Change-point detection of failure mechanism for electronic devices based on Arrhenius model

In this paper, we consider the abrupt change-point and continuous change-point failure mechanisms in the accelerated life tests of electronic devices and propose corresponding detection methods based on the Weibull distribution and the Arrhenius model. The new methods can handle the detection of failure mechanism change-point with censored data and small samples. Comprehensive simulation studies are conducted to test the performance of the proposed methods and investigate the influences of the change location, the parameters and the censored ratios. Results of the simulation studies show that the proposed methods perform well in terms of type I errors and powers, and the change of parameters has a stronger impact on the performance of the new methods compared to the change location and censored ratios. In the end, we provide two real-world examples. The new class H insulation example shows that the proposed methods can predict the reliability reasonably well by detecting the change point, and the metal oxide semiconductor transistor example shows that the new methods can greatly reduce the experimental time and provide accurate reliability predictions.