Joint modeling of laboratory and field data with application to warranty prediction for highly reliable products

ABSTRACT

To achieve a successful warranty management program, a good prediction of a product's field return rate during the warranty period is essential. This study aims to make field return rate predictions for a particular scenario, the one where multiple products have a similar design and discrete-type laboratory data together with continuous-type field data is available for each product. We build a hierarchical model to link the laboratory and field data on failure. The efficient sharing of information among products means that the proposed method generally provides a more stable laboratory summary for each individual product, especially for those cases with few or even no failures during the laboratory testing stage. Furthermore, a real case study is used to verify the proposed method. It is shown that the proposed method provides a better connection between laboratory reliability and field reliability, and this leads to a significant improvement in the estimated field return rate.

KEYWORDS:

• Field failure rate prediction
• go/no-go laboratory data
• empirical Bayes inference

Additional information

Notes on contributors

Sheng-Tsaing Tseng

Sheng-Tsaing Tseng received a Ph.D. in Management Science from Tamkang University, Taiwan. His research interests include quality and productivity improvement and reliability lifetime analysis. His articles have appeared in IIE Transactions, Technometrics, Journal of Quality Technology, Naval Research Logistics, International Journal of Production Research, European Journal of Operational Research, IEEE Transactions on Reliability, Reliability Engineering & System Safety, IEEE Transactions on Semiconductor Manufacturing, Journal of Statistical Planning and Inference, and other technical journals. He is an elected member of ISI and a senior member of ASQ. Currently, he serves as an Associate Editor of Technometrics.

Nan-Jung Hsu

Nan-Jung Hsu received a Ph.D. degree in Statistics from Iowa State University in 1997. She is currently a Professor at the Institute of Statistics at National Tsing-Hua University, Taiwan. Her research interests include time series analysis, industrial statistics, and environmental statistics.

Yi-Chiao Lin

Yi-Chiao Lin received an M.S. degree in Statistics from National Tsing-Hua University, Taiwan, in 2013. He is currently a statistician at Fu Bond Life Company, Taipei. His research interests include risk management and data analytics of big data.