Optimal design of experiments : a case study approach / / Peter Goos, Bradley Jones.
"This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variabili...
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Year of Publication: | 2011 |
Language: | English |
Online Access: | |
Physical Description: | xiv, 287 p. :; ill. |
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050 | 4 | |a T57.5 |b .G66 2011 | |
082 | 0 | 4 | |a 670.285 |2 22 |
100 | 1 | |a Goos, Peter. | |
245 | 1 | 0 | |a Optimal design of experiments |h [electronic resource] : |b a case study approach / |c Peter Goos, Bradley Jones. |
260 | |a Hoboken, N.J. : |b Wiley, |c 2011. | ||
300 | |a xiv, 287 p. : |b ill. | ||
504 | |a Includes bibliographical references and index. | ||
520 | |a "This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities?While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain. The structure of the book is organized around the following chapters: 1) Introduction explaining the concept of tailored DOE. 2) Basics of optimal design. 3) Nine case studies dealing with the above questions using the flow: description → design → analysis → optimization or engineering interpretation. 4) Summary. 5) Technical appendices for the mathematically curious"-- |c Provided by publisher. | ||
520 | |a "This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples"-- |c Provided by publisher. | ||
533 | |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
650 | 0 | |a Industrial engineering |x Experiments |x Computer-aided design. | |
650 | 0 | |a Experimental design |x Data processing. | |
650 | 0 | |a Industrial engineering |v Case studies. | |
655 | 4 | |a Electronic books. | |
700 | 1 | |a Jones, Bradley. | |
710 | 2 | |a ProQuest (Firm) | |
856 | 4 | 0 | |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=697607 |z Click to View |