- Paperback: 960 pages
- Publisher: Prentice Hall; 2 edition (25 July 2006)
- Language English
- ISBN-10: 0130413445
- ISBN-13: 978-0130413444
- Product Dimensions: 23.8 x 18.2 x 3.8 cm
- Amazon Bestsellers Rank: 2,651,630 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Description
Product Description
Emphasizing proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement, this text blends statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement.
Importance is placed on both the philosophical/conceptual underpinnings and the techniques and methods of SPC and DOE. The concepts and methods of Taguchi for quality design are combined with more traditional experimental design methods to promote the importance of viewing quality from an engineering design perspective.
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3 reviews
2 of 2 people found the following review helpful
Best book I've seen explaining statistical concepts & design of experiments
19 Oct 2010
Format:Paperback|Amazon Verified Purchase
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.
This book is probably already well-known for teaching statistical quality control techniques.
1 of 1 people found the following review helpful
Great book
19 April 2011
Format:Paperback|Amazon Verified Purchase
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
Very clear text with excellent examples.
16 April 2012
Format:Paperback|Amazon Verified Purchase
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.
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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