Change-point analysis of the failure mechanisms based on accelerated life tests

In the accelerated life tests, the common failure mechanism is considered as a necessary condition for the extrapolated procedure. The traditional extrapolation model may become unreliable if the failure mechanisms under the accelerated stress levels are different from that under the normal operating condition. In this paper, we propose a change-point model for the coefficients of variation to fit the abrupt change behavior of the failure mechanisms with a nonparametric empirical likelihood approach. The related statistical inferences of the proposed model are studied to test whether there exists a change and estimate the corresponding location of the change. Monte Carlo simulations are conducted to investigate the performance of the proposed change-point test model. For the small sample data, a bootstrapping method is presented as an alternative detecting procedure. The detailed calculation process is illustrated by the lifetime data of the metal oxide semiconductor transistors in the power distribution system of Chinese Tiangong aircrafts.