Imprecise Probability Method with the Power-Normal Model for Accelerated Life Testing

We present a new nonparametric predictive inference (NPI) method using a power-normal model for accelerated life testing (ALT). Combined with the accelerating link function and imprecise probability theory, the proposed method is a feasible way to predict the life of the product using ALT failure data. To validate the method, we run a series of simulations and conduct accelerated life tests with real products. The NPI lower and upper survival functions show the robustness of our method for life prediction. This is a continuous research, and some progresses have been made by updating the link function between different stress levels. We also explain how to renew and apply our model. Moreover, discussions have been made about the performance.

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