Robust Engineering: Learn How to Boost Quality While Reducing Costs & Time to Market

by Genichi Taguchi, Subir Chowdhury, Shin Taguchi

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Powerful and elegantly simple. Achieve higher quality...lower costs...faster time to market Companies worldwide have used the methods of quality expert Genichi Taguchi for the past 30 years with phenomenal product development cost savings and quality improvements. Robust Engineering, by this three-time Deming Prize winner, along with Subir Chowdhury and Shin Taguchi, is the first book to explain and illustrate his newest, most revolutionary methodology, Technology Development. It joins Design of Experiments and Robust Design as the framework on which your company can build a competitive edge. Case studies of real-world organizations Ford, ITT, 3M, Minolta, NASA, Nissan, Xerox and 9 others show you how the techniques of all three methodologies can besuccessfully applied. You'll hammer flexibility into your manufacturing organization to minimize product development costs, reduce product time-to-market, and fully satisfy customers needs.

255 pages, Hardcover

First published October 18, 1999

Reviews

[Alan · Rating 3 out of 5]

Three for me, simply because it was light on the Taguchi Methods, and heavy on the case studies of experiments. I'd have given it more stars if the case studies had been more about the use of the method and the thought processes. If I worked in manufacturing and engineering this would have been a five star book. The case studies all started to look the same to me towards the end, which brought home the uniformity of techniques in the Taguchi method and I will certainly interpret the notion of signal to noise for my work and it was a good reminder on experimental design.

My basic notes:

* Orthogonal Array
* Maximise Signal to noise ration
* "What information is generated ignorer to accomplish superior product/process design and meet all requirements at once?"
* “What should be measured as data in order to generate the best information?"
* “How should the experimentation be designed?"
* “How should the data be analysed?"
* “How is the validity of a result confirmed?"
* “How are these methods implemented?"

Other reading:
* https://en.wikipedia.org/wiki/Taguchi...
* https://www.isixsigma.com/methodology...
* https://www.researchgate.net/publicat...