Response Surface Methodology E-Book

Raymond H. Myers

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Veröffentlichungsjahr: 2016

Beschreibung

Praise for the Third Edition:

“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.”

- Zentralblatt Math

Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM.

With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes:

• Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses
• Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error
• Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout
• An extensive references section to help readers stay up-to-date with leading research in the field of RSM

An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.

Leseprobe

WILEY SERIES IN PROBABILITY AND STATISTICS

Established by WALTER A. SHEWHART and SAMUEL S. WILKS

Editors: David J. Balding, Noel A. C. Cressie, Garrett M. Fitzmaurice, Geof H. Givens, Harvey Goldstein, Geert Molenberghs, David W. Scott, Adrian F. M. Smith, Ruey S. Tsay, Sanford Weisberg

Editors Emeriti: J. Stuart Hunter, Iain M. Johnstone, Joseph B. Kadane, Jozef L. Teugels

A complete list of the titles in this series appears at the end of this volume.

RESPONSE SURFACE METHODOLOGY

Process and Product Optimization Using Designed Experiments

Fourth Edition

RAYMOND H. MYERS

Virginia Polytechnic University, Department of Statistics, Blacksburg, VA

DOUGLAS C. MONTGOMERY

Arizona State University, Department of Industrial Engineering, Tempe, AZ

CHRISTINE M. ANDERSON-COOK

Los Alamos National Laboratory, Los Alamos, NM

Copyright © 2016 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, [phone], fax [phone], or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, [phone], fax [phone], or online at http://www.wiley.com/go/permission.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at [phone], outside the United States at [phone] or fax [phone].

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic format. For more information about Wiley products, visit our web site at www.wiley.com.

Library of Congress Cataloging-in-Publication Data:

Myers, Raymond H. Response surface methodology : process and product optimization using designed experiments.  – 4th ed. / Raymond H. Myers, Douglas C. Montgomery, Christine M. Anderson-Cook.   p. cm. – (Wiley series in probability and statistics)  Includes bibliographical references and index.  ISBN 978-1-118-91601-8 (cloth)  1. Experimental design. 2. Response surfaces (Statistics). I. Montgomery, Douglas C.  II. Anderson-Cook, Christine M. III. Title.  QA279.M94 2016  519.507–dc22

2016019012

CONTENTS

Preface

Chapter 1: Introduction

1.1 Response Surface Methodology

1.2 Product Design and Formulation (Mixture Problems)

1.3 Robust Design and Process Robustness Studies

1.4 Useful References on RSM

Chapter 2: Building Empirical Models

2.1 Linear Regression Models

2.2 Estimation of the Parameters in Linear Regression Models

2.3 Properties of the Least Squares Estimators and Estimation of σ 

2

2.4 Hypothesis Testing in Multiple Regression

2.5 Confidence Intervals in Multiple Regression

2.6 Prediction of New Response Observations

2.7 Model Adequacy Checking

2.8 Fitting a Second-Order Model

2.9 Qualitative Regressor Variables

2.10 Transformation of the Response Variable

Exercises

Short Answer Questions

Note

Chapter 3: Two-Level Factorial Designs

3.1 Introduction

3.2 The 2

2

Design

3.3 The 2

3

Design

3.4 The General 2

k

Design

3.5 A Single Replicate of the 2

k

Design

3.6 2

k

Designs are Optimal Designs

3.7 The Addition of Center Points to the 2

k

Design

3.8 Blocking in the 2

k

Factorial Design

3.9 Split-Plot Designs

Exercises

Short Answer Questions

Chapter 4: Two-Level Fractional Factorial Designs

4.1 Introduction

4.2 The One-Half Fraction of the 2

k

Design

4.3 The One-Quarter Fraction of the 2

k

Design

4.4 The General 2

k

−

p

Fractional Factorial Design

4.5 Resolution III Designs

4.6 Resolution IV and V Designs

4.7 Alias Structures in Fractional Factorial and Other Designs

4.8 Nonregular Fractional Factorial Designs

4.9 Fractional Factorial Split-Plot Designs

4.10 Summary

Exercises

Short Answer Questions

Chapter 5: Process Improvement with Steepest Ascent

5.1 Determining the Path of Steepest Ascent

5.2 Consideration of Interaction and Curvature

5.3 Effect of Scale (Choosing Range of Factors)

5.4 Confidence Region for Direction of Steepest Ascent

5.5 Steepest Ascent Subject to a Linear Constraint

5.6 Steepest Ascent in a Split-Plot Experiment

Exercises

Short Answer Questions

Chapter 6: The Analysis of Second-Order Response Surfaces

6.1 Second-Order Response Surface

6.2 Second-Order Approximating Function

6.3 A Formal Analytical Approach to the Second-Order Model

6.4 Ridge Analysis of the Response Surface

6.5 Sampling Properties of Response Surface Results

6.6 Further Comments Concerning Response Surface Analysis

Exercises

Short Answer Questions

Chapter 7: Multiple Response Optimization

7.1 Balancing Multiple Objectives

7.2 Strategies for Multiple Response Optimization

7.3 A Sequential Process for Optimization—DMRCS

7.4 Incorporating Uncertainty of Response Predictions into Optimization

Exercises

Short Answer Questions

Chapter 8: Design of Experiments for Fitting Response Surfaces—I

8.1 Desirable Properties of Response Surface Designs

8.2 Operability Region, Region of Interest, and Metrics for Desirable Properties

8.3 Design of Experiments for First-Order Models and First-Order Models with Interactions

8.4 Designs for Fitting Second-Order Models

Exercises

Short Answer Questions

Chapter 9: Experimental Designs for Fitting Response Surfaces—II

9.1 Designs that Require a Relatively Small Run Size

9.2 General Criteria for Constructing, Evaluating, and Comparing Designed Experiments

9.3 Computer-Generated Designs in RSM

9.4 Multiple Objective Computer-Generated Designs for RSM

9.5 Some Final Comments Concerning Design Optimality and Computer-Generated Design

Exercises

Short Answer Questions

Notes

Chapter 10: Advanced Topics in Response Surface Methodology

10.1 Effects of Model BIAS on the Fitted Model and Design

10.2 A Design Criterion Involving Bias and Variance

10.3 Errors in Control of Design Levels

10.4 Experiments with Computer Models

10.5 Minimum Bias Estimation of Response Surface Models

10.6 Neural Networks

10.7 Split-Plot Designs for Second-Order Models

10.8 RSM for Non-normal Responses—Generalized Linear Models

Exercises

Short Answer Questions

Chapter 11: Robust Parameter Design and Process Robustness Studies

11.1 Introduction

11.2 What is Parameter Design?

11.3 The Taguchi Approach

11.4 The response surface approach

11.5 Experimental Designs For RPD and Process Robustness Studies

11.6 Dispersion Effects in highly Fractionated Designs

Exercises

Short Answer Questions

Chapter 12: Experiments with Mixtures

12.1 Introduction

12.2 Simplex Designs and Canonical Mixture Polynomials

12.3 Response Trace Plots

12.4 Reparameterizing Canonical Mixture Models to Contain a Constant Term (β

0

)

Exercises

Short Answer Questions

Chapter 13: Other Mixture Design and Analysis Techniques

13.1 Constraints on the Component Proportions

13.2 Mixture Experiments Using Ratios of Components

13.3 Process Variables in Mixture Experiments

13.4 Screening Mixture Components

Exercises

Short Answer Questions

Appendix 1: Moment Matrix of a Rotatable Design

Appendix 2: Rotatability of a Second-Order Equiradial Design

References

Index

Wiley Series in Probability and Statistics

EULA

List of Tables

Chapter 2

Table 2.1

Table 2.2

Table 2.3

Table 2.4

Table 2.5

Table 2.6

Table 2.7

Table 2.8

Table 2.9

Table 2.10

Table 2.11

Table 2.12

Table 2.13

Table 2.14

Table 2.15

Table 2.16

Table E2.1

Table E2.2

Table E2.3

Table E2.4

Table E2.5

Chapter 3

Table 3.1

Table 3.2

Table 3.3

Table 3.4

Table 3.5

Table 3.6

Table 3.7

Table 3.8

Table 3.9

Table 3.10

Table 3.11

Table 3.12

Table 3.13

Table 3.14

Table 3.15

Table 3.16

Table 3.17

Table 3.18

Table 3.19

Table 3.20

Table 3.21

Table 3.22

Table 3.23

Table 3.24

Table 3.25

Table 3.26

Table 3.27

Table E3.1

Chapter 4

Table 4.1

Table 4.2

Table 4.3

Table 4.4

Table 4.5

Table 4.6

Table 4.7

Table 4.8

Table 4.9

Table 4.10

Table 4.11

Table 4.12

Table 4.13

Table 4.14

Table 4.15

Table 4.16

Table 4.17

Table 4.18

Table 4.19

Table 4.20

Table 4.21

Table 4.22

Table 4.23

Table 4.24

Table 4.25

Table 4.26

Table 4.27

Table 4.28

Table 4.29

Table 4.30

Table 4.31

Table 4.32

Table 4.33

Table 4.34

Table 4.35

Table 4.36

Table 4.37

Table 4.38

Table 4.39

Table 4.40

Table 4.41

Table 4.42

Table E4.1

Table E4.2

Table E4.3

Table E4.4

Table E4.5

Table E4.6

Table E4.7

Table E4.8

Chapter 5

Table 5.1

Table 5.2

Table 5.3

Table 5.4

Table 5.5

Table 5.6

Table 5.7

Table 5.8

Table 5.9

Table 5.10

Table 5.11

Table 5.12

Table 5.13

Table 5.14

Table E5.1

Table E5.2

Table E5.3

Table E5.4

Chapter 6

Table 6.1

Table 6.2

Table 6.3

Table 6.4

Table 6.5

Table 6.6

Table 6.7

Table E6.1

Table E6.2

Table E6.3

Table E6.4

Table E6.5

Table E6.6

Table E6.7

Table E6.8

Table E6.9

Table E6.10

Table E6.11

Table E6.12

Table E6.13

Table E6.14

Table E6.15

Chapter 7

Table 7.1

Table 7.2

Table 7.3

Table 7.4

Table 7.5

Table 7.6

Table 7.7

Table 7.8

Table E7.1

Table E7.2

Table E7.3

Table E7.4

Table E7.5

Table E7.6

Table E7.7

Chapter 8

Table 8.1

Table 8.2

Table 8.3

Table 8.4

Table 8.5

Table 8.6

Table 8.7

Table 8.8

Table 8.9

Table 8.10

Table E8.1

Table E8.2

Chapter 9

Table 9.1

Table 9.2

Table 9.3

Table 9.4

Table 9.5

Table 9.6

Table 9.7

Table 9.8

Table 9.9

Table E9.1

Table E9.2

Table E9.3

Table E9.4

Table E9.5

Chapter 10

Table 10.1

Table 10.2

Table 10.3

Table 10.4

Table 10.5

Table 10.6

Table 10.7

Table 10.8

Table 10.9

Table 10.10

Table 10.11

Table 10.12

Table 10.13

Table 10.14

Table 10.15

Table 10.16

Table 10.17

Table 10.18

Chapter 11

Table 11.1

Table 11.2

Table 11.3

Table 11.4

Table 11.5

Table 11.6

Table 11.7

Table 11.8

Table 11.9

Table 11.10

Table 11.11

Table 11.12

Table 11.13

Table 11.14

Table 11.15

Table E11.1

Table E11.2

Table E11.3

Chapter 12

Table 12.1

Table 12.2

Table 12.3

Table 12.4

Table 12.5

Table 12.6

Table 12.7

Table 12.8

Table E12.1

Table E12.2

Table E12.3

Table E12.4

Table E12.5

Chapter 13

Table 13.1

Table 13.2

Table 13.3

Table 13.4

Table 13.5

Table 13.6

Table 13.7

Table 13.8

Table 13.9

Table 13.10

Table 13.11

Table 13.12

Table 13.13

Table 13.14

Table 13.15

Table 13.16

Table 13.17

Table 13.18

Table 13.19

Table 13.20

Table 13.21

Table 13.22

Table 13.23

Table 13.24

Table E13.1