A Fuzzy optimal planned replacement time based on availability and cost functions

Since the population or population’s parameters of a system or subsystem are generally unknown, if we use the point estimates of parameters to estimate other characteristics of systems using a random sample from data in the past, these estimates of the system may fluctuate around the point estimates during a time interval. It follows that to use the point estimates is not suitable for the real cases. Therefore, it is more desirable to use the statistical confidence interval. Transferring the statistical confidence interval into the triangular fuzzy number gives a good sense to the values which belong to it. In this paper, we consider the parameters of lifetime distributions as triangular fuzzy numbers. Through these parameters, we calculate a fuzzy optimal planned replacement time based on cost and availability functions.