Understanding Industrial Designed Experiments

I enjoyed doing the DOE examples using the DOE software that came with the book. I also liked the real world case studies on applying DOE.

Using simulation, application and some mathematics, this is a balanced book for basics and intermediate. A nice book for starters to build strong foundation in DOE.

This by far is one of the better books on the subject. The material is explained in an easy to understand format, and you do not need to be a statistician (or an aspiring one), although some basic knowledge on statistics would help. The authors have stayed away from biases (as is the case with some other authors who have published books on DOE), and used a combo approach. This makes so much sense. Few know that DOEs are one of the key reasons for the success of Japanese products. It is high time companies woke up and took this matter seriously. I can say from first hand experience that many processes that were considered "Not do-able" were made possible because of DOE applications. This I was able to do across many companies and many industries. I use this book frequently as a reference, and also when I am teaching the subject. If you are a serious student of DOE, you may also want to read the book by Box and Hunter.

This text is the first to successfully blend Taguchi and Classical techniques of Experimental Design into a new and powerful approach that is proven to yield high return on investment in the industrial arena. It incorporates traditional topics along with creative ways to implement and communicate statistics without mathematical complexity. Topics include: Full and Fractional Factorials, Plackett-Burman, Taguchi, Box-Behnken, CCD, and Robust Designs; Rules of Thumb for Design Selection, Sample Size, Analysis, and Tests for Confirmation. There are 279 pages of case studies from a variety of industries. The first two chapters (125 pages) are an excellent overview with emphasis on proper planning, variance reduction, modeling, and statistical simplicity. Subsequent chapters provide more depth on design types such as objectives and advantages/disadvantages. Analysis strategies include simple graphs, normal probability plots, ANOVA, regression, and response surface methods aimed at optimizing the average response and minimizing variation. Contents Include: Foundations and Motivation Conducting Simple Experimental Designs and Analysis Design Types Statistical Techniques (ANOVA and Regression) Design Evaluation (graphically and statistically) Variance Reduction and Robustness Taguchi Philosophy, Design, and Analysis Optimization and Response Surface Methods Case Studies Rules of Thumb

If you don't want to get your Ph.D. in statistics but you still want to benefit from the power of designed experiments then this book has it. The accompanying software "DOE Keeping it simple statistically" also makes learning easy and fun.