Human reliability assessment for tank overfilling incident utilizing minimized human performance shaping factors
ASHER AHMED Malik, RISZA Rusli, FATIN AFIFAH Binti Mohd Nasir, SALMAN Nazir, RIZAL HARRIS Wongdownload PDF
Abstract. Human errors are identified as significant contributors to process industry accidents. Human reliability analysis (HRA) has been conducted in previous studies to improve human performance in several industrial operations. However, human error predictions are greatly influenced by various performance-shaping factors (PSFs). Research also demonstrates that PSFs are interdependent, which thereby complicates the modeling and analysis. Therefore, this study performs HRA, for a tank overfilling accident scenario that resulted due to human failure. Fewer independent PSFs through careful classification were used to estimate tank overfilling probability resulting from different human-triggered factors. For HRA, this study uses a combination of the Standardized Plant Analysis Risk Human Reliability Analysis (SPAR-H) and Bayesian Belief Network (BBN). The failure probability distributions of individual interconnecting tasks were calculated using SPAR-H, and the probabilistic interdependence of each task to the final tank overfilling scenario was modeled using a BBN. From the current analysis, divergent stream identification is determined as the key to lead tank overfilling with 40% probability. This study concludes that BBN can be reliably employed in the Quantitative Risk Analysis (QRA) framework to examine human factors in industrial failure probability estimation for various other human-related industrial accident scenarios.
Human Reliability Assessment, Quantitative Risk Analysis, Bayesian Networks, Reliability, Safety
Published online 5/20/2023, 10 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: ASHER AHMED Malik, RISZA Rusli, FATIN AFIFAH Binti Mohd Nasir, SALMAN Nazir, RIZAL HARRIS Wong, Human reliability assessment for tank overfilling incident utilizing minimized human performance shaping factors, Materials Research Proceedings, Vol. 29, pp 135-144, 2023
The article was published as article 17 of the book Sustainable Processes and Clean Energy Transition
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