Introduction to Statistical Quality Control / Edition 6

Introduction to Statistical Quality Control / Edition 6

by Douglas C. Montgomery

ISBN-10: 0470169923

ISBN-13: 9780470169926

Pub. Date: 04/28/2008

Publisher: Wiley

The trusted guide to the statistical methods for quality control and improvement.

Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control, Sixth Edition gives you a sound

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The trusted guide to the statistical methods for quality control and improvement.

Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control, Sixth Edition gives you a sound understanding of the principles of statistical quality control (SQC) and how to apply them in a variety of situations for quality control and improvement.

With this text, you'll learn how to apply state-of-the-art techniques for statistical process monitoring and control, designing experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques.

You’ll appreciate the significant updates in the Sixth Edition including:

  • In-depth attention to DMAIC, the problem-solving strategy of Six Sigma. It will give you an excellent framework to use in conducting quality improvement projects.
  • New examples that illustrate applications of statistical quality improvement techniques in non-manufacturing settings. Many examples and exercises are based on real data.
  • New developments in the area of measurement systems analysis
  • New features of Minitab V15 incorporated into the text
  • Numerous new examples, exercises, problems, and techniques to enhance your absorption of the material

Product Details

Publication date:
Wiley Desktop Editions Series
Edition description:
Older Edition
Product dimensions:
8.27(w) x 9.94(h) x 1.30(d)

Table of Contents

Chapter 1Quality Improvement in the Modern Business Environment1
Chapter Overview and Learning Objectives1
1-1The Meaning of Quality and Quality Improvement2
1-2A Brief History of Quality Control and Improvement8
1-3Statistical Methods for Quality Control and Improvement11
1-4Management Aspects of Quality Improvement15
Part IStatistical Methods Useful in Quality Control and Improvement39
Chapter 2Modeling Process Quality41
Chapter Overview and Learning Objectives41
2-1Describing Variation42
2-2Important Discrete Distributions55
2-3Important Continuous Distributions61
2-4Probability Plots74
2-5Some Useful Approximations77
Chapter 3Inferences about Process Quality86
Chapter Overview and Learning Objectives86
3-1Statistics and Sampling Distributions87
3-2Point Estimation of Process Parameters93
3-3Statistical Inference for a Single Sample96
3-4Statistical Inference for Two Samples112
3-5What If There Are More Than Two Populations? The Analysis of Variance128
Part IIBasic Methods of Statistical Process Control and Capability Analysis145
Chapter 4Methods and Philosophy of Statistical Process Control147
Chapter Overview and Learning Objectives147
4-2Chance and Assignable Causes of Quality Variation148
4-3Statistical Basis of the Control Chart150
4-4The Rest of the "Magnificent Seven"169
4-5Implementing SPC175
4-6An Application of SPC176
4-7Nonmanufacturing Applications of Statistical Process Control183
Chapter 5Control Charts for Variables194
Chapter Overview and Learning Objectives194
5-2Control Charts for x and R196
5-3Control Charts for x and s222
5-4The Shewhart Control Chart for Individual Measurements231
5-5Summary of Procedures for x, R, and s Charts242
5-6Applications of Variables Control Charts243
Chapter 6Control Charts for Attributes265
Chapter Overview and Learning Objectives265
6-2The Control Chart for Fraction Nonconforming266
6-3Control Charts for Nonconformities (Defects)288
6-4Choice Between Attributes and Variables Control Charts306
6-5Guidelines for Implementing Control Charts311
Chapter 7Process and Measurement System Capability Analysis326
Chapter Overview and Learning Objectives326
7-2Process Capability Analysis Using a Histogram or a Probability Plot329
7-3Process Capability Ratios333
7-4Process Capability Analysis Using a Control Chart349
7-5Process Capability Analysis Using Designed Experiments351
7-6Gauge and Measurement System Capability Studies352
7-7Setting Specification Limits on Discrete Components367
7-8Estimating the Natural Tolerance Limits of a Process374
Part IIIOther Statistical Process-Monitoring and Control Techniques383
Chapter 8Cumulative Sum and Exponentially Weighted Moving Average Control Charts385
Chapter Overview and Learning Objectives385
8-1The Cumulative Sum Control Chart386
8-2The Exponentially Weighted Moving Average Control Chart405
8-3The Moving Average Control Chart417
Chapter 9Other Univariate Statistical Process Monitoring and Control Techniques423
Chapter Overview and Learning Objectives423
9-1Statistical Process Control for Short Production Runs424
9-2Modified and Acceptance Control Charts429
9-3Control Charts for Multiple-Stream Processes434
9-4SPC With Autocorrelated Process Data438
9-5Adaptive Sampling Procedures455
9-6Economic Design of Control Charts457
9-7Cuscore Charts467
9-8The Changepoint Model for Process Monitoring470
9-9Overview of Other Procedures472
Chapter 10Multivariate Process Monitoring and Control486
Chapter Overview and Learning Objectives486
10-1The Multivariate Quality-Control Problem487
10-2Description of Multivariate Data489
10-3The Hotelling T[superscript 2] Control Chart491
10-4The Multivariate EWMA Control Chart504
10-5Regression Adjustment507
10-6Control Charts for Monitoring Variability511
10-7Latent Structure Methods513
10-8Profile Monitoring520
Chapter 11Engineering Process Control and SPC526
Chapter Overview and Learning Objectives527
11-1Process Monitoring and Process Regulation527
11-2Process Control by Feedback Adjustment528
11-3Combining SPC and EPC541
Part IVProcess Design and Improvement with Designed Experiments547
Chapter 12Factorial and Fractional Factorial Experiments for Process Design and Improvement549
Chapter Overview and Learning Objectives549
12-1What is Experimental Design?550
12-2Examples of Designed Experiments In Process Improvement551
12-3Guidelines for Designing Experiments555
12-4Factorial Experiments557
12-5The 2[superscript k] Factorial Design567
12-6Fractional Replication of the 2[superscript k] Design595
Chapter 13Process Optimization with Designed Experiments611
13-1Response Surface Methods and Designs612
13-2Process Robustness Studies621
13-3Evolutionary Operation631
Part VAcceptance Sampling643
Chapter 14Lot-by-Lot Acceptance Sampling for Attributes645
Chapter Overview and Learning Objectives645
14-1The Acceptance-Sampling Problem646
14-2Single-Sampling Plans for Attributes652
14-3Double, Multiple, and Sequential Sampling662
14-4Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859)672
14-5The Dodge-Romig Sampling Plans681
Chapter 15Other Acceptance-Sampling Techniques688
15-1Acceptance Sampling by Variables689
15-2Designing a Variables Sampling Plan with a Specified OC Curve692
15-3MIL STD 414 (ANSI/ASQC Z1.9)694
15-4Other Variables Sampling Procedures699
15-5Chain Sampling700
15-6Continuous Sampling702
15-7Skip-Lot Sampling Plans706
I.Summary of Common Probability Distributions Often Used in Statistical Quality Control715
II.Cumulative Standard Normal Distribution716
III.Percentage Points of the x[superscript 2] Distribution718
IV.Percentage Points of the t Distribution719
V.Percentage Points of the F Distribution720
VI.Factors for Constructing Variables Control Charts725
VII.Factors for Two-Sided Normal Tolerance Limits726
VIII.Factors for One-Sided Normal Tolerance Limits727
Answers to Selected Exercises713

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