Response Surface Methodology: Process and Product Optimization Using Designed Experiments [NOOK Book]

Overview

Identifying an appropriate response surface model from experimental data requires knowledge of statistical experimental design fundamentals, regression modeling techniques, and elementary optimization methods. This book integrates these three topics into a comprehensive, state-of-the-art presentation of response surface methodology (RSM). This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of...
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Response Surface Methodology: Process and Product Optimization Using Designed Experiments

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Overview

Identifying an appropriate response surface model from experimental data requires knowledge of statistical experimental design fundamentals, regression modeling techniques, and elementary optimization methods. This book integrates these three topics into a comprehensive, state-of-the-art presentation of response surface methodology (RSM). This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM. Working with the most useful software packages, the authors bring an applied focus that emphasizes models useful in industry for product and process design and development.
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Editorial Reviews

Booknews
A practical guide to response surface methodology (RSM)--the process of identifying and fitting an appropriate response surface model from experimental data--for statisticians in fields including chemistry, engineering, quality control, computer science, industrial engineering, and the experimental sciences. While the opening chapter lays down the basic conceptual groundwork, the bulk of the volume is devoted to providing step-by-step guidance on the use of statistical and empirical modeling techniques that have proven their efficacy in industry. Numerous real-world examples illuminate critical points covered. Includes end-of-chapter problems. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From The Critics
A textbook for a graduate level course on the optimization of response surfaces under experiment. The authors describe two-level factorial and fractional factorial designs, the method of steepest ascent, second-order response surfaces, designs for fitting response surface models, and experiments that involve mixtures. The second edition uses Design Expert version 6 for much of the computing. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From the Publisher
“This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.Working with the most useful software packages, the authors bring an applied focus that emphasizes models useful in industry for product and process design and development.” (Zentralblatt Math, 1 October 2013)

"The third edition of a well-regarded text on response surface methodology. Christine M. Anderson-Cook, has been added … [bringing] an applied perspective to the material." (Mathematical Reviews, December 2009)

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Product Details

  • ISBN-13: 9781118210475
  • Publisher: Wiley
  • Publication date: 9/20/2011
  • Series: Wiley Series in Probability and Statistics , #705
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 3
  • Pages: 704
  • File size: 13 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Raymond H. Myers, PhD, is Professor Emeritus in the Department of Statistics at Virginia Polytechnic Institute and State University. He has over forty years of academic experience in the areas of experimental design and analysis, response surface analysis, and designs for nonlinear models. A Fellow of the American Statistical Society, Dr. Myers has authored or coauthored numerous journal articles and books, including Generalized Linear Models: With Applications in Engineering and the Sciences, also published by Wiley.

Douglas C. Montgomery, PhD, is Regents' Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery has over thirty years of academic and consulting experience and has devoted his research to engineering statistics, specifically the design and analysis of experiments. He has authored or coauthored numerous journal articles and twelve books, including Generalized Linear Models: With Applications in Engineering and the Sciences; Introduction to Linear Regression Analysis, Fourth Edition; and Introduction to Time Series Analysis and Forecasting, all published by Wiley.

Christine M. Anderson-Cook, PhD, is Project Leader a t the Los Alamos National Laboratory, New Mexico. Dr. Anderson-Cook has over ten years of academic and consulting experience and has written numerous journal articles on the topics of design of experiments and response surface methodology.

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Table of Contents

1 Introduction

2 Building Empirical Models

3 Two-Level Factorial Designs

4 Two-Level Fractional Factorial Designs

5 Process Improvement with Steepest Ascent

6 The Analysis of Second-Order Response Surfaces

7 Experimental Designs for Fitting Response Surfaces - I

8 Experimental Designs for Fitting Response Surfaces - II

9 Advanced Topics in Response Surface Methodology

10 Robust Parameter Design and Process Robustness Studies

11 Experiments with Mixtures

12 Other Mixture Design and Analysis Techniques

Appendix 1 Moment Matrix of a Rotatable Design

Appendix 2 Rotatability of a Second-Order Equiradial Design

Index

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