Estimation and Optimal Plan for Bivariate Step-Stress Accelerated Life Test under Progressive Type-I Censoring

In this paper, a step-stress accelerated life test with two stress variables for Weibull distribution under progressive Type-I censoring is considered. The stress-life relationship is a log-linear function of stress levels, and for each combination of stress levels, a cumulative exposure model is assumed. The maximum likelihood and Bayes estimates of the model parameters are obtained. The optimum test plan is developed using the variance-optimality criterion, which consists of finding out the optimal stress change time by minimizing the asymptotic variance of the maximum likelihood estimates of the log of the scale parameter at the design stress. The proposed study is illustrated by using simulated data.