Accelerated degradation tests with inspection effects

Accelerated degradation tests with inspection effects

Zhao, Xiujie (Tianjin University)
Chen, P. (TU Delft Statistics)
Gaudoin, Olivier (Université Grenoble Alpes)
Doyen, Laurent (Université Grenoble Alpes)

2021-08-01

This study proposes a framework to analyze accelerated degradation testing (ADT) data in the presence of inspection effects. Motivated by a real dataset from the electric industry, we study two types of effects induced by inspections. After each inspection, the system degradation level instantaneously reduces by a random value. Meanwhile, the degrading rate is elevated afterwards. Considering the absence of observations due to practical reasons, we employ the expectation–maximization (EM) algorithm to analytically estimate the unknown parameters in a stepwise Wiener degradation process with covariates. Moreover, to maintain the level of generality for the adaption of the method in various scenarios, a confidence density approach is utilized to hierarchically estimate the parameters in the acceleration link function. The proposed methods can provide efficient parameter estimation under complex link functions with multiple stress factors. Further, confidence intervals are derived based on the large-sample approximation. Simulation studies and a case study from Schneider Electric are used to illustrate the proposed methods. The results show that the proposed model yields a remarkably better fit to the Schneider data in comparison to the conventional Wiener ADT model.

Accelerated degradation tests
Confidence density
Degradation modeling
Reliability
Wiener process

http://resolver.tudelft.nl/uuid:4814315c-3230-497f-970f-2b9e760358ca

https://doi.org/10.1016/j.ejor.2020.11.041

0377-2217

European Journal of Operational Research, 292 (3), 1099-1114

Institutional Repository

journal article

© 2021 Xiujie Zhao, P. Chen, Olivier Gaudoin, Laurent Doyen