Quality Through Design: Experimental Design, Off-line Quality Control, and Taguchi's ContributionsFrom a review by P. D. T. O`Connor in the Journal of Quality and Reliability Engineering: `The authors clearly state their objectives, to explain the Taguchi methods, describing their advantages and disadvantages, and to describe extensions to the ideas, such as the use of simulations drivenby computer aided design, and response surface and other optimization methods. They seek to make friends among engineers whilst pleading for mercy from statisticians. In fact they do rather more, since the book covers the general principles of experimental design in some detail, thereby settingTaguchi's contribution in context. The result is a very good book, the best so far on the Taguchi phenomenon.'This important and acclaimed text is not available in paperback. This book describes the theoretical background to the techniques of experimental design and quality control that are now ssen of fundamental importance in the engineering and and process industries. The approach is two-fold; firstthe authors emphasise the importance of examples - mostly from the engineering industry - to illustrate the principles of Taguchi's methods. Secondly, they draw on methods available in statistics which together with the special Taguchi methodology and philosophy should form the backbone of apost-Taguchi methodology in off-line quality improvements.This paperback edition will be welcomed by the many students and teachers on undergraduate and graduate courses in design of experiments and quality control. |
Contents
Fundamentals of data analysis | 25 |
Designing experiments | 90 |
51 | 141 |
Copyright | |
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2-level factors A₁ analysis ANOVA Appendix assigned block breakdown voltages C₁ calculated case-study Chapter coefficients components considered contribution ratios controllable factors corresponding data values decibel degrees of freedom design of experiments dummy level engineering error sum error variance estimate example experiment experimental design experimental trials F-ratio factor levels factorial experiments fractional full-factorial function interaction columns interval Latin squares main effect matrix mean response method minimize missing values noise factors normal distribution number of observations number of replications obtained optimal optimum orthogonal array parameter design phosphor-type procedure quality control R₁ random variables regression represents residual response surface sample Section shown in Table significant Source df standard deviation statistical sum of squares Taguchi method target target-control factors technique tolerance transformation variation X₁ Y₁ Y₂