Stock photo: cover may vary
Process Optimization: A Statistical Approach Paperback - 2007
by Enrique del Castillo
- New
- Paperback
A$133.00
A$48.23
Delivery to USA
Standard delivery: 7 to 14 days
More delivery options
Standard delivery: 7 to 14 days
Ships from Revaluation Books (Devon, United Kingdom)
Details
- Title Process Optimization: A Statistical Approach
- Author Enrique del Castillo
- Binding Paperback
- Edition Softcover reprin
- Condition New
- Pages 462
- Volumes 1
- Language ENG
- Publisher Springer US
- Publication date 2007
- Bookseller's Inventory # x-144194396X
- ISBN 9781441943965 / 144194396X
- Weight 1.48 lbs (0.67 kg)
- Dimensions 9.21 x 6.14 x 0.97 in (23.39 x 15.60 x 2.46 cm)
- Category Technology & Industrial Arts
- Dewey Decimal Code 620
- Quantity available 2
About Revaluation Books Devon, United Kingdom
Biblio member since 2020
General bookseller of both fiction and non-fiction.
Reader reviews for Process Optimization: A Statistical Approach
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the publisher
From the rear cover
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.
