Process Optimization A Statistical Approach
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- Engels
- Paperback
- 9781441943965
- 29 november 2010
- 484 pagina's
Samenvatting
PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "noisy" systems where the main emphasis is process optimization.
PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "noisy" systems where the main emphasis is process optimization. The book can also be used as a reference text by Industrial, Quality and Process Engineers and Applied Statisticians working in industry, in particular, in semiconductor/electronics manufacturing and in biotech manufacturing industries.
The major features of PROCESS OPTIMIZATION: A Statistical Approach are:
- It provides a complete exposition of mainstream experimental design techniques, including designs for first and second order models, response surface and optimal designs;
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- Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches;
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- Includes an extensive discussion of Robust Parameter Design (RPD) problems, including experimental design issues such as Split Plot designs and recent optimization approaches used for RPD;
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- Presents a detailed treatment of Bayesian Optimization approaches based on experimental data (including an introduction to Bayesian inference), including single and multiple response optimization and model robust optimization;
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- Provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization and more;
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- Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization;
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- Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods;
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- Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods;
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- Includes an introduction to Kriging methods and experimental design for computer experiments;
Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results.
Productspecificaties
Inhoud
- Taal
- en
- Bindwijze
- Paperback
- Oorspronkelijke releasedatum
- 29 november 2010
- Aantal pagina's
- 484
- Illustraties
- Nee
Betrokkenen
- Hoofdauteur
- Enrique Del Castillo
- Tweede Auteur
- Enrique Del Castillo
- Co Auteur
- Enrique Del Castillo
- Hoofduitgeverij
- Springer
Overige kenmerken
- Editie
- Softcover reprint of hardcover 1st ed. 2007
- Extra groot lettertype
- Nee
- Product breedte
- 155 mm
- Product lengte
- 235 mm
- Studieboek
- Nee
- Verpakking breedte
- 157 mm
- Verpakking hoogte
- 33 mm
- Verpakking lengte
- 238 mm
- Verpakkingsgewicht
- 710 g
EAN
- EAN
- 9781441943965
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