Accelerated life tests analyzed by a piecewise exponential distribution via generalized linear models

Efficient industrial experiments for the reliability analysis of manufactured products consist of subjecting the units to accelerated life tests where, for each pre-fixed stress level, the experiment ends after the failure of a certain pre-fixed proportion of units or a certain test time is reached. This paper estimates the mean life of the units under usual working conditions, based on censored data obtained from units under stress conditions. This problem is approached through a generalized linear model and related inferential techniques, considering the very flexible class of failure distributions, piecewise exponential model and a log-linear stress-response relationship. The general framework has as particular cases, among others, the power law model, the Arrhenius model and the generalized Eyring model. A numerical example illustrates the methodology.