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Six Sigma Quality Improvement with Minitab, Second Edition

Book Description

This book aims to enable readers to understand and implement, via the widely used statistical software package Minitab (Release 16), statistical methods fundamental to the Six Sigma approach to the continuous improvement of products, processes and services.

The second edition includes the following new material:

  • Pareto charts and Cause-and-Effect diagrams

  • Time-weighted control charts cumulative sum (CUSUM) and exponentially weighted moving average (EWMA)

  • Multivariate control charts

  • Acceptance sampling by attributes and variables (not provided in Release 14)

  • Tests of association using the chi-square distribution

  • Logistic regression

  • Taguchi experimental designs

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