A novel approach to optimal accelerated life test planning with interval censoring

Accelerated life testing (ALT) is widely used in industry to obtain the lifetime estimate of a product which is expected to last years or even decades. It is important to find an effective experimental design of ALT with the consideration of certain optimality criteria. In this paper, we discuss a new approach to designing ALT test plans when readout data (i.e., interval censoring) are collected. We utilize the proportional hazard (PH) model for a failure time distribution, and formulate a generalized linear model (GLM) for censored data. The optimal design is obtained such that the prediction variance of the expected product lifetime at the product's use condition is minimized.