Complex system reliability modelling with Dynamic Object Oriented Bayesian Networks (DOOBN)
| Autor: | Lionel Jouffe, Philippe Weber |
|---|---|
| Přispěvatelé: | Centre de Recherche en Automatique de Nancy (CRAN), Université Henri Poincaré - Nancy 1 (UHP)-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Bayesia (BAYESIA), BAYESIA |
| Rok vydání: | 2006 |
| Předmět: |
0209 industrial biotechnology
Engineering media_common.quotation_subject Complex system Dynamic Object Oriented Bayesian Networks (DOOBNs) Context (language use) 02 engineering and technology Industrial and Manufacturing Engineering Adaptability 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Added value Safety Risk Reliability and Quality Reliability (statistics) media_common Object-oriented programming [STIC]domain_stic business.industry Reliability estimation Bayesian network Markov Chain Industrial engineering A priori and a posteriori 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Reliability Engineering and System Safety Reliability Engineering and System Safety, Elsevier, 2006, 91(2), pp.149-162. ⟨10.1016/j.ress.2005.03.006⟩ |
| ISSN: | 0951-8320 1879-0836 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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