A nonparametric CUSUM scheme for monitoring multivariate time-between-events-and-amplitude data with application to automobile painting

Abstract

Monitoring time-between-events-and-amplitude (TBEA) data, including the time interval between two successive nonconforming events and the amplitude of an event, is significant in many applications, especially manufacturing and service operations. Almost all TBEA control charts consider only one quality characteristic of the event, and most of the related research is restricted to cases where data are assumed to follow specific distributions. However, an event is usually described by multiple quality characteristics of which underlying distributions are unknown. In this article, we integrate the TBEA data into a specified form and then design a nonparametric multivariate TBEA (NMTBEA) control chart based on log-linear modelling. This chart is used to monitor the location shifts of the time interval and the amplitudes in an event. Next, we investigate the performance of some improved nonparametric control charts in monitoring multivariate TBEA data. The numerical simulation results show that the NMTBEA control chart performs best in most shifts that occur in six representative distributions. A real example of the colour difference monitoring of the car body in the automotive industry is provided to illustrate the implementation of the proposed chart.

Keywords:

• Multivariate time-between-events-and-amplitude
• nonparametric process
• log-linear modelling
• high-quality process
• statistical process control
• automobile painting

Acknowledgments

The authors thank three anonymous reviewers and the Associate Editor for their thoughtful and constructive comments that greatly improved the quality and presentation of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [Project Nos. 71661147003, 72032005, and 71902138].

Notes on contributors

Zhen He

Prof. Zhen He is the head of the Department of Industrial Engineering at Tianjin University. He is also the Area Editor of the Computers & Industrial Engineering (CIE). He is an Academician of the International Academy for Quality (IAQ). He received both his Ph.D. and M.S. in industrial engineering from Tianjin University. He has authored over 200 refereed journal publications. His research interests include quality engineering and Six Sigma.

Yuan Gao

Yuan Gao is a Ph.D. student in the Department of Management Science and Engineering at the College of Management and Economics, Tianjin University. Her current research interests include quality engineering, statistical process control, and product fault detection.

Liang Qu

Liang Qu currently is an associate professor of the College of Management and economic at Tianjin University. She received her Ph.D. degree in system and engineering management at the Nanyang Technology University in Singapore. Her major research areas include statistical process control, quality management, and supply chain management.

Zhiqiong Wang

Zhiqiong Wang received his Ph.D. degree in 2018 from the College of Management and Economics of the Tianjin University in China. He is currently an assistant professor of the School of Management at the Tianjin University of Technology. His major research interests include quality control and management, change-point detection, and various quality-related applications.