A Bayesian Reliability Growth Model

Abstract

A model is presented for the change (growth) in reliability of a system during a test program. Parameters of the model are assumed to be random variables with appropriate prior density functions. Expressions are then derived that enable estimates (in the form of expectations) and precision statements (in the form of variances) to be made of: 1) projected system reliability at time τ after the start of the test program, and 2) system reliability after the observation of failure data. Numerical examples are presented, and extension to multimode failures is indicated.