Customer Reviews

DOE Simplified: Practical Tools for Effective Experimentation (Quality Management)

5 star:		(4)
4 star:		(3)
3 star:		(3)
2 star:		(1)
1 star:		(0)

 

 

As a mechanical engineer (just beginning self study on the topic of DOE) I found this book very useful. The author provides practical insight that I was unable to find in other DOE or statistics books. This is not a book for advanced statisticians, however, it is a great book for someone trying to understand and apply the principles of DOE.

DOE Simplified is perhaps overly simplified. The author tries to pack ANOVA, factorial experimentation, use of blocking and fold overs, and response-surface methodology inside 200 pages. The attempt is admirable, but the book would be hard for a beginner to fully understand due to information gaps, especially on why the techniques work (at least on an intuitive level). The person who would benefit most is that person needing a refresher after a being away from DOE for some time.

The book is a very brief introduction to DOE. I had read other reviews that stated that it was only a very brief intro to DOE. My thoughts when purchasing the book was that would be what I needed since I had not previously worked with statistical experimental design. Having now gone more than half way through the book, I found that I could not follow the solutions without the aid of other more detailed statistical design of experiments texts. If you are truly a beginner, I suggest using this book while referring to Design & Analysis of Experiments by Douglas Montgomery. In this manner while using a book similar to Montgoemery's 5th or later edition as a reference, the "DOE Simplified" text serves as a pacer book to hurry you through an intro to DOE. It certainly helped me become much more interested in pursuing DOE and thus order a number of additional books of which Montgomery's was one of seven that I have recently purchased from Amazon. Although I am digressing, my rating of Montgoemry's 5th Edition is FANTASTIC!!!!! DOE Simplified.... good summary as long as you have reference material.

Being a beginner in the world of DOE (with minimal statistics training), this book was TRULY a godsend. Very easy to understand-- I feel I was able to get a nice grasp of the concepts I'd heard about so often before but could never quite nail down. I did a 2-day training at SAS on DOE and this little book blew that away. Lots of examples and practice problems to get some experience under my belt.

Some people are critical because they say it's "oversimplified"... but come on guys, read the title of the book! It is not for hardcore math guys. It is for novices and practical-minded folk who need to get a fast, easy intro.

Finished it in 2 easy afternoons and now I feel comfortable to move on to more detailed/ math oriented texts to learn all the nuances of DOE. Highly, highly recommended for novices. Looking forward to the other books written by these very talented authors!

Simplified is the key. This book offers a very basic approach to DOE. It's good for someone who wants a quick start in DOE.

Great book. Steps through basic stats in anticipation of use for DOEs. Good examples and well-written. Easy to recommend.

Received the book - however there was no cd as was stated. If this review is published, it is because there was no option to contact seller.

The book is fine, but the software included the main reason to buy the book.

Using of DOE is useful for metallurgical engineering.I use doe for design of alloys (based on requirments and metallurgical parameters)and control of metallurgical parameters for improvment of mechanical properties.I suggest this book for all engineers especially for metallurgical engineers (for control and improvment of heat tratment, casting, electropalting,and other process).
I use DOE in my PHD project for design of a new steel alloy.

I got this so I could get new ideas for teaching the basics of DOE to others. Though I don't have any trouble understanding the text, it didn't do what I had hoped. I'm sure it's simpler than really statistics intensive texts, but really simple, it just isn't.