Developing Data-based Bayesian Network for Human Operation Analysis during Hot Work
Wang, Yanchun
Liu, Yi
Wang, Wei
Chen, Jian
Dong, Hanhai
Zhao, Dongfeng
Khan, Faisal
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How to Cite

Wang Y., Liu Y., Wang W., Chen J., Dong H., Zhao D., Khan F., 2019, Developing Data-based Bayesian Network for Human Operation Analysis during Hot Work, Chemical Engineering Transactions, 77, 733-738.
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Hot work has caused numerous accidents during the inspection and maintenance process in recent years in China. This paper collected the hot work accidents in China since 2007 and integrated them into a database. The database contained the information such as the time, site, sequence, source, type, cause and consequence. Through analysing the database, most accidents were relevant to human operations. We classified unsafe and irregular operations caused by human factors during hot work. The causes of hot work accidents involved a series of problems during the approval, supervision and construction. Integrating hot work procedures, we established the main safety evaluation framework containing three factors, i.e., approval, execution environment, and protective measures. The method of Bayesian Network (BN) aiming at solving uncertain problems was utilized to identify unsafe operations quantitatively during hot work. Eventually, eight key proposals were presented to avoid hot work accidents. The proposed framework was developed to assess human operations in chemical plants during hot work. Causes of hot work accidents in chemical plants mainly consisted of failure to handle permits of hot work, production system without isolation, unremoved flammable materials, and failure to install fire prevention measures. The results can provide compelling support for human management and training during hot work.
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