Optimal Reliability of Components of Complex Systems Using Hierarchical System Models

Authors

Kazuyoshi Nishijima, Marc A. Maes, Jean Goyet and Michael H. Faber

Abstract

The present paper addresses the issue of optimization of reliability acceptance criteria for components of complex engineered systems with given criterion to acceptable system risk. To this end, the paper first describes how complex engineered systems may be modelled hierarchically by use of Bayesian probabilistic networks. The Bayesian probabilistic network serves as a function relating the reliability acceptance criteria of the individual components of the system to the risk acceptance criteria for the system. Thereafter, a constrained optimization problem is formulated for the optimization of the
component reliabilities. In this optimization problem the system risk acceptance criterion defines the constraint and the expected utility from the system, is considered as the objective function. A ship hull structure is taken as an example of a complex engineered system to illustrate how the proposed framework may be implemented into a software tool using commonly available techniques and algorithms.

Published in/by

Special Workshop on Risk Acceptance and Risk Communication, March 26-27, 2007, Stanford University, Stanford, USA.
Available on http://www.ripid.ethz.ch/