Introduction To Statistical Quality Control 8th Edition

Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.

Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences. A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge.

OC Content available in eBook

SS Student solution available in interactive e-text

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 x̄ and R 219

6.3. Control Charts for x̄ and s 242

6.4. T