Evidence map›Paper›PMID 36536010›Full record

ArticleScientific reports2022

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network.

Linhui Sun, Liao Wang, Chang Su, Fangming Cheng, Xinping Wang, Yuanrui Jia, Ziming Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Linhui SunSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, China.
Liao WangSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, China.
Chang SuSchool of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an, 710054, China.
Fangming ChengSchool of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an, 710054, China. chengfm@xust.edu.cn.
Xinping WangSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, China.
Yuanrui JiaSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, China.
Ziming ZhangSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human reliability of intelligent coal mine hoist operation system is affected by many factors, in order to reduce the occurrence of human error in the hoist system and improve the reliability of the system. The characteristics of phased-mission task operation of hoists is combined, the phase dependence of human cognitive errors is considered and, a new human reliability evaluation method is proposed with the help of Bayesian network (BN) model in this paper. Firstly, the phase dependence of human cognitive errors was analyzed based on the cognitive behavior model. Then the human error analysis in the hoist system was carried out, and several main performance shaping factors are selected. Secondly, BN was used to build the human reliability model of the hoist system at each stage. Finally, it is found that the phase dependence of cognitive errors has a negative impact on the human reliability of the hoist system through the case analysis. At the same time, several main performance shaping factors (PSFs)were quantitatively analyzed by using the reverse reasoning ability of BN, which proves the effectiveness of the proposed method, and provides a scientific and reasonable theoretical basis for the development of effective human error prevention measures for the operation of intelligent coal mine hoists.

Indexed as

CoalCoal MiningBayes TheoremHumansReproducibility of ResultsCoal

Identifiers

PMID36536010
PMCPMC9763394

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