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## Book Description

The Seventh Edition of Introduction to Statistical Quality Control provides a comprehensive treatment of the major aspects of using statistical methodology for quality control and improvement. Both traditional and modern methods are presented, including state-of-the-art techniques for statistical process monitoring and control and statistically designed experiments for process characterization, optimization, and process robustness studies. The seventh edition continues to focus on DMAIC (define, measure, analyze, improve, and control--the problem-solving strategy of six sigma) including a chapter on the implementation process. Additionally, the text includes new examples, exercises, problems, and techniques. Statistical Quality Control is best suited for upper-division students in engineering, statistics, business and management science or students in graduate courses.

1. Coverpage
2. Titlepage
5. Preface
6. Contents
7. PART 1 INTRODUCTION
1. 1 QUALITY IMPROVEMENT IN THE MODERN BUSINESS ENVIRONMENT
1. Chapter Overview and Learning Objectives
2. 1.1 The Meaning of Quality and Quality Improvement
3. 1.2 A Brief History of Quality Control and Improvement
4. 1.3 Statistical Methods for Quality Control and Improvement
5. 1.4 Management Aspects of Quality Improvement
2. 2 THE DMAIC PROCESS
1. Chapter Overview and Learning Objectives
2. 2.1 Overview of DMAIC
3. 2.2 The Define Step
4. 2.3 The Measure Step
5. 2.4 The Analyze Step
6. 2.5 The Improve Step
7. 2.6 The Control Step
8. 2.7 Examples of DMAIC
8. PART 2 STATISTICAL METHODS USEFUL IN QUALITY CONTROL AND IMPROVEMENT
1. 3 MODELING PROCESS QUALITY
1. Chapter Overview and Learning Objectives
2. 3.1 Describing Variation
3. 3.2 Important Discrete Distributions
4. 3.3 Important Continuous Distributions
5. 3.4 Probability Plots
6. 3.5 Some Useful Approximations
2. 4 INFERENCES ABOUT PROCESS QUALITY
1. Chapter Overview and Learning Objectives
2. 4.1 Statistics and Sampling Distributions
3. 4.2 Point Estimation of Process Parameters
4. 4.3 Statistical Inference for a Single Sample
5. 4.4 Statistical Inference for Two Samples
6. 4.5 What If There Are More Than Two Populations? The Analysis of Variance
7. 4.6 Linear Regression Models
9. PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS
1. 5 METHODS AND PHILOSOPHY OF STATISTICAL PROCESS CONTROL
1. Chapter Overview and Learning Objectives
2. 5.1 Introduction
3. 5.2 Chance and Assignable Causes of Quality Variation
4. 5.3 Statistical Basis of the Control Chart
5. 5.4 The Rest of the Magnificent Seven
6. 5.5 Implementing SPC in a Quality Improvement Program
7. 5.6 An Application of SPC
8. 5.7 Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses
2. 6 CONTROL CHARTS FOR VARIABLES
1. Chapter Overview and Learning Objectives
2. 6.1 Introduction
3. 6.2 Control Charts for X and R
4. 6.3 Control Charts for X and s
5. 6.4 The Shewhart Control Chart for Individual Measurements
6. 6.5 Summary of Procedures for X, R, and s Charts
7. 6.6 Applications of Variables Control Charts
3. 7 CONTROL CHARTS FOR ATTRIBUTES
1. Chapter Overview and Learning Objectives
2. 7.1 Introduction
3. 7.2 The Control Chart for Fraction Nonconforming
4. 7.3 Control Charts for Nonconformities (Defects)
5. 7.4 Choice Between Attributes and Variables Control Charts
6. 7.5 Guidelines for Implementing Control Charts
4. 8 PROCESS AND MEASUREMENT SYSTEM CAPABILITY ANALYSIS
1. Chapter Overview and Learning Objectives
2. 8.1 Introduction
3. 8.2 Process Capability Analysis Using a Histogram or a Probability Plot
4. 8.3 Process Capability Ratios
5. 8.4 Process Capability Analysis Using a Control Chart
6. 8.5 Process Capability Analysis Using Designed Experiments
7. 8.6 Process Capability Analysis with Attribute Data
8. 8.7 Gauge and Measurement System Capability Studies
9. 8.8 Setting Specification Limits on Discrete Components
10. 8.9 Estimating the Natural Tolerance Limits of a Process
10. PART 4 OTHER STATISTICAL PROCESS-MONITORING AND CONTROL TECHNIQUES
1. 9 CUMULATIVE SUM AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CONTROL CHARTS
1. Chapter Overview and Learning Objectives
2. 9.1 The Cumulative Sum Control Chart
3. 9.2 The Exponentially Weighted Moving Average Control Chart
4. 9.3 The Moving Average Control Chart
2. 10 OTHER UNIVARIATE STATISTICAL PROCESS-MONITORING AND CONTROL TECHNIQUES
1. Chapter Overview and Learning Objectives
2. 10.1 Statistical Process Control for Short Production Runs
3. 10.2 Modified and Acceptance Control Charts
4. 10.3 Control Charts for Multiple-Stream Processes
5. 10.4 SPC With Autocorrelated Process Data
7. 10.6 Economic Design of Control Charts
8. 10.7 Cuscore Charts
9. 10.8 The Changepoint Model for Process Monitoring
10. 10.9 Profile Monitoring
11. 10.10 Control Charts in Health Care Monitoring and Public Health Surveillance
12. 10.11 Overview of Other Procedures
3. 11 MULTIVARIATE PROCESS MONITORING AND CONTROL
1. Chapter Overview and Learning Objectives
2. 11.1 The Multivariate Quality-Control Problem
3. 11.2 Description of Multivariate Data
4. 11.3 The Hotelling T2 Control Chart
5. 11.4 The Multivariate EWMA Control Chart
7. 11.6 Control Charts for Monitoring Variability
8. 11.7 Latent Structure Methods
4. 12 ENGINEERING PROCESS CONTROL AND SPC
1. Chapter Overview and Learning Objectives
2. 12.1 Process Monitoring and Process Regulation
3. 12.2 Process Control by Feedback Adjustment
4. 12.3 Combining SPC and EPC
11. PART 5 PROCESS DESIGN AND IMPROVEMENT WITH DESIGNED EXPERIMENTS
1. 13 FACTORIAL AND FRACTIONAL FACTORIAL EXPERIMENTS FOR PROCESS DESIGN AND IMPROVEMENT
1. Chapter Overview and Learning Objectives
2. 13.1 What is Experimental Design?
3. 13.2 Examples of Designed Experiments In Process and Product Improvement
4. 13.3 Guidelines for Designing Experiments
5. 13.4 Factorial Experiments
6. 13.5 The 2k Factorial Design
7. 13.6 Fractional Replication of the 2k Design
2. 14 PROCESS OPTIMIZATION WITH DESIGNED EXPERIMENTS
1. Chapter Overview and Learning Objectives
2. 14.1 Response Surface Methods and Designs
3. 14.2 Process Robustness Studies
4. 14.3 Evolutionary Operation
12. PART 6 ACCEPTANCE SAMPLING
1. 15 LOT-BY-LOT ACCEPTANCE SAMPLING FOR ATTRIBUTES
1. Chapter Overview and Learning Objectives
2. 15.1 The Acceptance-Sampling Problem
3. 15.2 Single-Sampling Plans for Attributes
4. 15.3 Double, Multiple, and Sequential Sampling
5. 15.4 Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859)
6. 15.5 The Dodge–Romig Sampling Plans
2. 16 OTHER ACCEPTANCE-SAMPLING TECHNIQUES
1. Chapter Overview and Learning Objectives
2. 16.1 Acceptance Sampling by Variables
3. 16.2 Designing a Variables Sampling Plan with a Specified OC Curve
4. 16.3 MIL STD 414 (ANSI/ASQC Z1.9)
5. 16.4 Other Variables Sampling Procedures
6. 16.5 Chain Sampling
7. 16.6 Continuous Sampling
8. 16.7 Skip-Lot Sampling Plans
13. APPENDIX
14. BIBLIOGRAPHY