Design of optimal step–stress accelerated life tests under progressive type I censoring with random removals

This paper considers the analysis of exponential distributed lifetime data observed under k-stage step–stress accelerated life test under progressive type I censoring with random removal (PCRR), where the number of units removed at each stress follows a binomial distribution. We compute the expected Fisher information matrix of the maximum likelihood estimator of the log mean life at design (use) stress. The problem of choosing the optimal time τi, i = 1, . . . , k − 1 under k-stage step–stress is addressed using variance (V)-optimality as well as determinant (D)-optimality criteria. An illustrative example is provided with discussion.