Produktbild: Introduction to Statistical Quality Control, EMEA Edition

Introduction to Statistical Quality Control, EMEA Edition

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.12.2019

Verlag

John Wiley & Sons Inc

Seitenzahl

768

Maße (L/B/H)

25,5/20,7/3 cm

Gewicht

1287 g

Auflage

8. Auflage

Sprache

Englisch

ISBN

978-1-119-65711-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.12.2019

Verlag

John Wiley & Sons Inc

Seitenzahl

768

Maße (L/B/H)

25,5/20,7/3 cm

Gewicht

1287 g

Auflage

8. Auflage

Sprache

Englisch

ISBN

978-1-119-65711-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Introduction to Statistical Quality Control, EMEA Edition
  • About the Author iii

    Preface v

    Part 1 Introduction 1

    1 Quality Improvement in the Modern Business Environment 3

    Chapter Overview and Learning Objectives 3

    1.1. The Meaning of Quality and Quality Improvement 3

    1.2. A Brief History of Quality Control and Improvement 9

    1.3. Statistical Methods for Quality Control and Improvement 13

    1.4. Management Aspects of Quality Improvement 16

    2 The DMAIC Process 47

    Chapter Overview and Learning Objectives 47

    2.1. Overview of DMAIC 47

    2.2. The Define Step 50

    2.3. The Measure Step 52

    2.4. The Analyze Step 53

    2.5. The Improve Step 54

    2.6. The Control Step 55

    2.7. Examples of DMAIC 56

    Part 2 Statistical Methods Useful in Quality Control and Improvement 63

    3 Modeling Process Quality 65

    Chapter Overview and Learning Objectives 65

    3.1. Describing Variation 65

    3.2. Important Discrete Distributions 79

    3.3. Important Continuous Distributions 85

    3.4. Probability Plots 96

    3.5. Some Useful Approximations 100

    4 Inferences About Process Quality 103

    Chapter Overview and Learning Objectives 103

    4.1. Statistics and Sampling Distributions 104

    4.2. Point Estimation of Process Parameters 109

    4.3. Statistical Inference for a Single Sample 111

    4.4. Statistical Inference for Two Samples 128

    4.5. What if There are More than Two Populations? The Analysis of Variance 143

    4.6. Linear Regression Models 152

    Part 3 Basic Methods of Statistical Process Control and Capability Analysis 173

    5 Methods and Philosophy of Statistical Process Control 175

    Chapter Overview and Learning Objectives 175

    5.1. Introduction 175

    5.2. Chance and Assignable Causes of Quality Variation 176

    5.3. Statistical Basis of the Control Chart 177

    5.4. The Rest of the Magnificent Seven 195

    5.5. Implementing SPC in a Quality Improvement Program 201

    5.6. An Application of SPC 202

    5.7. Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses 208

    6 Control Charts for Variables 218

    Chapter Overview and Learning Objectives 218

    6.1. Introduction 218

    6.2. Control Charts for x¿ and R 219

    6.3. Control Charts for x¿ and s 242

    6.4. The Shewhart Control Chart for Individual Measurements 250

    6.5. Summary of Procedures for x¿, R, and s Charts 260

    6.6. Applications of Variables Control Charts 261

    7 Control Charts for Attributes 265

    Chapter Overview and Learning Objectives 265

    7.1. Introduction 265

    7.2. The Control Chart for Fraction Nonconforming 266

    7.3. Control Charts for Nonconformities (Defects) 289

    7.4. Choice Between Attributes and Variables Control Charts 307

    7.5. Guidelines for Implementing Control Charts 311

    8 Process and Measurement System Capability Analysis 317

    Chapter Overview and Learning Objectives 317

    8.1. Introduction 317

    8.2. Process Capability Analysis Using a Histogram or a Probability Plot 319

    8.3. Process Capability Ratios 323

    8.4. Process Capability Analysis Using a Control Chart 336

    8.5. Process Capability Analysis Using Designed Experiments 338

    8.6. Process Capability Analysis with Attribute Data 338

    8.7. Describing Capability for Many Processes 340

    8.8. Gauge and Measurement System Capability Studies 341

    8.9. Setting Specification Limits on Discrete Components 360

    8.10. Estimating the Natural Tolerance Limits of a Process 366

    Part 4 Other Statistical Process-Monitoring and Control Techniques 369

    9 Cumulative Sum and Exponentially Weighted Moving Average Control Charts 371

    Chapter Overview and Learning Objectives 371

    9.1. The Cumulative Sum Control Chart 372

    9.2. The Exponentially Weighted Moving Average Control Chart 390

    9.3. The Moving Average Control Chart 400

    10 Other Univariate Statistical Process-Monitoring and Control Techniques 403

    Chapter Overview and Learning Objectives 403

    10.1. Statistical Process Control for Short Production Runs 404

    10.2. Modified and Acceptance Control Charts 407

    10.3. Control Charts for Multiple-Stream Processes 412

    10.4. SPC with Autocorrelated Process Data 415

    10.5. Adaptive Sampling Procedures 431

    10.6. Economic Design of Control Charts 433

    10.7. Cuscore Charts 442

    10.8. The Changepoint Model for Process Monitoring 444

    10.9. Profile Monitoring 445

    10.10. Control Charts in Health Care Monitoring and Public Health Surveillance 449

    10.11. Overview of Other Procedures 450

    11 Multivariate Process Monitoring and Control 458

    Chapter Overview and Learning Objectives 458

    11.1. The Multivariate Quality-Control Problem 459

    11.2. Description of Multivariate Data 460

    11.3. The Hotelling T2 Control Chart 462

    11.4. The Multivariate EWMA Control Chart 473

    11.5. Regression Adjustment 476

    11.6. Control Charts for Monitoring Variability 479

    11.7. Latent Structure Methods 482

    12 Engineering Process Control and SPC 488

    Chapter Overview and Learning Objectives 488

    12.1. Process Monitoring and Process Regulation 488

    12.2. Process Control by Feedback Adjustment 489

    12.3. Combining SPC and EPC 500

    Part 5 Process Design and Improvement with Designed Experiments 505

    13 Factorial and Fractional Factorial Experiments for Process Design and Improvement 507

    Chapter Overview and Learning Objectives 507

    13.1. What is Experimental Design? 507

    13.2. Examples of Designed Experiments in Process and Product Improvement 509

    13.3. Guidelines for Designing Experiments 512

    13.4. Factorial Experiments 514

    13.5. The 2k Factorial Design 523

    13.6. Fractional Replication of the 2k Design 551

    14 Process Optimization with Designed Experiments 563

    Chapter Overview and Learning Objectives 563

    14.1. Response Surface Methods and Designs 563

    14.2. Process Robustness Studies 572

    14.3. Evolutionary Operation 583

    Part 6 Acceptance Sampling 589

    15 Lot-by-Lot Acceptance Sampling for Attributes 591

    Chapter Overview and Learning Objectives 591

    15.1. The Acceptance-Sampling Problem 591

    15.2. Single-Sampling Plans for Attributes 596

    15.3. Double, Multiple, and Sequential Sampling 606

    15.4. Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859) 615

    15.5. The Dodge-Romig Sampling Plans 623

    16 Other Acceptance-Sampling Techniques 627

    Chapter Overview and Learning Objectives 627

    16.1. Acceptance Sampling by Variables 627

    16.2. Designing a Variables-Sampling Plan with a Specified OC Curve 630

    16.3. MIL STD 414 (ANSI/ASQC Z1.9) 631

    16.4. Other Variables Sampling Procedures 635

    16.5. Chain Sampling 636

    16.6. Continuous Sampling 638

    16.7. Skip-Lot Sampling Plans 641

    Problems (Available in e-text for students) P-1

    Appendix A-1

    Bibliography (Available in e-text for students) B-1

    Index I-1