ASQ - Electronics and Communications Division

Downwards Propagating: Bayesian Analysis of Complex on-demand Systems

Abstract: 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must first be obtained from the IEEE.

A Bayesian approach for inference from multiple overlapping higher level data sets on component failure probabilities within complex on demand systems is presented in this paper (systemic or sub-systemic data is referred to as higher level data as it appears ‘higher’ in visualization methodologies). The approach is based on a detailed understanding of the system logic represented using faulttrees, reliability block diagrams or another similar representation. Structure functions of the relevant sensors in terms of component states are used in conjunction with the probability of all possible system states to generate the likelihood function of overlapping evidence. This forms the basis of the likelihood function used in the Bayesian analysis of the overlapping data sets.

Keywords: RAMS 2010 Proceedings - Integrated Systems Analysis - Bayesian - Reliability Analysis/Allocation/Prediction/Estimation

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