 Complex system reliability modelling with Dynamic Object Oriented Bayesian Networks (DOOBN)☆☆Revised version of the paper presented at QUALITA 2003Philippe Weber and Lionel Jouffe Reliability Engineering and System Safety, 2006, vol. 91, issue 2, 149-162 Abstract: Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance policies. This article presents a methodology that will help developing Dynamic Object Oriented Bayesian Networks (DOOBNs) to formalise such complex dynamic models. The goal is to have a general reliability evaluation of a manufacturing process, from its implementation to its operating phase. The added value of this formalisation methodology consists in using the a priori knowledge of both the system's functioning and malfunctioning. Networks are built on principles of adaptability and integrate uncertainties on the relationships between causes and effects. Thus, the purpose is to evaluate, in terms of reliability, the impact of several decisions on the maintenance of the system. This methodology has been tested, in an industrial context, to model the reliability of a water (immersion) heater system. Keywords: Dynamic Object Oriented Bayesian Networks (DOOBNs); Markov Chain; Reliability estimation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:2:p:149-162 DOI: 10.1016/j.ress.2005.03.006 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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