The structure of underground coal mines is vulnerable to many mishaps because of the challenging conditions of production and the unique features of the earth. These incidents could cause significant financial and production losses for the mines in addition to worker injury, disability, or death. In coal mines, methane explosions are a frequent threat. Establishing a safe work environment requires managing these problems with an accident control method. The current study used the fuzzy TOPSIS and fuzzy AHP techniques for this aim. The framework was used to tackle the four-alternative problem of underground coal mine explosion control method selection. To identify potential risks of a methane explosion, a data gathering survey was conducted as part of the suggested hybrid methodology. The fuzzy AHP was used to compute the fuzzy weights of the hazards. “Improper ventilation system” is ranked highest out of the 34 sub-risk factors. The fuzzy TOPSIS was then utilized to rank the explosion control methods using the weights. To assess the viability of the study’s conclusions, a sensitivity analysis was carried out. The findings indicate that “improving safety technology” and “financial investments” are the best ways to reduce such events. The results additionally indicate that the fuzzy TOPSIS approach in combination with the fuzzy AHP provides a helpful framework for dynamically assessing mine methane explosion accidents.

In occupational studies, it is a known situation that technical and organizational attempts are used to prevent occupational accidents. Especially in the mining sector, if these attempts cannot prevent occupational accidents, personal protective equipment (PPE) becomes a necessity. Thus, in this study, the main objective is to examine the effects of the variables on the use of PPE and identify important factors. A questionnaire was implemented and structural equation modeling was conducted to ascertain the significant factors affecting the PPE use of mining employees. The model includes the factors that ergonomics, the efficiency of PPE and employee training, and PPE usage habit. The results indicate that ergonomics and employee training have no significant effect (p > 0.05) on the use of PPE. The efficiency of PPE has a statistically meaningful effect (p < 0.05) on the use of PPE. Various variables have been evaluated in previous studies. However, none of them examined the variables simultaneously. The developed model in the study enables to better focus on ergonomics and employee training in the PPE usage. The effectiveness of a PPE makes its use unavoidable. Emphasizing PPE effectiveness in OHS training and even showing them in practice will increase employees’ PPE usage. The fact that a PPE with high effectiveness is also ergonomic means that it will be used at high rates by the employee.

Spontaneous combustion of coal is a complex underground mining disaster, which mainly threats mine safety and efficiency. Several factors usually cause spontaneous combustion of coal such as gas concentration, ventilation, coal properties. In this study, spontaneous combustion tendencies of the coal mines were predicted considering the effective parameters for an underground coal mine in Turkey. The Multinomial Logistic Regression which is a multivariate statistical technique was applied. Gas concentrations (CH₄, CO, O₂) and air velocity were defined as factors affecting spontaneous coal combustion. Fire hazard levels of the coal mines were determined as “normal situation” and “potential combustion”. It was observed that CH₄, CO variables, and CH₄*CO interaction were effective in the formation of clusters. The results indicate that Mine I is more liable to spontaneous combustion than Mine II and Mine III. At the same time, the effects of variations in factors are examined in the study.