Robust Design for Quality Engineering and Six Sigma

Citation

Yao, Y. (2010), "Robust Design for Quality Engineering and Six Sigma", Assembly Automation, Vol. 30 No. 1. https://doi.org/10.1108/aa.2010.03330aae.001

Robust Design for Quality Engineering and Six Sigma

Robust Design for Quality Engineering and Six Sigma

Article Type: Book review From: Assembly Automation, Volume 30, Issue 1

Sung H. Park and Jiju Antony,World Scientific,September 2008,$104.00,560 pp.,ISBN: 9789812778673,www.worldscibooks.com/engineering/6655.html,

The book entitled Robust Design for Quality Engineering and Six Sigma consists of 14 chapters, nine appendixes, a reference list, and an index list. As a start, Chapter 1 introduces the concepts and Taguchi's robust design principles for quality engineering. In Chapter 2, the tools and procedures for quality analysis and quality problem-solving are systematically expatiated. After that, the authors set forth the methodologies of experiment design in quality engineering in Chapters 3 and 4. From Chapters 5 to 8, parameter design methods and procedures for continuous process and discrete process are introduced clearly. Chapter 9 tells readers the methods for tolerance design. Robust response surface design and analysis, the concept of Six Sigma and its application in quality management, and robust design and implementation of Six Sigma, are expounded in Chapters 10-14. To clarify the above-mentioned concepts, tools, procedures and knowledge, the authors give plenty of figures, data tables, examples, and case studies.

The book is well organized and delivered in a way easy for readers to understand. I am very impressed with the logicality and the forthright expression that the authors used in writing the book. The reasons I like this book are that it combines classical experimental design methods with those of Taguchi's robust designs, demonstrating their prowess in DFSS and suggesting new directions for the development of statistical design and analysis; and, that it bridges the gap between quality engineering and Six Sigma through value creation effort by the robust design methodology. Almost all the mathematical equations are deduced from the original concept in a succinct and pellucid way. The examples and case studies taken from manufacturing disciplines make the readers want to read the book and the knowledge is easily grasped. Through reading the book, I can feel that the authors have a very solid base and ample experiences in quality engineering and quality management. I consider this book to be among the few best books I have ever read in this area.

I believe engineers and researchers who have some knowledge and experience in quality engineering and have the need to use statistical robust design for quality engineering and Six Sigma, and for statisticians who wish to know about the wide range of applications of experimental design in industry, will like this book as much as I do, because they will benefit from this book, as well as enhance their knowledge about quality control, quality management, and continuous quality improvements. The book is also valuable for some students, managers, and professionals interested in Taguchi's robust design methods, as well as the implementation of Six Sigma. However, for those who lack some basic knowledge and experience in quality engineering before reading this book, may find it dull and unattractive as background requirements are seldom introduced, and the description of the content is not so tightly close to the real production process.

Yingxue YaoSchool of Mechanical and Electrical Engineering, Harbin Institute of Technology, Harbin, China