SAMPLING PROCEDURES455

11-4.1 Sampling by Variables to Give Assurance Regarding the Lot or Process Mean455

11-4.2 Sequential Sampling by Variables456

11-4.3 The Lot-Plot Method456

11-4.4 Narrow-Limit Gaging457

11-5 EXERCISES458

12 Other Acceptance-Sampling Procedures461

12-1 CHAIN SAMPLING461

12-2 CONTINUOUS SAMPLING463

12-2.1 CSP-1464

12-2.2 CSP-2，CSP-3，and Multilevel Plans468

12-2.3 MIL STD 1235B470

12-3 SKIP-LOT SAMPLING PLANS473

12-4 CONSIDERATION OF INSPECTION ERROR477

12-5 ECONOMIC DESIGN OF ACCEPTANCE-SAMPLING PLANS481

12-6 EXERCISES485

BIBLIOGRAPHY489

APPENDIX497

Ⅰ Cumulative Poisson Distribution498

Ⅱ Cumulative Standard Normal Distribution501

Ⅲ Percentage Points of the x2Distribution503

Ⅳ Percentage Points of the r Distribution504

Ⅴ Percentage Points of the F Distribution505

Ⅵ Factors for Constructina variables Control Charts510

Ⅶ Factors for Two-Sided Normal Tolerance Limits511

Ⅷ Factors for One-Sided Normal Tolerance Limits512

Ⅸ Random Numbers513

Index515