Probabilistic analysis of aluminium production explosion accidents based on a fuzzy Bayesian network

故障树分析 贝叶斯网络 工程类 法律工程学 模糊逻辑 冶金 可靠性工程 计算机科学 人工智能 材料科学
作者
Li Li,Kaili Xu,Xiwen Yao,Shoukun Chen
出处
期刊:Journal of Loss Prevention in The Process Industries [Elsevier]
卷期号:73: 104618-104618 被引量:9
标识
DOI:10.1016/j.jlp.2021.104618
摘要

Explosion accidents of molten aluminium in contact with water during aluminium production often occur and may cause injury and death. In this paper, a fuzzy Bayesian network (BN) was employed to probabilistically analyse the explosion accident of molten aluminium in contact with water. A fault tree-Bayesian network (FT-BN) model was established in the cause-effect analysis of the explosion accident, including three processes: electrolysis, molten aluminium transportation and aluminium casting. Fifty-three nodes were proposed in the model to represent the evolution process of the explosion accident from failure causes to consequences. Furthermore, the occurrence probabilities of basic events (BEs) were determined by expert judgement with weighted treatments based on fuzzy theory. By giving certain occurrence probabilities of each BE, the probability of an explosion accident was estimated. Subsequently, importance measures were assessed for each BE, which could reflect the impact on the occurrence of the top event (TE), and the final ranks were provided. The results indicate that using wet ladles and tools, water on the ground, breakage of the tap hole, damage to the casting mould, and leakage of circulating water are five main problems that cause explosion accidents. Safety advice was provided based on the analysis results. This study can help decision makers improve the safety management of aluminium production.
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