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

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

Applying evidential reasoning extended SPAR-H modelling to analyse human reliability on crude oil tanker cargo operation

Human reliability analysis is essential to predict ship crew performance at the operation level for critical shipboard operations which pose a high risk. Specifically, the crew who are working on tanker ships has to be extra vigilant against the hazardous nature of the cargo. This paper performs a detailed human reliability analysis step by step for cargo discharging operations in crude oil tankers. To achieve this purpose, a Standardised Plant Analysis Risk Human Reliability Analysis (SPAR-H) extended by the Evidential Reasoning (ER) approach is used to systematically predict human errors. While SPAR-H provides a robust tool to calculate human errors simultaneously, the ER fuses raters' opinions in decision-making. The finding of the research shows that the overall human reliability is found at 6.52E-01 for cargo discharging operations in crude oil tankers. Besides its practical contributions to maritime crude oil transportation, the proposed approach presents how a comprehensive insight into human reliability can be gained