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A human reliability analysis for ship to ship LNG bunkering process under D-S evidence fusion HEART approach

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Elsevier BV

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LNG (Liquid Natural Gas) ship to ship bunkering process is quite a new concept for the maritime industry since the usage of LNG has been increasing worldwide. The LNG bunkering process poses a high risk due to human errors, while a minor error may be catastrophic. The expectation of the ship's crew is to carry out operations without any errors. Therefore, human reliability analysis (HRA) is paramount to improving operational safety during the ship to ship LNG bunkering process. In this context, this paper performs a systematic HRA under the D–S (Dempster-Shafer) evidence fusion-based HEART (human error assessment and reduction technique) approach. While the HEART quantifies human error for the tasks being performed, the extended D-S evidence fusion deals with the limitation of APOA (assessing the proportion of effect) calculation since it significantly relies on evaluating a single rater. The finding shows that human reliability for the ship to ship LNG bunkering process is 5.98E-01 and reasonable, but not at the desired level. The paper's outcomes will contribute to the utmost for LNG ship operators, safety inspectors, and ship owners to establish a safe and efficient ship to ship LNG bunkering process and minimise human error-based accidents.

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Risk, Safety engineering, Human error assessment, Errors, Naval architecture. Shipbuilding. Marine engineering, Framework, D-S evidences, Reliability theory, Maintenance procedures, Engineering, Liquefied natural gas, Fusion theory, Operations, Assessment technique, Ships, Error reduction, Facilities, Evidence fusion, Human error probabilities, Marine, D-S evidence fusion theory, D-S evidence Fusion theory, Systems, Heart, Liquid natural gas, Human reliability, Electrical Engineering, Electronics & Computer Science - Safety & Maintenance - Safety Climate, Liquid natural gas bunkering process, Human Error, Nuclear Power Plants, HEART, Human error assessment and reduction technique, Ergonomics, LNG bunkering process, Reliability analysis, Liquefied natural-gas, Reduction techniques, Model

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