Accelerated Life Testing in Interference Models with Monte-Carlo Simulation

Here we have presented two accelerated Life Testing (ALT) models for interference theory of reliability. We have assumed that instead of a single stress, as faced by a system in normal operating conditions, for accelerated conditions a number of stresses are applied to the system simultaneously. In the first model we assume that the system fails if the sum of the stresses exceeds the strength of the system and assumption in the second is that the system fails if maximum of the stresses exceeds the strength. For the first model assuming that both stress and strength follow either exponential or gamma or normal distributions and in the second, generalized exponentials, we have obtained the reliability, say (R), of the system in the accelerated condition. The expressions show that when the number of stresses increases R, decreases or failure probability increases and one may get more failure data quickly, justifying the models. Using Monte-Carlo simulation we have estimated R. Another estimate of R is obtained from proportion of successes. From R we obtained estimates of reliability, say RA, at use level. Some numerical values of RA are tabulated for particular values of the parameters of stress-strength distributions. The numerical values also justify the use of the models.