Overview on Bayesian networks applications for dependability,risk analysis and maintenance areas |
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| Authors: | P. Weber G. Medina-Oliva C. Simon B. Iung |
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| Affiliation: | 1. China University of Petroleum, No. 66 Changjiang West Road, Economic& Technological Development Zone, Qingdao 266555, China;2. City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China;1. LISES-DICAM Dipartimento di Ingegneria Civile, Chimica, Ambientale e dei Materiali, Alma Mater Studiorum – Università di Bologna, via Terracini 28, 40131 Bologna, Italy;2. Department of Production and Quality Engineering, Norwegian University of Science and Technology NTNU, S.P. Andersens veg 5, 7031 Trondheim, Norway;3. SINTEF Technology and Society, Safety Research, S.P. Andersens veg 5, 7031 Trondheim, Norway;4. Safety and Risk Engineering Group (SREG), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada;1. Department of Mechanical Engineering, Ramco Institute of Technology, Rajapalayam 626117, India;2. Dr. Sivanthi Aditanar College of Engineering, Tiruchendur 628215, India;3. Department of Mechanical Engineering, Kalasalingam University, Anand Nagar, Krishnankoil 626126, India;1. Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL, Canada A1B 3X5;2. Department of Process Engineering and Applied Science, Dalhousie University, Halifax, NS, Canada B3J 2X4;1. Liverpool Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool L3 3AF, UK;2. Department of International Shipping, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, 200240, China;1. School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;2. Department of Civil & Environmental Engineering, University of Maryland, College Park, MD 20742-3021, USA;3. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Poland;4. Department of Building, School of Design & Environment, National University of Singapore, Singapore |
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| Abstract: | In this paper, a bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance. It is shown an increasing trend of the literature related to these domains. This trend is due to the benefits that Bayesian networks provide in contrast with other classical methods of dependability analysis such as Markov Chains, Fault Trees and Petri Nets. Some of these benefits are the capability to model complex systems, to make predictions as well as diagnostics, to compute exactly the occurrence probability of an event, to update the calculations according to evidences, to represent multi-modal variables and to help modeling user-friendly by a graphical and compact approach. This review is based on an extraction of 200 specific references in dependability, risk analysis and maintenance applications among a database with 7000 Bayesian network references. The most representatives are presented, then discussed and some perspectives of work are provided. |
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