Approximate Interval Estimation Methods for the Reliability of Systems UsingDiscrete Component Data

摘要

Three lower confidence interval estimation procedures for system reliability ofcoherent systems with cyclic components are developed and their accuracy evaluated by Monte Carlo methods. Each method uses estimates of the ratios of component unreliabilities and the Poisson approximation to the binomial distribution to obtain the equation for the lower confidence limit. This is an extension of a method previously reported in the literature which has been shown to be fairly robust. The procedures developed here can be combined with similar procedures already developed for systems with continuous components. The combined procedure may yield a reasonably accurate lower confidence interval procedure for the reliability of coherent systems with mixtures of continuous and cyclic components.