Six Sigma Quality Improvement with Minitab, Second Edition

Table of contents

1. Cover
2. Title Page
3. Copyright
4. Dedication
5. Foreword
6. Preface
   1. Rationale
   2. Content
   3. Using the Book
7. Acknowledgements
8. About the Author
9. Chapter 1: Introduction
   1. Overview
   2. 1.1 Quality and Quality Improvement
   3. 1.2 Six Sigma Quality Improvement
   4. 1.3 The Six Sigma Roadmap and DMAIC
   5. 1.4 The Role of Statistical Methods in Six Sigma
   6. 1.5 Minitab and Its Role in the Implementation of Statistical Methods
   7. 1.6 Exercises and follow-up Activities
10. Chapter 2: Data Display, Summary and Manipulation
    1. Overview
    2. 2.1 The Run Chart – a First Minitab session
    3. 2.2 Display and Summary of Univariate Data
    4. 2.3 Data Input, Output, Manipulation and Management
    5. 2.4 Exercises and Follow-up Activities
11. Chapter 3: Exploratory Data Analysis, Display and Summary of Multivariate Data
    1. Overview
    2. 3.1 Exploratory Data Analysis
    3. 3.2 Display and Summary of Bivariate and Multivariate Data
    4. 3.4 Exercises and follow-up Activities
12. Chapter 4: Statistical Models
    1. Overview
    2. 4.1 Fundamentals of Probability
    3. 4.2 Probability Distributions for Counts and Measurements
    4. 4.3 Distribution of Means and Proportions
    5. 4.4 Multivariate Normal Distribution
    6. 4.5 Statistical Models Applied to Acceptance Sampling
    7. 4.6 Exercises and follow-up Activities
13. Chapter 5: Control Charts
    1. Overview
    2. 5.1 Shewhart Charts for Measurement Data
    3. 5.2 Shewhart Charts for Attribute Data
    4. 5.3 Time-weighted Control Charts
    5. 5.4 Process Adjustment
    6. 5.5 Multivariate Control Charts
    7. 5.6 Exercises and follow-up Activities
14. Chapter 6: Process Capability Analysis
    1. Overview
    2. 6.1 Process Capability
    3. 6.2 Exercises and Follow-up Activities
15. Chapter 7: Process Experimentation with a Single Factor
    1. Overview
    2. 7.1 Fundamentals of Hypothesis Testing
    3. 7.2 Tests and Confidence Intervals for the Comparison of Means and Proportions with a Standard
    4. 7.3 Tests and Confidence Intervals for the Comparison of two Means or Two Proportions
    5. 7.4 The Analysis of Paired Data – t-tests and Sign Tests
    6. 7.5 Experiments with a Single Factor Having More Than Two Levels
    7. 7.6 Blocking in single-factor Experiments
    8. 7.7 Experiments with a Single Factor, with More Than Two Levels, where the Response is a Proportion
    9. 7.8 Tests for Equality of Variances
    10. 7.9 Exercises and Follow-up Activities
16. Chapter 8: Process Experimentation with Two or More Factors
    1. Overview
    2. 8.1 General factorial experiments
    3. 8.2 Full Factorial Experiments in the 2k Series
    4. 8.3 Fractional Factorial Experiments in the 2k−p Series
    5. 8.4 Taguchi Experimental Designs
    6. 8.5 Exercises and Follow-Up Activities
17. Chapter 9: Evaluation of Measurement Processes
    1. 9.1 Overview
    2. 9.2 Measurement Process Concepts
    3. 9.3 Gauge Repeatability and Reproducibility Studies
    4. 9.4 Comparison of Measurement Systems
    5. 9.5 Attribute Scenarios
    6. 9.6 Exercises and Follow-Up Activities
18. Chapter 10: Regression and Model Building
    1. Overview
    2. 10.1 Regression with a Single Predictor Variable
    3. 10.2 Multiple Regression
    4. 10.3 Response Surface Methods
    5. 10.4 Categorical Data and Logistic Regression
    6. 10.5 Exercises and Follow-Up Activities
19. Chapter 11: Learning More and Further Minitab
    1. Overview
    2. 11.1 Learning More about Minitab and Obtaining Help
    3. 11.2 Macros
    4. 11.3 Further Features of Minitab
    5. 11.4 Quality Companion
    6. 11.5 Postscript
20. Appendix 1
21. Appendix 2
22. Appendix 3
    1. Charts Based on Variables (Measurements)
    2. Charts Based on Attributes (Counts)
23. Appendix 4
24. References
25. Index