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Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station
Affiliation: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. DHI-NTU, Nanyang Environment and Water Research Institute, Interdisciplinary Graduate School, Nanyang Technological University, 1 Clean tech Loop, Singapore 637141, Singapore;2. School of Business IT & Logistics, RMIT University, 124 La Trobe St, Melbourne, VIC 3000, Australia;1. Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Turkey;2. Surmene Faculty of Marine Sciences, Karadeniz Technical University, Turkey;1. Sciences & Research Branch, Tehran Science and Research Branch University, Hesarak, Tehran, Iran;2. Department of Maritime Management, Bursa Technical University, Osmangazi, Bursa, Turkey
Abstract:
A method is presented for analysis of reliability of complex engineering systems using information from fault tree analysis and uncertainty/imprecision of data. Fuzzy logic is a mathematical tool to model inaccuracy and uncertainty of the real world and human thinking. The method can address subjective, qualitative, and quantitative uncertainties involving risk analysis. Risk analysis with all the inherent uncertainties is a prime candidate for Fuzzy Logic application. Fuzzy logic combined with expert elicitation is employed in order to deal with vagueness of the data, to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing.The proposed model is able to quantify the fault tree of LPG refuelling facility in the absence or existence of data. This paper also illustrates the use of importance measures in sensitivity analysis. The result demonstrates that the approach is an apposite for the probabilistic reliability approach when quantitative historical failure data are unavailable. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process.
Keywords:Fuzzy fault tree analysis  Failure probability  Theory of fuzzy set  Expert elicitation  Sensitivity analysis
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