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Statistical Analysis of Profile Monitoring
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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,
Harvey Goldstein, Iain M. Johnstone, Geert Molenberghs, David W. Scott,
Adrian F. M. Smith, Ruey S. Tsay, Sanford Weisberg
Editors Emeriti: Vic Barnett, J. Stuart Hunter, Joseph B. Kadane, Jozef L. Teugels
A complete list of the titles in this series appears at the end of this volume.
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Statistical Analysis of
Profile Monitoring
RASSOUL NOOROSSANA
Industrial Engineering Department
Iran University of Science and Technology
Tehran, Iran
ABBAS SAGHAEI
Industrial Engineering Department
Islamic Azad University – Science and Research Branch
Tehran, Iran
AMIRHOSSEIN AMIRI
Industrial Engineering Department
Shahed University
Tehran, Iran
A JOHN WILEY & SONS, INC., PUBLICATION
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Library of Congress Cataloging-in-Publication Data
Noorossana, Rassoul, 1959–
Statistical analysis of profile monitoring / Rassoul Noorossana, Abbas
Saghaei, Amirhossein Amiri.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-470-90322-3 (cloth)
1. Process control–Statistical methods.
2. Quality control–Statistical methods.
1972– II. Amiri, Amirhossein, 1979– III. Title.
TS156.8.N656 2011
658.5–dc22
I. Saghaei, Abbas,
2011002197
Printed in Singapore
oBook ISBN: 9781118071984
ePDF ISBN: 9781118071960
ePub ISBN: 9781118071977
10
9 8 7 6 5 4 3 2 1
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Contents
Preface
Contributors
1
Introduction to Profile Monitoring
Introduction, 1
1.1 Functional Relationships Qualified as Profiles, 6
1.2 Functional Relationships not Qualified as Profiles, 13
1.3 Structure of This Book, 15
References, 19
2 Simple Linear Profiles
Introduction, 21
2.1 Phase I Simple Linear Profile, 22
2.2 Phase II Simple Linear Profile, 53
2.3 Special Cases and an Important Application, 74
2.4 Diagnostic Statistics, 77
2.5 Violation of the Model Assumptions, 81
Appendix, 83
References, 89
3 Multiple Linear and Polynomial Profiles
Introduction, 93
3.1 Monitoring Multiple Linear Profiles, 94
3.2 Monitoring Polynomial Profiles, 108
References, 116
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4 Binary Response Profiles
Introduction, 117
4.1 Model Setting and Parameter Estimation, 118
4.2 Phase I Control, 120
4.3 Phase II Monitoring, 122
4.4 Applications, 123
4.5 Conclusions, 126
References, 128
5 Parametric Nonlinear Profiles
Introduction, 129
5.1 Nonlinear Model Estimation, 130
5.2 Phase I Methods, 132
5.3 Phase II Methods, 142
5.4 Variance Profiles, 145
Appendix, 154
References, 155
6 Nonparametric Nonlinear Profiles
Introduction, 157
6.1 Model Formulation and Nonparametric Example, 159
6.2 Splines, 162
6.3 Component Analysis, 170
6.4 Wavelets, 174
References, 187
7 Multivariate Linear Profiles Monitoring
Introduction, 189
7.1 Monitoring Multivariate Simple Linear Profiles, 190
7.2 Monitoring Multivariate Multiple Linear Profiles, 204
References, 216
CONTENTS
117
129
157
189
8 Statistical Process Control for Geometric Specifications
217
Introduction, 217
8.1 Examples of Geometric Feature Concerning Circularity, 221
8.2 Control Charts for Profile Monitoring, 224
8.3 Simple Approaches for Monitoring Manufactured Profiles: The
Industrial Practice, 233
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CONTENTS
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8.4 Performance Comparison, 237
8.5 Moving from 2D Profiles to 3D Surfaces, 245
8.6 Concluding Remarks, 249
Acknowledgments, 250
References, 250
9 Correlation and Autocorrelation in Profiles
253
Introduction, 253
9.1 Methods for WPA for Linear Models, 255
9.2 Methods for BPC for Linear Models, 257
9.3 Methods for WPA and BPC for Other (Nonlinear) Models, 258
9.4 Phase I Analysis, 259
9.5 Phase II Analysis, 262
9.6 Related Issues: Rational Subgrouping and Random Effects, 263
9.7 Discussion and Open Questions, 266
Acknowledgment, 267
References, 267
10 Nonparametric Profile Monitoring
269
Introduction, 269
10.1 Monitoring Profiles Based on Nonparametric Regression, 270
10.2 Nonparametric Profile Monitoring Using Change-Point
Formulation and Adaptive Smoothing, 281
10.3 Nonparametric Profile Monitoring by Mixed-Effects Modeling, 288
Appendix A: Approximate the Distributions of Quadratic Forms
Like zT Az, 299
Appendix B: The Expression of lrt,k in Model (10.8), 300
References, 301
Index
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Preface
The aim of this book is to summarize major achievements in statistical profile moni-
toring methods. Statistical profile monitoring can be considered as a potential subarea
of statistical quality control that has recently attracted attention of many researchers
and practitioners. One major reason behind this attractiveness is the wide range of
applications that one can identify for the concept of profile monitoring in different
service and manufacturing settings. It should not be too long before the concept,
methods, and issues related to statistical profile monitoring and its related analy-
ses are introduced in different engineering and statistical textbooks and software
packages.
It is well known that, in standard statistical process control applications, one is
traditionally concerned with monitoring performance of a process or product using
measurements on a single quality characteristic or a vector of quality characteristics
at a given time or space. However, in many applications of statistical process control,
quality of a process or product is best characterized and summarized by a functional
relationship. In the literature of profile monitoring, this functional relationship is
usually referred to as profile, signature, or waveform. Fortunately, advances in tech-
nology have made it possible for process or statistical engineers and practitioners
to collect a large number of process or product measurements to reconstruct this
functional relationship with the aim of understanding and evaluating its stability over
time using statistical methods.
This book addresses the fundamental concepts, methods, and issues related to
statistical profile monitoring. The book begins with an introduction to the concept of
profile monitoring and its applications in practice, and then throughout the remain-
ing nine chapters, issues related to simple linear profiles, complex nonlinear pro-
files, and roundness profiles or profiles associated with geometric specifications are
discussed.
This book can be used as a major reference or textbook for researchers, engineers,
and statisticians who are interested in advanced topics in statistical process control. In
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