An integrated evaluation based on the entropy weight and grey clustering methods to improve safety in mines

The analysis of mine safety indicators using a scientific method can improve mine safety and assist management in making informed decisions. This research establishes a mine safety evaluation index and proposes an integrative evaluation model based on the entropy weight and grey clustering methods. The index consists of 27 indicators classified into seven criteria: working environment (A), miners’ attributes (B), safety policies and education (E), prevention and control (F), and monitoring and supervision system (G). Using Pakistan’s mine safety situation as a case study, the proposed model categorized the indicators into five safety levels (very low, low, medium, high, very high) for the present situation and for their relevance in terms of future safety improvement. The results show all of the criteria falling into the very low level for the current mine safety situation. Three of the criteria — C, E and G — are identified as having very high levels of significance for future safety improvements.