Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems

Citation

(2009), "Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems", Assembly Automation, Vol. 29 No. 2. https://doi.org/10.1108/aa.2009.03329bae.001

Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems

Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems

Article Type: Book review From: Assembly Automation, Volume 29, Issue 2

Gareth J. Monkman, Stefan Hesse, Ralf Steinmann and Henrik Schunk,Springer,2006,Price: $94.00,529 pp.,ISBN: 978-1-85233-955-5

Overview

The book is focused on the statistical tools used within six sigma and provides an overview of the define, measure, analyse, improve, and control (DMAIC) phases of the six sigma methodology, followed by a detailed exploration of how and when to apply each method, backed up with many examples and exercises to build the readers understanding and confidence with the methods.

Who would find the book useful

The book is aimed at university students and has an academic style; the book is also useful for experienced users of six sigma who are interested in a deeper exploration of design of experiment techniques, or simply as a reference to refresh understanding of statistical techniques.

Strengths

The statistical tools are presented to the reader step-by-step with simple examples to illustrate the use of the tools, and the application of the DMAIC project phases, followed up with formal exercises to enable the reader to develop a deeper understanding of the techniques and their application. In particular, the book presents a good overview of control charting and DOE techniques and when to apply them with a summary of the techniques’ strengths and weaknesses.

Weaknesses

The main weakness of the book is that the exercise and examples are mainly from manufacturing applications or student projects, and there is very little coverage of examples from the service industry where six sigma techniques are having significant impact.

Furthermore, the book only presents a few of the many non-statistical tools used in six sigma projects, which form a very significant role in most six sigma projects; in particular the team building, change management, and lateral thinking techniques, which are absolutely necessary to ensure successful projects.

Overall, the book is a good reference text for the statistical techniques used in six sigma projects; however, due to its academic style, it is a very dry read, and the excitement of the application and power of six sigma does not always come across.

Nigel EdmondsonProcess Excellence Master Black Belt, Maersk Line