Analyzing human reliability for the operation of cargo oil pump using fuzzy CREAM extended Bayesian Network (BN).

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. • Quantitative human reliability analysis is performed under fuzzy and Bayesian Network CREAM (Cognitive Reliability and Error Analysis Method) modelling. • Human reliability is predicted for the cargo oil pump operation process on tanker ships. • Insight can be provided to maritime stakeholders to improve process safety on tanker ships. [ABSTRACT FROM AUTHOR]