STOCHASTIC BOUNDS FOR GENERALIZED SYSTEMS IN RELIABILITY THEORY

Abstract

Practically, it is not feasible to obtain the precise reliability of systems in a reasonable time, when the systems are large and complex. In this paper, we present some stochastic bounds on generalized systems of which state spaces are mathematically partially ordered sets. In the first place we introduce a notion of generalized systems and then present some stochastic bounds on the system reliability by using maximal and minimal elements of the structures of the systems. The bounds are generalization of the well-known max-min bounds on binary-state system reliability. Furthermore, we present the other stochastic bounds when systems are decomposed into several modules and satisfy a condition which is called MC (Maximal Coincidence) condition. We show that these bounds are tighter than the former. For a few simple systems, we give numerical examples and estimations of computational complexity for obtaining these stochastic bounds.