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Process Optimization

A Statistical Approach

  • Textbook
  • © 2007

Overview

  • A much stronger treatment of the topic than the Wiley books published in this area for these reasons: (1) on the strength of the book’s author and (2) on its coverage and treatment of process optimization
  • Provides in the form of a text a contemporary account not only of the classical techniques and tools used in Design of Experiments (DOE) and Response Surface Methods (RSM), but also to present more advanced process optimization techniques from the recent literature which has not been used that much in industrial practice
  • Contains a mix of technical and practical sections, appropriate for a first year graduate text in the subject or useful for self-study or reference
  • Includes supplementary material: sn.pub/extras

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 105)

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Table of contents (18 chapters)

  1. Preliminaries

  2. Statistical Inference in Process Optimization

  3. Robust Parameter Design and Robust Optimization

  4. Bayesian Approaches in Process Optimization

  5. Introduction to Optimization of Simulation and Computer Models

Keywords

About this book

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.

Authors and Affiliations

  • Pennsylvania State University, USA

    Enrique Del Castillo

Bibliographic Information

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