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Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian Network based CREAM

机译:利用故障树分析评估人力误差对油轮碰撞的贡献及改进模糊贝叶斯网络奶油

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摘要

Human error is a significant factor triggering oil tanker collisions. Drawbacks jeopardizing the effectiveness of human error analysis from traditional studies are spotted. This study proposes a risk assessment of human error contribution to oil tanker collision. The research evaluates the collision probability of oil tanker using a Fault Tree Analysis (FTA) structure under which a modified Fuzzy Bayesian Network based Cognitive Reliability Error Analysis Method (CREAM) is developed to conduct human error assessment. 39 specialists with substantial seagoing experience are invited to provide expert judgement for oil tanker navigation particularly in vicinity of the Taiwanese waters. Different from traditional studies, the proposed methodology provides a higher degree of result distinguishability meanwhile contemplating the weights and quantitative effects caused by the ambient elements without the loss of information from the experts. It is concluded that lack of Bridge Resource Management Communication, lack of Communication between Ships, Fatigue and Collision Regulation Violations are the elements with higher occurrence rates and would also have great potential contributing to oil tanker collision once the likelihoods deteriorated. In addition, Number of Simultaneous Goals in the bridge is the Common Performance Condition (CPC) that significantly causes the occurrence of all the human error basic events.
机译:人为错误是触发油轮碰撞的重要因素。发现了发现危害传统研究人为误差分析的有效性的缺点。本研究提出了对油轮碰撞的人为错误贡献的风险评估。该研究评估了使用故障树分析(FTA)结构的油轮的碰撞概率,在该结构下,开发了一种改进的模糊贝叶斯网络的认知认知可靠性误差分析方法(奶油)来进行人为错误评估。邀请39名具有大量海洋经验的专家,为油轮导航提供专家判决,特别是在台湾水域附近。与传统研究不同,所提出的方法提供了更高程度的结果区分性,同时考虑由环境元件造成的重量和定量效果而不会损失专家的信息。得出结论认为,缺乏桥梁资源管理通信,船舶之间缺乏沟通,疲劳和碰撞监管违规是具有较高率的元素,并且一旦可能性恶化,就会对油轮碰撞的巨大潜力也会产生极大的潜力。此外,桥梁中的同时目标的数量是常见的性能条件(CPC),其显着导致所有人为误差基本事件的发生。

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