Free PDF Statistical Quality Design and Control (2nd Edition), by Richard E. DeVor, Tsong-how Chang, John W. Sutherland
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Statistical Quality Design and Control (2nd Edition), by Richard E. DeVor, Tsong-how Chang, John W. Sutherland
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Features a blend of statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement. The book places particularly strong emphasis on proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement.
- Sales Rank: #643252 in Books
- Brand: Devor, Richard E./ Chang, Tsong-How/ Sutherland, John W.
- Published on: 2006-08-04
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 2.10" w x 6.80" l, 2.80 pounds
- Binding: Paperback
- 960 pages
- textbook about quality control and design
Most helpful customer reviews
2 of 2 people found the following review helpful.
Best book I've seen explaining statistical concepts & design of experiments
By amazipinions
I feel sorry that many people who want to learn statistical concepts and design of experiments will not look for this book, since it feels like an engineering book. In reality, chapters 3, 4, and part III of this book teaches these concepts very gently and with easy to follow examples. I wish the writers write books on other statistical techniques as well.
This book is probably already well-known for teaching statistical quality control techniques.
1 of 1 people found the following review helpful.
Great book
By Raed
all you need and more to learn about quality control. its amazing book, well written and takes you by hand and introduce to real life examples
0 of 0 people found the following review helpful.
Very clear text with excellent examples.
By TFM3
This book starts with a fascinating history of statistical process control (SPC). Then it moves along nicely through process measurement and control, and finishes with a fine treatment of design of experiments (DOE). It assumes a rudimentary understanding of statistics.
I felt that the book's strongest point was its use of real-world examples. In addition to giving a context to the material, it also provided a way to walk one through the calculations and results. Finally, the analysis of the results had meaning, and allowed the authors to show which parameters were important to the process, and which could be ignored.
Finally, this was a very good read. At no point during the 900+ pages did I think, "when will this ever end". I can't remember the last time I felt that way about what is essentially a textbook.
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