Constrained optimal designs for step-stress accelerated life testing experiments

Abstract

In this paper, we consider multiple step-stress accelerated life testing (ALT) plans with time-censoring. The maximum likelihood method is used for estimating the model parameters. The information matrix is derived, and the optimal stress levels and the optimal stress-changing times are determined under three optimality criteria: D-, A-, and Q-optimalities for the proportional hazards models. The efficiencies of our resulting optimal three-step-stress ALT plans are compared with their competitors. The efficiency comparison results have shown that the three-step-stress designs we have obtained with both an optimal middle stress level and two optimal stress changing times are more efficient.