Publication
Title
Safety analysis of process systems using Fuzzy Bayesian Network (FBN)
Author
Abstract
Quantitative risk assessment (QRA) has played an effective role in improving safety of process systems during the last decades. However, QRA conventional techniques such as fault tree and bow-tie diagram suffer from drawbacks as being static and ineffective in handling uncertainty, which hamper their application to risk analysis of process systems. Bayesian network (BN) has well proven as a flexible and robust technique in accident modeling and risk assessment of engineering systems. Despite its merits, conventional applications of BN have been criticized for the utilization of crisp probabilities in assessing uncertainty. The present study is aimed at alleviating this drawback by developing a Fuzzy Bayesian Network (FBN) methodology to deal more effectively with uncertainty. Using expert elicitation and fuzzy theory to determine probabilities, FBN employs the same reasoning and inference algorithms of conventional BN for predictive analysis and probability updating. A comparison between the results of FBN and BN, especially in critically analysis of root events, shows the out-performance of FBN in providing more detailed, transparent and realistic results.
Language
English
Source (journal)
Journal of loss prevention in the process industries. - Stoneham
Publication
Stoneham : 2019
ISSN
0950-4230
Volume/pages
57(2019), p. 7-16
ISI
000457949500002
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 13.11.2018
Last edited 15.07.2021
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