On dynamically monitoring aggregate warranty claims for early detection of reliability problems

Abstract

Warranty databases managed by most world-leading manufacturers are constantly expanding in the big data era. An important application of warranty databases is to detect unobservable reliability problems that emerge at design and/or manufacturing stages, through modeling and analysis of warranty claims data. Usually, serious reliability problems will result in certain abnormal patterns in warranty claims, which can be captured by appropriate statistical methods. In this article, a dynamic control charting scheme is developed for early detection of reliability problems by monitoring warranty claims one period after another, over the product life cycle. Instead of specifying a constant control limit, we determine the control limits progressively by considering stochastic product sales and non-homogeneous failure processes, simultaneously. The false alarm rate at each time period is controlled at a desired level, based on which abrupt changes in field reliability, if any, will be detected in a timely manner. Furthermore, a maximum-likelihood-based post-signal diagnosis scheme is presented to aid in identifying the most probable time of problem occurrence (i.e., change point). It is shown, through in-depth simulation studies and a real case study, that the proposed scheme is able to detect an underlying reliability problem promptly and meanwhile estimate the change point with an acceptable accuracy. Finally, a moving window approach concerning only recent production periods is introduced to extend the original model so as to mitigate the “inertia” problem.

Keywords:

• Warranty
• reliability
• product life cycle
• statistical process monitoring
• diagnostics

Acknowledgments

The authors are grateful to the Editors and the anonymous referees for their insightful comments that helped to significantly improve this article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 71601166, 71532008, 71801179), the Research Grants Council of Hong Kong under Theme-based Research Fund (Grant No. T32-101/15-R) and General Research Fund (Grant Nos. CityU 11213116, CityU 11203519), and also the Singapore AcRF Tier 2 Funding (Grant No. R-266-000-125-112).

Notes on contributors

Chenglong Li

Chenglong Li is an associate professor in the School of Management at Northwestern Polytechnical University, China. He received his Ph.D. from Xi’an Jiaotong University and City University of Hong Kong in 2017. He received a B.E. in industrial engineering from Xi’an Jiaotong University in 2011. Currently, his research interests are mainly on quality engineering, statistical modeling and intelligent decision.

Xiaolin Wang is a Ph.D. candidate in industrial engineering at City University of Hong Kong. He received his B.E. and M.S. degrees in industrial engineering from Southeast University in 2013 and 2016, respectively. Currently, he is interested in applying machine learning, stochastic modeling, and optimization techniques in reliability, maintenance, and warranty management areas. He is a recipient of the prestigious Hong Kong Ph.D. Fellowship (HKPFS) from the Hong Kong Research Grants Council.

Xiaolin Wang

Xiaolin Wang is a Ph.D. candidate in industrial engineering at City University of Hong Kong. He received his B.E. and M.S. degrees in industrial engineering from Southeast University in 2013 and 2016, respectively. Currently, he is interested in applying machine learning, stochastic modeling, and optimization techniques in reliability, maintenance, and warranty management areas. He is a recipient of the prestigious Hong Kong Ph.D. Fellowship (HKPFS) from the Hong Kong Research Grants Council.

Lishuai Li is an assistant professor in the Department of Systems Engineering and Engineering Management at City University of Hong Kong. She received a Ph.D. and a M.S. in air transportation systems from Massachusetts Institute of Technology (MIT). She received a B.E. from Fudan University. She is interested in developing analytical methods and practical algorithms to improve air transportation systems with the use of large-scale data generated from real-world operations.

Lishuai Li

Lishuai Li is an assistant professor in the Department of Systems Engineering and Engineering Management at City University of Hong Kong. She received a Ph.D. and a M.S. in air transportation systems from Massachusetts Institute of Technology (MIT). She received a B.E. from Fudan University. She is interested in developing analytical methods and practical algorithms to improve air transportation systems with the use of large-scale data generated from real-world operations.

Min Xie is a Chair Professor in industrial engineering at City University of Hong Kong. He received his Ph.D. from Linkoping University, Sweden in 1987. He did his undergraduate study and received a M.S. at Royal Institute of Technology in Sweden in 1984. Dr. Xie joined the National University of Singapore in 1991 as one of the first recipients of the prestigious Lee Kuan Yew Research Fellowship. He has authored or co-authored numerous refereed journal papers and several books. He is a Department Editor of IISE Transactions and Editor of Reliability Engineering & System Safety and serves in a number of other international journals. He has organized many international conferences, and also 50 Ph.D. students have graduated under his supervision. He was elected a fellow of IEEE for his contribution to systems and software reliability.

Min Xie

Min Xie is a Chair Professor in industrial engineering at City University of Hong Kong. He received his Ph.D. from Linkoping University, Sweden in 1987. He did his undergraduate study and received a M.S. at Royal Institute of Technology in Sweden in 1984. Dr. Xie joined the National University of Singapore in 1991 as one of the first recipients of the prestigious Lee Kuan Yew Research Fellowship. He has authored or co-authored numerous refereed journal papers and several books. He is a Department Editor of IISE Transactions and Editor of Reliability Engineering & System Safety and serves in a number of other international journals. He has organized many international conferences, and also 50 Ph.D. students have graduated under his supervision. He was elected a fellow of IEEE for his contribution to systems and software reliability.

Xin Wang is a research fellow in the Department of Industrial Systems Engineering and Management at National University of Singapore. She received a Ph.D. in industrial engineering from National University of Singapore. She received a B.E. in international economy and trade from Harbin Institute of Technology. Her research interests include warranty management, resilience modeling and assessment, and reliability engineering.

Xin Wang

Xin Wang is a research fellow in the Department of Industrial Systems Engineering and Management at National University of Singapore. She received a Ph.D. in industrial engineering from National University of Singapore. She received a B.E. in international economy and trade from Harbin Institute of Technology. Her research interests include warranty management, resilience modeling and assessment, and reliability engineering.