Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.

Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A revi...

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Autores principales:	Yaju Wu, Kaili Xu, Ruojun Wang, Xiaohu Xu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/11b9844b4c1c435384681f613aceb4e9
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spelling	oai:doaj.org-article:11b9844b4c1c435384681f613aceb4e92021-12-02T20:18:54ZHuman reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.1932-620310.1371/journal.pone.0254861https://doaj.org/article/11b9844b4c1c435384681f613aceb4e92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254861https://doaj.org/toc/1932-6203Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.Yaju WuKaili XuRuojun WangXiaohu XuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0254861 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yaju Wu Kaili Xu Ruojun Wang Xiaohu Xu Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
description	Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.
format	article
author	Yaju Wu Kaili Xu Ruojun Wang Xiaohu Xu
author_facet	Yaju Wu Kaili Xu Ruojun Wang Xiaohu Xu
author_sort	Yaju Wu
title	Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
title_short	Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
title_full	Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
title_fullStr	Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
title_full_unstemmed	Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.
title_sort	human reliability analysis of high-temperature molten metal operation based on fuzzy cream and bayesian network.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/11b9844b4c1c435384681f613aceb4e9
work_keys_str_mv	AT yajuwu humanreliabilityanalysisofhightemperaturemoltenmetaloperationbasedonfuzzycreamandbayesiannetwork AT kailixu humanreliabilityanalysisofhightemperaturemoltenmetaloperationbasedonfuzzycreamandbayesiannetwork AT ruojunwang humanreliabilityanalysisofhightemperaturemoltenmetaloperationbasedonfuzzycreamandbayesiannetwork AT xiaohuxu humanreliabilityanalysisofhightemperaturemoltenmetaloperationbasedonfuzzycreamandbayesiannetwork
_version_	1718374209181188096

Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.

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