Availability modelling of repairable systems using Bayesian networks

We present a hybrid Bayesian network (HBN) framework to model the availability of renewable systems. We use an approximate inference algorithm for HBNs that involves dynamically discretizing the domain of all continuous variables and use this to obtain accurate approximations for the renewal or repa...

Full description

Saved in:
Bibliographic Details
Published in:Engineering applications of artificial intelligence Vol. 25; no. 4; pp. 698 - 704
Main Authors: Neil, Martin, Marquez, David
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.06.2012
Subjects:
Approximation
Availability
Bayesian analysis
Bayesian networks
Bayesian software
Dynamic discretization
Dynamical systems
Dynamics
Mathematical models
Networks
Renewable systems
Repair time
Systems availability
Systems dependability
Dynamic discretization
Systems availability
Bayesian networks
Systems dependability
Bayesian software
Renewable systems
ISSN:0952-1976, 1873-6769
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present a hybrid Bayesian network (HBN) framework to model the availability of renewable systems. We use an approximate inference algorithm for HBNs that involves dynamically discretizing the domain of all continuous variables and use this to obtain accurate approximations for the renewal or repair time distributions for a system. We show how we can use HBNs to model corrective repair time, logistics delay times and scheduled maintenance time distributions and combine these with time-to-failure distributions to derive system availability. Example models are presented and are accompanied by detailed descriptions of how repair (renewal) distributions might be modelled using HBNs.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0952-1976
1873-6769
DOI:10.1016/j.engappai.2010.06.003