In the context of the rapid development of digital technologies and increasing demands on energy efficiency, sustainability and competitiveness of industrial enterprises, the fuel and energy (FEC) and mineral resources (MR) complexes are undergoing major changes. Digital transformation is becoming a key factor in improving the efficiency, reliability, and sustainability of production processes, as well as an important element of the strategy for technological sovereignty and the modernization of production systems. Modern approaches to managing equipment and process chains are based on the use of machine learning methods, big data analysis, digital modeling, and the creation of digital twins, which, in turn, allows not only the optimization of technological and business processes, but also the formation of new control architectures from local systems to industrial metauniverses.

This article examines the problem of managing ore flow quality at mining enterprises from the perspective of applying big data to improve the efficiency of mineral quality management. It is noted that assessing the feasibility of collecting and processing big data for ore flow quality control requires an optimal quantifiable weight parameter, which determines the data collection discreteness and the effectiveness of their processing. Currently, this parameter is the ore (or concentrate) batch. A scientific-practical approach to determining batch sizes at mining enterprises is proposed, based not on business process conditions, but on the analysis of the distribution of quality parameters within the ore body, considering subsequent methods of mineral raw material transportation. An analysis was conducted on the data from every technological process within the mining technical system, leading to the establishment of principles for calculating the minimum required data samples for each stage of the process. The applicability of the Kotelnikov theorem (Nyquist – Shannon sampling theorem) for determining the optimal quantifiable weight parameter of a mineral raw material batch within quality control frameworks is considered. To obtain a qualitative model, the required scope of quarry operation statistics should range from 16 to 52 months of excavator operation at the face. This range depends on the value of the mineral quality distribution coefficient at the mining enterprise. It was also established that for building a qualitative model, the mentioned coefficient must be considered; the higher its value, the lower the sampling frequency should be when collecting data from technological processing stages.

Long-term activity of mining enterprises causes the necessity to substantiate the strategies of management of the mining and technical system functioning in terms of improvement of ore quality control, which is determined by its change in the course of field development due to the priority development of the main reserves and, as a consequence, forced transition to the mining of complex structural rock blocks with a decrease in the recovery percentage, which is typical in case the ore component meets the requirements of the feasibility study in terms of grade at substandard capacity. In this case, it is possible to identify the recovery percentage and the potential for its increase by analyzing the long-term activity of the mining and industrial enterprise, namely, by analyzing the data of mining complex structural rock blocks with the subsequent establishment of the relationship between the primary data on mining and geological conditions and information on the quality of the mineral obtained from the technological equipment. Therefore, the purpose of the research was to substantiate the necessity of improving the management strategy of the mining-technical system functioning, which consists in the fact that on the basis of analyzing the mining data of complex structural rock blocks it is possible to determine the ore mass losses and their quantity and to lay the basis for the development of decisions on its extraction. For this purpose, the collected data on the mining of complex structural rock blocks, accounting the geological and industrial type of extracted ores, were considered in modeling the conditions and studying the parameters of technological processes, the implementation of which provides additional products. It was revealed that the ore mass from substandard thickness layers is delivered to the dumps, and ore mass losses have been estimated at 25-40 % per year. It is proved that determination of ore mass losses based on the analysis of data on mining of complex structural rock blocks, as well as timely solution of this issue can significantly increase the production efficiency of mining and technical system. Taking into account for the results obtained, the options for optimizing the production of the mining and engineering system were proposed.