School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China.
Public Administration and Humanities College, Dalian Maritime University, Dalian 116026, China.
Int J Environ Res Public Health. 2021 Dec 28;19(1):297. doi: 10.3390/ijerph19010297.
The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified human factor analysis classification system (HFACS) was applied to identify the human factors involved in the accidents, the results of which were then converted into diverse components of a fault tree and, as a result, a single-level nested model was established. For the development of a double-nested model, the structured fault tree was mapped into a Bayesian network (BN), which can be simulated with the obtained prior probabilities of parent nodes and the conditional probability table by fuzzy theory and expert elicitation. Finally, the developed BN model is simulated for various scenarios to analyze the identified human factors by means of structural analysis, path dependencies and sensitivity analysis. The general interpretation of these analysis verify the effectiveness of the proposed methodology to evaluate the human factor risks involved in operational accidents in a shipyard.
造船厂的作业活动存在与人相关的高风险。为了研究造船厂作业事故中的人为因素，本研究提出了一种双重嵌套模型。采用修正后的人因分析分类系统（HFACS）来识别事故中的人为因素，将结果转化为故障树的不同组件，从而建立了一个单层嵌套模型。为了开发双重嵌套模型，将结构化故障树映射到贝叶斯网络（BN）中，可以使用模糊理论和专家启发式方法获得父节点的先验概率和条件概率表对其进行模拟。最后，通过结构分析、路径依赖和敏感性分析对所开发的 BN 模型进行各种场景的模拟，以分析确定的人为因素。这些分析的总体解释验证了所提出的方法在评估造船厂作业事故中人因风险方面的有效性。
