Developing the human reliability analysis model tailored for intelligent coal mining face system

Yan Zhang, Ninghao Sun, Xiangyang Hu and Ruipeng Tong

Resources Policy, 2024, vol. 98, issue C

Abstract: The still severe situation of work safety and the increasingly prominent issue of labor shortage are currently the key factors affecting the safety and sustainable development of coal industry. To fundamentally solve these problems, the construction of intelligent coal mines has become an inevitable trend. In the current construction context, intelligent coal mining operations rely more on human-system interaction, bringing new human error risks. The applicable human reliability analysis (HRA) method can effectively identify and evaluate the risks, and further improve the safety level of intelligent coal mines. However, research on HRA for intelligent coal mines is still in early stages, lacking applicable theoretical basis and methodological system. To make up for the limitations, focusing on the research object of intelligent coal mining face (ICMF) system, firstly, a cognitive model suitable for ICMF operations was constructed combining with the system structure and task characteristics, laying a cognitive theoretical foundation for initiating research on human safety of intelligent coal mines. Based on this, the ICMF-HRA variables including general human failure event (HFE), seven main crew functions (MCFs), eighteen crew activity primitives (CAPs), twenty-five crew failure modes (CFMs), and twenty-nine performance influencing factors (PIFs), and three qualitative dependency structures (i.e., HFE-MCF-CAP-CFM, CFM-PIF, and PIF-PIF) and six quantitative probability relationships between them are developed using fuzzy Bayesian network, which constitutes the ICMF-HRA model. Moreover, the application of this model is elaborated combining communication interruption event, confirming the availability and adaptability of this model. The ICMF-HRA model fills the HRA research gap of intelligent coal mines and can be used for predictive and retrospective analysis, providing decision support for risk prevention and disposal. This study is expected to establish theoretical basis and provide practical tool for improving human safety level of intelligent coal mines, further promoting the safety and sustainable development of coal industry.

Keywords: Intelligent coal mine; Intelligent coal mining face; Human reliability analysis; Dependency modeling; Hierarchical Bayesian network (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:98:y:2024:i:c:s0301420724007426

DOI: 10.1016/j.resourpol.2024.105375

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