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Process Optimization - Enrique Del Castillo
Livre non disponible
(*)
Enrique Del Castillo:

Process Optimization - nouveau livre

2007, ISBN: 9780387714349

ID: 602861130

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; * Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches; * 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; * 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; * 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; * Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization; * Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods; * Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods; * Includes an introduction to Kriging methods and experimental design for computer experiments; * Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results. This is an ideal textbook for students of experimental optimization techniques used in industrial production processes. It presents a detailed treatment of Bayesian Optimization approaches and it contains a mix of technical and practical sections. Bücher > Fremdsprachige Bücher > Englische Bücher gebundene Ausgabe 06.08.2007 Buch (fremdspr.), Springer, .200

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Process Optimization - Enrique Del Castillo
Livre non disponible
(*)

Enrique Del Castillo:

Process Optimization - nouveau livre

2007, ISBN: 9780387714349

ID: 215485609

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; * Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches; * 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; * 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; * 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; * Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization; * Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods; * Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods; * Includes an introduction to Kriging methods and experimental design for computer experiments; * Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results. This is an ideal textbook for students of experimental optimization techniques used in industrial production processes. It presents a detailed treatment of Bayesian Optimization approaches and it contains a mix of technical and practical sections. Bücher > Fremdsprachige Bücher > Englische Bücher gebundene Ausgabe 06.08.2007, Springer, .200

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Process Optimization - Enrique Del Castillo
Livre non disponible
(*)
Enrique Del Castillo:
Process Optimization - nouveau livre

ISBN: 9780387714349

ID: 51291b7c894ef47f4eccdc50799b7848

This is an ideal textbook for students of experimental optimization techniques used in industrial production processes. It presents a detailed treatment of Bayesian Optimization approaches and it contains a mix of technical and practical sections. 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; * Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches; * 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; * 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; * 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; * Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization; * Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods; * Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods; * Includes an introduction to Kriging methods and experimental design for computer experiments; * Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-387-71434-9, Springer

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Process Optimization - Enrique Del Castillo
Livre non disponible
(*)
Enrique Del Castillo:
Process Optimization - nouveau livre

ISBN: 9780387714349

ID: 672385824

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; * Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches; * 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; * 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; * 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; * Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization; * Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods; * Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods; * Includes an introduction to Kriging methods and experimental design for computer experiments; * Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results. This is an ideal textbook for students of experimental optimization techniques used in industrial production processes. It presents a detailed treatment of Bayesian Optimization approaches and it contains a mix of technical and practical sections. Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, Springer

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Process Optimization - Enrique del Castillo
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Enrique del Castillo:
Process Optimization - edition reliée, livre de poche

2007, ISBN: 9780387714349

ID: 7880233

Hardcover, Buch, [PU: Springer-Verlag New York Inc.]

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Détails sur le livre
Process Optimization
Auteur:

del Castillo, Enrique

Titre:

Process Optimization

ISBN:

0387714340

This book covers several bases at once. It is useful as a textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it 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.

Informations détaillées sur le livre - Process Optimization


EAN (ISBN-13): 9780387714349
ISBN (ISBN-10): 0387714340
Version reliée
Livre de poche
Date de parution: 2007
Editeur: Springer-Verlag GmbH
462 Pages
Poids: 0,798 kg
Langue: eng/Englisch

Livre dans la base de données depuis 05.07.2007 14:37:06
Livre trouvé récemment le 04.02.2017 22:44:22
ISBN/EAN: 0387714340

ISBN - Autres types d'écriture:
0-387-71434-0, 978-0-387-71434-9

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