Six Sigma Quality Improvement with Minitab

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9780470741740: Six Sigma Quality Improvement with Minitab

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

"synopsis" may belong to another edition of this title.

From the Back Cover:

As Six Sigma evolves, it continues to be used worldwide to identify and remove causes of nonconformance and to reduce variability in manufacturing, business and healthcare processes. It is applied through a structured, project-based approach that places emphasis on the use of statistical methods. This new edition of Six Sigma Quality Improvement with Minitab enables readers to understand and implement data displays and statistical methods fundamental to Six Sigma via the highly popular, widely available and easy to use statistical software Minitab (Release 16).

Key Features:
    Provides an introduction to key statistical methods for Six Sigma and quality improvement and their application via Minitab.
  • No prior knowledge of statistics or Minitab is assumed and theory is kept to an absolute minimum.
  • Explanations are detailed, carefully worded and supported by numerous screen captures.
  • Explores additional topics, including Pareto charts, cause-and-effect diagrams, time-weighted control charts, multivariate control charts and logistics regression.
  • Uses random data generation facilities in Minitab, to illustrate key statistical results and concepts.
  • Presents informative follow-up exercises from a wide variety of scenarios, on each topic.
  • Supported by a website providing data sets for download and comprehensive notes and answers to the follow-up exercises.
  • Includes information on the comprehensive help facilities available to Minitab users such as the new Assistant.

      This book will be of great value to Six Sigma Green and Black Belts and to quality improvement practitioners generally. In addition, students and anyone with an interest in quality improvement, data analysis, statistics methods and their implementation via Minitab, will also find this book of value.

      About the Author:

      Robin Henderson studied Mathematics in Professor Alexander Aitken’s department at the University of Edinburgh. Professor Aitken developed the matrix formulation of linear regression models that is employed in statistical software packages such as MINITAB1. Following graduation, the author trained as a secondary school teacher and began his career in education at Boroughmuir School, Edinburgh.
      Since 2001, Robin has been operating as a sole consultant, trading as Halcro Consultancy, Loanhead, providing training and consultancy in statistics for quality improvement and Six Sigma. He has assisted Colin Barr Associates with the training of three groups of Six Sigma Black Belts, some participants being from nonmanufacturing organizations. With the Scottish Advanced Manufacturing Centre he has provided training and consultancy in statistical methods for quality improvement to two major companies.
      He is also currently employed as Coordinator at the Royal Infirmary of Edinburgh for the Scottish National Stroke Audit. On this project he has introduced the use of Shewhart control charts for monitoring aspects of the process of stroke care. Membership of the Committee of the Quality Improvement Section of the Royal Statistical Society, of which he is a Fellow, is a role that the author finds stimulating and enjoyable. He is also a member of ENBIS, the European Network for Business and Industrial Statistics.

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