Optimal design of experiments : a case study approach / Peter Goos and Bradley Jones.
Material type: TextPublication details: Hoboken, N.J. : Wiley, 2011.Description: xiv, 287 p. : ill. ; 24 cmISBN:- 9780470744611 (hardback)
- 670.285 22
- T57.5 .G66 2011
- SCI028000
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Books | Prof. Ram Dayal Munda Central Library General Stacks | Physics | 670.285 GOO (Browse shelf(Opens below)) | Available | 70367 | ||
Books | Prof. Ram Dayal Munda Central Library General Stacks | Physics | 670.285 GOO (Browse shelf(Opens below)) | Available | 70366 |
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621.395 GAY Op-amps and linear integrated circuits / | 621.395 GAY Op-amps and linear integrated circuits / | 670.285 GOO Optimal design of experiments : | 670.285 GOO Optimal design of experiments : |
Includes bibliographical references (p. [277]-282) and index.
"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"-- Provided by publisher.
"This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples"-- Provided by publisher.
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