Dynamic monitoring of polynomial profiles with attribute responses and between-profile correlation

Abstract

Profile monitoring is a popular statistical process control problem in recent years. In many applications, quality characteristics of interest are attribute data due to the inherent feature of processes or limitation of data collection costs. The correlation among data is becoming more significant, since data collection intervals are becoming shorter in the big data era. However, research on monitoring profiles with attribute responses in the presence of Between-Profile Correlation (BPC) has received relatively scant attention. Motivated by a real example of automobile warranty claims, this article aims to monitor polynomial profiles with attribute responses and BPC. The generalized polynomial model and the learning curve model are adopted to characterize the profile relationship and the correlation between profiles, respectively. Then, an EWMA chart with dynamic control limits (dEWMA) is developed. Simulation studies show that ignoring the BPC does not affect the in-control performance of the chart with dynamic control limits, but does have devastating effects on the out-of-control performance. The proposed dEWMA chart can address the impact of correlation and provide superior monitoring performance compared with some competitors. Finally, a real example of warranty claims data is presented to illustrate the implementation of the proposed chart.

Keywords:

• Attribute data
• between-profile correlation
• dynamic control limits
• polynomial profiles
• profile monitoring
• warranty claims data

Acknowledgments

The authors are grateful to the numerous valuable comments provided by the editor, the department editor, the associate editor, and two referees that have resulted in great improvements of this article.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Shuguang He, upon reasonable request.

Additional information

Funding

This work was supported by the Research Foundation of North China University of Technology, the National Natural Science Foundation of China [grant numbers 72032005, 71902138, 71872123, 72231005], and the Humanity and Social Science Youth Foundation of the Ministry of Education of China [grant number 19YJC630181].

Notes on contributors

Lisha Song

Lisha Song is an assistant professor in the College of Science, North China University of Technology, China. She received her PhD degree in business administration from Tianjin University, China. She received her M.S. degree in statistics from Nanjing Normal University, China. Her research interests include statistical process control and profile monitoring.

Shuguang He

Shuguang He is a professor in the College of Management and Economics, Tianjin University, China. He received his PhD degree in management science and engineering from Tianjin University, China. His research interests focus on quality management, warranty data analysis, and statistical quality control. He has published more than 50 papers in research journals, such as Journal of Quality Technology, Reliability Engineering & System Safety, International Journal of Production Economics, International Journal of Production Research, Annals of Operations Research, and Journal of Intelligent Manufacturing.

Zhiqiong Wang

Zhiqiong Wang is an associate professor of the School of Management at the Tianjin University of Technology, China. He received his PhD degree in management science and engineering from Tianjin University, China. His major research interests include quality control and management, statistical process control, and change-point detection.

Zhen He

Zhen He is a professor in the College of Management and Economics, Tianjin University, China. He is the head of the Department of Industrial Engineering at Tianjin University. He is the recipient of the Outstanding Research Young Scholar Award of the National Natural Science Foundation of China. He is an Academician of the International Academy for Quality (IAQ). He serves as the Area Editor of Computers & Industrial Engineering. So far, he has published over 100 research papers in refereed journals. His current research interests include quality management and engineering, reliability analysis, design of experiments, and six sigma management.