Combining Component and System Information in System Reliability Calculation

Abstract

In system reliability prediction, one of the most difficult problems (especially if the classical statistics approach is used) is to combine component and system failure data. Asymptotic and approximate methods to calculate classical confidence intervals on system reliability continue to be produced each year [cf Martz and Waller (1982), Chapter 11]. However, since classical confidence intervals do not produce a probability for system survival conditional on data, they c a n n o t provide the basis for action in the decision theory sense [see Lindley (1972), p. 16 for a discussion of confidence intervals]. Since the Bayesian Approach does provide a means for producing a probability for system survival, conditional on data, which can be used for decision, we concentrate on this approach.