RESULTS OF MODELING PRODUCTION INDICATORS AND CLUSTERING OF LOW-CAPACITY COAL MINES UNDER RESIDUAL RESERVE EXTRACTION CONDITIONS

Purpose. To investigate the production indicators of low-capacity coal mines under various configurations of productive flows in the context of residual reserve extraction. Methods. The Cobb-Douglas production function was applied to model the performance of low-capacity coal mining enterprises. Based on elasticity coefficient determination, modeling of productive flow configurations — coal, methane gas, rock, and water — was carried out for different coal quality indicators. Cluster analysis using dendrogram construction was employed to describe mine operation strategies. Findings. A novel approach to modeling production indicators of coal mining enterprises under residual reserve extraction conditions has been developed. Four operational production scenarios were simulated. It was found that as coal quality increases, its share in the total balance grows regardless of the operational scenario. When coal ash content is below 20%, it is advisable to focus on increasing coal extraction, while the feasibility of processing mining waste decreases, and wastewater treatment becomes inefficient. It was established that at low ash content, coal remains the primary productive flow regardless of extraction volume. Regardless of coal ash content, methane extraction from underground spaces appears to be of questionable benefit for low-capacity coal mines. A range of productive flow configurations for various operational conditions was obtained. Originality. Based on the modeling, four types of low-capacity coal mines were identified according to the configuration of productive flows. For the first time, cluster boundaries were defined and technologically characterized. Classifying an enterprise into a specific cluster enables appropriate strategy development and the application of optimization and production management methods to improve efficiency and rationalize coal field development parameters. Practical implication. The proposed approach, based on the Cobb-Douglas function, was validated for determining productive flow configurations. The hypothesis of productive flow elasticity was confirmed using analytic hierarchy process (AHP) methods. A decision support system in the form of software for modeling the performance of low-capacity coal mines was proposed.