Optimum test condition setting and sample allocation for accelerated degradation tests under the last-exit-time failure mode

ABSTRACT

Accelerated degradation tests (ADTs) have been widely adopted for products whose failure is defined as the first-passage-time (FPT) when the degradation path crosses a given threshold. However, for products whose failure is defined as the last-exit-time (LET), few studies related to ADT have been investigated. In this paper, we focus on designing an optimum test condition setting and sample allocation scheme for ADTs under the LET failure mode. In particular, the widely adopted Wiener process model and the generalized exponential acceleration model are used to describe the fluctuating degradation behaviors of products. By minimizing the asymptotic variance of mean-time-to-failure under the normal use condition, we design a two-level optimum test plan and a three-level compromise plan under the constraints of total sample size and stress region. The optimum plans are given in analytical forms, and we prove that the optimum plans under the FPT failure mode and LET failure mode are equivalent under some situations. Finally, a renewed selection method for the upper limit of the stress level in ADTs is proposed based on the prior ADT information from the perspective of accelerated mechanism equivalence. The proposed method is illustrated using a real-world application to rubber rings.

KEYWORDS:

• Accelerated degradation test
• optimization scheme
• first-passage-time
• last-exit-time
• degradation mechanism equivalence

Acknowledgements

The authors are grateful to the editor, associate editor, and anonymous referees for many insightful suggestions that significantly improved the quality of this article.

Disclosure statement

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

Additional information

Funding

This work was supported by the Ammunition & Missile Support Techniques Laboratory [2022SYSJ02]; Reliability and Environmental Engineering Science & Technology Laboratory [6142004210105].

Notes on contributors

Junchao Dong

Junchao Dong is currently a PhD student with the School of Reliability of Systems Engineering, Beihang University, China. He received the BE degree from Beihang University in 2014. His research interests include accelerated life tests and reliability assessment.

Xiaobing Ma

Xiaobing Ma received a PhD degree in engineering mechanics from Beihang University, Beijing, China, in 2006. He is currently a professor with the School of Reliability and Systems Engineering, Beihang University. His current research interests include reliability data analysis, durability design, and system life modeling.

Han Wang

Han Wang received a PhD degree in systems engineering from Beihang University, Beijing, China, in 2020. He is currently an associate professor with the School of Reliability and Systems Engineering, Beihang University. His research interests include accelerated tests, stochastic degradation modeling, and remaining useful life prediction.

Yujie Liu

Yujie Liu is currently a PhD student with the School of Reliability of Systems Engineering, Beihang University, China. He received the BE degree from Beihang University in 2021. His research interests include accelerated life tests and reliability assessment.

Yu Zhao

Yu Zhao received a PhD degree in systems engineering from Beihang University, Beijing, China, in 2005. He is currently a professor with the School of Reliability and Systems Engineering, Beihang University, where he is also the Associate Director of the Key Laboratory on Reliability and Environmental Engineering Technology. His current research interests include reliability engineering, quality management, and application of statistics techniques.