Analyzing human reliability for the operation of cargo oil pump using fuzzy CREAM extended Bayesian Network (BN)
Citation
Sezer, Ş.İ, Alidolu, G., Aydın, M., Ahn, S.I., Akyüz, E. & Kurt, R.E. (2024). Analyzing human reliability for the operation of cargo oil pump using fuzzy CREAM extended Bayesian Network (BN). Ocean Engineering, 299, 117345. https://doi.org/10.1016/j.oceaneng.2024.117345Abstract
Crude oil cargo discharging operations can be performed by cargo oil pumps in tanker ships. Considering the harmful effects of crude oil, any failure during the cargo oil pump operation may pose acute hazards such as temperature and pressure increase in pipelines, leakage, fire, and following undesired events that lead to marine environmental pollution and toxic effects to humans. The process is managed by the ship's crew, and it requires following the operational steps in order. This paper aims at performing a detailed human reliability analysis (HRA) for the operational process of cargo oil pumps on a tanker ship. In the paper, the Cognitive Reliability and Error Analysis Method (CREAM) is used to calculate human error probability under a fuzzy set which deals with the uncertainty and ambiguity of the CPC (Common Performance Condition). The Bayesian Network (BN) approach is adopted to determine the probability distribution of the control modes in reliability assessment. In view of the findings, the human reliability for the entire process of cargo oil pump operation on tanker ship is found 8.82E-01. The outcomes of the paper provide valuable insight into the improvement of tanker safety in shipboard operation and performance reliability assessment.