A one-of-a-kind presentation of the major achievements in
statistical profile monitoring methods



Statistical profile monitoring is an area of statistical quality
control that is growing in significance for researchers and
practitioners, specifically because of its range of applicability
across various service and manufacturing settings. Comprised of
contributions from renowned academicians and practitioners in the
field, Statistical Analysis of Profile Monitoring presents
the latest state-of-the-art research on the use of control charts
to monitor process and product quality profiles. The book presents
comprehensive coverage of profile monitoring definitions,
techniques, models, and application examples, particularly in
various areas of engineering and statistics.

The book begins with an introduction to the concept of profile
monitoring and its applications in practice. Subsequent chapters
explore the fundamental concepts, methods, and issues related to
statistical profile monitoring, with topics of coverage
including:

* Simple and multiple linear profiles

* Binary response profiles

* Parametric and nonparametric nonlinear profiles

* Multivariate linear profiles monitoring

* Statistical process control for geometric specifications

* Correlation and autocorrelation in profiles

* Nonparametric profile monitoring

Throughout the book, more than two dozen real-world case studies
highlight the discussed topics along with innovative examples and
applications of profile monitoring. Statistical Analysis of
Profile Monitoring is an excellent book for courses on
statistical quality control at the graduate level. It also serves
as a valuable reference for quality engineers, researchers and
anyone who works in monitoring and improving statistical
processes.

RASSOUL NOOROSSANA, PhD, is Professor of Industrial
Engineering at Iran University of Science and Technology. A
Certified Six Sigma Black Belt, he has published extensively in the
areas of statistical quality control, engineering statistics, total
quality management, and Six Sigma.

ABBAS SAGHAEI, PhD, is Associate Professor of Industrial
Engineering at Islamic Azad University, Iran. He currently focuses
his research in the areas of statistical process control, design of
experiments, and Six Sigma.

AMIRHOSSEIN AMIRI, PhD, is Assistant Professor of
Industrial Engineering at Shahed University, Iran. He has authored
numerous papers in the areas of statistical process control and
improvement, quality management and productivity, and design of
experiments.

Statistical profile monitoring is an area of statistical quality control that is growing in significance for researchers and practitioners, specifically because of its range of applicability across various service and manufacturing settings. Comprised of contributions from renowned academicians and practitioners in the field, Statistical Analysis of Profile Monitoring presents the latest state-of-the-art research on the use of control charts to monitor process and product quality profiles. The book presents comprehensive coverage of profile monitoring definitions, techniques, models, and application examples, particularly in various areas of engineering and statistics.

The book begins with an introduction to the concept of profile monitoring and its applications in practice. Subsequent chapters explore the fundamental concepts, methods, and issues related to statistical profile monitoring, with topics of coverage including:

• Simple and multiple linear profiles
• Binary response profiles
• Parametric and nonparametric nonlinear profiles
• Multivariate linear profiles monitoring
• Statistical process control for geometric specifications
• Correlation and autocorrelation in profiles
• Nonparametric profile monitoring

Throughout the book, more than two dozen real-world case studies highlight the discussed topics along with innovative examples and applications of profile monitoring. Statistical Analysis of Profile Monitoring is an excellent book for courses on statistical quality control at the graduate level. It also serves as a valuable reference for quality engineers, researchers and anyone who works in monitoring and improving statistical processes.

Contributors xi

1 Introduction to Profile Monitoring 1

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 21

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 93

Introduction, 93

3.1 Monitoring Multiple Linear Profiles, 94

3.2 Monitoring Polynomial Profiles, 108

References, 116

4 Binary Response Profiles 117

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 129

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 157

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 189

Introduction, 189

7.1 Monitoring Multivariate Simple Linear Profiles, 190

7.2 Monitoring Multivariate Multiple Linear Profiles, 204

References, 216

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

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