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Design and Analysis of Experiments
By Douglas C. Montgomery
* Publisher: Wiley
* Number Of Pages: 660
* Publication Date: 2004-12-21
* ISBN / ASIN: 047148735X
By Douglas C. Montgomery
* Publisher: Wiley
* Number Of Pages: 660
* Publication Date: 2004-12-21
* ISBN / ASIN: 047148735X
Book Description:
Now in its 6th edition, this bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments.
Douglas Montgomery arms readers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. He shows how to use statistically designed experiments to obtain information for characterization and optimization of systems, improve manufacturing processes, and design and develop new processes and products. You will also learn how to evaluate material alternatives in product design, improve the field performance, reliability, and manufacturing aspects of products, and conduct experiments effectively and efficiently.
Discover how to improve the quality and efficiency of working systems with this highly-acclaimed book. This 6th Edition:
* Places a strong focus on the use of the computer, providing output from two software products: Minitab and DesignExpert.
* Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects.
* Includes detailed discussions on how computers are currently used in the analysis and design of experiments.
* Offers new material on a number of important topics, including follow-up experimentation and split-plot design.
* Focuses even more sharply on factorial and fractional factorial design
* Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects.
* Includes detailed discussions on how computers are currently used in the analysis and design of experiments.
* Offers new material on a number of important topics, including follow-up experimentation and split-plot design.
* Focuses even more sharply on factorial and fractional factorial design
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