Research on the classification and control of human factor characteristics of coal mine accidents based on K-Means clustering analysis

• Published in: International journal of industrial ergonomics 2023-09, Vol.97, p.103481, Article 103481
• Main Authors: Miao, Dejun, Wang, Wenhao, Lv, Yueying, Liu, Lu, Yao, Kaixin, Sui, Xiuhua
• Format: Article
• Language: English
• Subjects: Coal mine accident; Human factors control; K-means clustering analysis; Safety; System design
• ISSN: 0169-8141
• DOI: 10.1016/j.ergon.2023.103481

The occurrence of coal mine accidents is closely related to human factors. Six-hundred eighty five coal mine accident reports were analyzed to identify risk factors for coal mine accidents. A total of 29 human factors were classified from three levels of supervision-management-production using the improved HFACS (Human Factors Analysis and Classification System) model, and the degree of clustering of human factors was verified by complex networks. Then, the 29 human factors were classified into four categories by K-Means clustering analysis, namely subjective corrective accident human factors, perceived corrective accident human factors, associated corrective accident human factors, and critical corrective accident human factors, and control suggestions were proposed for different categories. Finally, the interface of the supervision-management-production-based coal mine employee control system was designed in order to provide a solid theoretical basis for the subsequent system development and its application in specific coal mines. This study can provide new ideas for the study of human factors of coal mine accidents and help coal mine enterprises to strengthen the control of human factors. •Studied the classification and control of human factors in coal mine accidents.•Using K-Means clustering analysis and HFACS model as the main method.•Divide 29 coal mine accidents into four categories of corrective human factors.•Completed the interface design of the coal mine employee control system.