Enhancing Mining Enterprise Energy Resource Extraction Efficiency Through Technology Synthesis and Performance Indicator Development

Abstract

The extraction of minerals continues to face rising costs, but advancements in engineering and technology help reduce these costs, making efficiency improvement a critical goal for mining enterprises. The integration of additional technologies is one approach to achieving increased efficiency, though it presents challenges in accounting for the parameters of these technologies and determining their influencing factors. This paper proposes a methodical approach to developing performance indicators for mining enterprises under such conditions. Based on previous research, the mining enterprise is divided into subsystems, allowing for detailed analysis and the creation of indicators that represent the overall operations. Scientific studies on the definition and application of indicators in production enterprises are examined and adapted to mining enterprises, where the synthesis of multiple technologies is feasible. The paper introduces a methodology for determining integral performance indicators, which is tested through a case study using the “Heroiv Kosmosu” mine, applying both traditional longwall coal mining and coal seam well gasification technologies. This selection of technologies facilitates a detailed description of the necessary equipment, extraction methods, and organizational measures for safe operations. It also offers insights into the potential for scaling the analysis of multiple technologies operating simultaneously. The integration of a consistency coefficient in the model allows for more accurate final values of the indicators, reflecting their qualitative homogeneity.

1. Introduction

One of the main factors that leads to the growth of costs in the underground development of minerals is their exhaustion, which complicates extraction each year, increasing costs and other dependent factors [1]. However, technical and economic development partially neutralizes such negative impacts [2]. In addition to mineral exhaustion, unforeseen factors such as the deterioration of mining or geological conditions and economic fluctuations also lead to increased costs [1,3]. These challenges affect the planned development of an enterprise and force its management to seek and more intensively implement various innovations at all stages of mining [4]. One such innovation is the introduction of additional technology designed to ensure planned performance indicators.

Indicators must reflect the current state of the mineral development project by using the most recent data and being updated at appropriate intervals [5]. A comprehensive approach should be taken considering all aspects of mineral development, including exploration, extraction, processing, and environmental impact [6]. Indicators should cover economic, technical, environmental, and social dimensions while recognizing the interdependencies between them. They should be adaptable to different scales of operations and flexible enough to accommodate technological advancements and changes in project scope [7]. Economic viability is crucial, so indicators should assess the project’s economic viability, considering the cost-per-ton of material processed, return on investment (ROI), and net present value (NPV) [8]. Market conditions and commodity price fluctuations must also be factored into economic indicators. Environmental and social impacts are equally important; therefore, indicators should measure aspects of the environmental footprint, such as emissions, water usage, and land disturbance, and include lifecycle analysis for a comprehensive assessment. Social impact indicators should evaluate job creation, health and safety, and effects on cultural heritage. Risk assessment is another critical area, requiring indicators that help manage risks associated with geological, market, and operational factors [9]. Sensitivity analysis should be used to understand the impact of variable changes on overall project viability [8,10]. Lastly, regulatory compliance is vital, so indicators should monitor adherence to all relevant regulations and standards, including environmental laws, safety regulations, and labor laws [11].

Given these complexities, it is necessary to pay more attention to the interaction of all subsystems and the overall efficiency of mining enterprises. This includes exploring and applying modern development technologies, improving management efficiency, enhancing equipment productivity, and ensuring the economic validity of decisions. These factors necessitate the invention of a method to synthesize performance indicators effectively. Numerous technologies are available for underground mineral mining, so for illustration, we will choose two fundamentally different coal technologies that can coexist within the same mining enterprise: traditional longwall coal mining extraction and borehole gasification of a coal seam. Based on these, the necessary sets of relevant indicators for technologies and their subsystems can be formed [12].

The synthesis of mineral development technologies involves integrating various scientific, technical, and economic factors [2]. When forming indicators for analysis in this context, it is essential to ensure they are relevant, accurate, and useful for decision-making. Indicators should align with the objectives of the mineral development project and cater to the needs of stakeholders, providing valuable insights. They must be based on quantifiable data with standard units to ensure consistency and comparability, and processes for validating and verifying data should be implemented to maintain accuracy and reliability.

The problem of determining performance indicators for enterprises engaged in efficient mineral extraction has only been addressed by a relatively small number of researchers. However, significant advancements have been made by several scientists who have developed various methods to determine these performance indicators and improve enterprise efficiency. Notable contributions have been made by researchers such as R.O. Dychkovsky, M.S. Surgai, S.M. Honcharenko, A.V. Sokolovskyi, and N.V. Sokolov, among others. The scientific principles behind combining coal mining technologies for weakly metamorphosed rocks were focused on in work [12]. This research provided foundational knowledge that has been crucial for advancements in this specific area of mining technology. It contributed to creating an information model of mine operations. This model was pivotal in determining key performance indicators, allowing for a more systematic and analytical approach to mine management and efficiency [13].

Developing a technical and economic model for mining and ore enterprises is a current task for mining operating. Through such a model, it is possible to define strategic decisions for enterprise development by utilizing performance indicators, thereby aligning technical processes with economic outcomes [5,14]. Recent research made strides in defining the parameters necessary for the efficient operation of mining enterprises, particularly quarries [15,16]. These works enabled the combination of various technological processes, leading to more effective and streamlined operations [17]. Well-known publications by N.V. Sokolov are focused on developing a comprehensive system of indicators for industrial enterprises [18]. His approach aims to enhance the sustainability of these enterprises by focusing on technological work cycles and their respective indicators, ensuring a more resilient and efficient operational framework.

The collective achievements of these scientists and their peers have provided a robust foundation for the authors of this article. Building on this foundation, the authors have developed their own vision for the simultaneous operation of multiple technologies within a single enterprise. They have employed a wide array of technical and technological indicators to create novel approaches for evaluating performance across all subsystems. This comprehensive evaluation framework has facilitated both theoretical advancements and practical applications in the field of mineral extraction and enterprise efficiency.

2. Research Methods for Studying

Forecasting the economic efficiency of a mining enterprise with the simultaneous use of several technologies can be effectively performed for each subsystem separately. This approach allows researchers to cover the mining and geological features of mineral formation and the full range of equipment operation, technological features, and economic and organizational factors. In this way, an information model is created that connects all the influential indicators of the enterprise and allows researchers to combine them into a common calculation system [19,20]. Therefore, determining the indicators of the production enterprise for the studied technologies becomes one of the main tasks of this research, and the works of scientists in this direction help to determine their own approaches. So, let us consider their main achievements.

A substantial amount of data regarding coal seams in Ukraine were collected, analyzed, and processed [21]. The research offers a comprehensive overview of coal seam characteristics, providing valuable insights into further geological and technological investigations. Accordingly, the author analyzed and researched the rate of change in the reliability of the enterprise’s work overtime. As a result of the analysis of the mine performance indicators, Surgay N.S. established that the rate of decrease in the reliability of the enterprise’s work increased due to the decrease in efficiency depending on the planned level and decreased linearly with the increase in the actual level of production.

A fundamental study defines the efficiency indicators of a mining enterprise, and the system of technological indicators of its operations is considered in comparison with the ideal performance parameters of the mining enterprise [22]. The author selected from all indicators those that had the greatest impact on the efficiency of his work and combined them into three groups: mining and geological, technological, and organizational. On the basis of this group of indicators, the company’s development strategy was chosen, and a complex selection criterion f(xj) = d(xij, xiopt)/Prj was implemented, which included the measure of proximity d(xij, xiopt) to the ideal point and the probability of implementation Pr of strategic alternative j [22,23]. The following formula was used to determine the degree of proximity, which allows one to calculate the distance between the ideal and actual points:

$$d\left(x_{ij},x_{iopt}\right)=\sqrt{{{\displaystyle \sum }}_i^n{k}_i{\left(x_{ij}-x_{iopt}\right)}^2} i=1, 2 \dots n$$

(1)

where ki is the weighting coefficient for each relevant parameters reflecting the structure of preferences of strategic decision-makers; i is the research enterprise; and n is the number of enterprises under consideration. In other words, the author developed a modernized calculation algorithm using the “ideal point” method.

The direction of modernization of a mining enterprise was determined through a search for optimal work parameters [24,25]. For this purpose, the parameters were divided into three groups: technological—mode of mining operations and construction of the quarry space; technical—the balance of the technological chain and the intensity of cargo flows; and organizational—the structure of personnel by functions and qualifications and the rhythm of technological processes. The set of presented parameters, in the opinion of the author, ensured the completeness and reliability of the assessment of the state of the mining enterprise and the choice for the direction of its modernization. In addition, in the case of significant changes in the factors of the external environment, especially those taking into account design decisions, the economic and technological expediency of the reconstruction of the mining enterprise was considered. The authors claimed that during modernization, the stability of the operation of a mining enterprise decreases and the risk of its economic condition deteriorates. Therefore, necessary solutions are provided that increase the efficiency and stability of functioning at transitional stages. Otherwise, there is a contradiction between the need for continuous development and the desire to preserve the sustainability of the mining enterprise.

Also, researchers have presented a comprehensive assessment of a company’s indicators that affect its sustainable development [25,26]. A list of indicators that characterize the main elements of the technological process include the level of qualification of performers, the maneuverability of the workplace regarding the development of matrices for mastering operations, and maps of organizational and technological modules that allow for the creation of a data bank of the innovative potential of the enterprise [26,27]. The main direction of the development strategy is the determination of the main data and factors for increasing the stability of technological processes in the market conditions of development. The application of a systems approach to the analysis of indicators makes it possible to regulate the internal structures of technological processes and the interaction of their elements at the stage of technological preparation of production.

Examples of determining indicators in proposed diagnostic models for assessing both the internal and external sustainability of an enterprise are presented in [28,29]. These models are based on a comprehensive system of economic indicators, which account for the influence of various factors from both the internal and external environments. By analyzing these indicators, the authors were able to develop a conceptual framework for diagnosing the economic sustainability of an industrial enterprise. Additionally, this framework allowed for the evaluation of the economic attractiveness of the enterprise, considering a range of variables that affect its performance. This conceptual model has been referenced in other studies, further validating its relevance and applicability in the field [8,30].

And the last example of application is the candidate work of A.A. Aroshidze [31]. This author developed a methodology for assessing the economic sustainability of an enterprise’s work and conducted a data analysis based on available activity indicators. The key feature of this methodology was a two-component assessment based on the criteria selected within the developed framework of the approach to understanding economic sustainability. The basis of the comparison included the indicators factored into the company’s development plan. This approach made it possible to identify, evaluate, and analyze the development of crisis processes in the company’s activities by developing a set of signals, calculating their scale and intensity.

As mentioned, there is a wide range of technologies available for the underground development of minerals. To define the relevant indicators more clearly, we will narrow the focus to the combination of two technologies used within a single mining enterprise for coal development: traditional longwall coal mining extraction and borehole gasification technology for coal seams [32].

Subsystem: Mineral Exploration. This subsystem includes the study of the mining and geological conditions of the deposit and the determination of the quantity and quality of these reserves. The overall integral indicator of this subsystem will be determined as a function of the defined complex indicators Ri, their weights Ki, and the number of these indicators n, yielding Rexp = f(Ri) = ΣRiKi/n. Based on the specified parameters, it becomes possible to evaluate the geoeconomic parameters of natural resources and the use of raw materials (Figure 1).

Subsystem: Equipment. This subsystem comprises the set of machines and mechanisms essential for the opening, preparation, extraction, transportation, and storage of mined materials. These machines support the primary function of the mining enterprise—mineral extraction through mining equipment. The focus will be on parameters that ensure comprehensive mechanization. These indicators are defined by the technical and operational characteristics of the key types of machines and mechanisms that influence the performance parameters of their operations. The emphasis will be placed on equipment that significantly impacts the productivity of mining processes, while auxiliary equipment will be adjusted using coefficients. The overall integral indicator of this subsystem will be determined as a function of the defined complex indicators (Ci), their weights (Ki), and the number of these indicators (n). Therefore, the equation for this subsystem will be expressed as Ceq = f(Ci) = ΣCiKi/n.

Considering the technology of coal extraction using mechanized complexes with harvesters, the following complex indicators will be taken into account: C1—the regulation of the productivity of the mechanized complex, taking into account a number of parameters for this; C2—the determination of the performance of the equipment to ensure the performance of preparatory work, which takes into account the corresponding performance of the tunnel complex used; and C3—the productivity of the equipment for transporting mining mass within the mine field [33].

3. Results and Discussion

3.1. Geotechnological and Technological Indicators

In the case of geotechnological mining, the following complex indicators are used: C4—the productivity of drilling machines and mechanisms that provide access to the mineral [34], which takes into account the depth of drilling operations, the speed of rotation of the working body, the overall speed of drilling, the diameter of the bit, indicators of drilling complexity, the performance of equipment for arranging and testing wells before use, etc., and C5—the pumping of the mineral from the mining site to the surface and the supply of a steam–oxygen mixture for blowing to the pit, which includes the power of the pumps, the depth of the work, the working diameters of the receiving and supply pipes, the maximum pressure difference, etc.

Considering the specified technical characteristics of the equipment used, we will group them and depict them based on connections of the specified elements within the entire technical subsystem (Figure 2).

Subsystem: Technologies. This subsystem includes parameters that ensure technological processes of disclosure and production. Since this article examines the development of a mineral deposit using the example of two fundamentally different technologies for the extraction of a mineral from coal, we will determine the methods of discovery and preparatory work for these two technologies. The overall integral indicator of this subsystem will be determined as a function of the defined complex indicators Ti, their weights Ki, and the number of these indicators n, where Tth = f(Ti) = ΣTiKi/n.

3.2. Technological and Economic Performance Analysis

Considering the technology of coal extraction using mechanized complexes with harvesters, the following complex indicators of the technology will be taken into account: T1—preparation for the extraction of a mineral, which includes opening and carrying out preparatory work, which will depend on the sequence of operations that provide access to the mineral, the volume and duration of discovery works, the technology for conducting preparatory productions, and the used pilot complex; T2—the extraction of mining mass, which is provided by a set of mineral extraction processes, taking into account the productivity of mining sites, the number of cleaning pits, the thickness of layers, stoping face length, the density of the mineral, and others; and T3—the efficiency of transportation within the enterprise, which takes into account the load of the transport network.

And in the case of geotechnological mining, the following complex indicators are used: T4—mineral extraction, which takes into account the technological efficiency of mineral extraction, including the actual yield of fuel gas, the width of the pillar or strip, the capacity of the formation, the linear rate of gasification of the coal wall of the fire pit, the output of the gas mixture from the unit mass of coal, the volumetric mass of coal, etc.; T5—the pumping of gas through the transport network of pipeline transport, where the level of use of technological parameters of the entire transport network is taken into account; and T6—the enrichment of the obtained raw materials, where the amount of fuel gas obtained after extraction from extraneous fractions is taken into account.

Based on the determined technological parameters for both technologies under consideration, we determine the complex indicators of their operation (Figure 3).

Subsystem: Economy. This subsystem includes parameters that allow us to determine the costs of exploration, development, preparation, extraction, transportation, beneficiation, and support work for both technologies. From real-world experience and based on the methodology [35], all costs will be described by the cost of the work, materials used, the number of depreciation deductions for equipment, wages, and depreciation deductions for all components. The overall integral indicator of this subsystem will be determined as a function of the defined complex indicators Ei, their weights Ki, and the number of these indicators n, such that Eec = f(Ei) = ΣEiKi/n.

3.3. Economic Efficiency and Cost Evaluation

Considering the technology of coal extraction using mechanized complexes with harvesters, the following complex indicators will be taken into account: E1—the economic efficiency of geological exploration works, which is determined by the costs of the work, which are attributed to the unit volume of the mineral in the massif; E2—the economic efficiency of mining and capital works, which is determined by the costs of carrying out production over a unit of length and is considered in the total costs; E3—the economic efficiency of mining and preparatory works, which is determined by the costs of excavation work and maintenance for production over a certain unit of length relative to the total length; E4—the economic efficiency of costs for clean mining, characterized by the costs of materials, current repairs, electricity, and transportation within the mining area assigned to a unit of mass or volume of a mineral; and E5—the economic efficiency of moving a certain amount of mining mass, including storage and transfer per unit length. And with geotechnological extraction, the following complex indicators are used: E6—the economic efficiency of gas pumping, where the cost of moving the mixture of gases from the coal seam to the surface is taken into account and is attributed to the unit of total costs, and E7—the economic efficiency of cleaning the resulting mixture of gases from non-combustible impurities per unit volume of the final product.

Based on the determined costs for both technologies, we determine the comprehensive indicators of their operation within the limits of this subsystem (Figure 4).

3.4. Organizational and Management Dynamics

Subsystem: Organization. For this subsystem, we refer to the system of connections and relations within one mining enterprise and its organization [36]. All participants in this process play an important role, from the lower level of managers to the head of the enterprise. The overall integral indicator of this subsystem will be determined as a function of the defined complex indicators Oi, their weights Ki, and the number of these indicators n, where Oorg = f(Oi) = ΣOiKi/n.

These indicators are common to the two technologies under consideration. Therefore, the following comprehensive indicators will be taken into account: O1—compliance with the rules, which takes into account the rules of mineral extraction and compliance with labor protection rules and the monitoring of compliance, including the number of accidents and other disciplinary sanctions for non-compliance with these rules; O2—the level of performance of assigned tasks, which takes into account the number of issued and completed tasks; O3—the level of continuous operation of equipment and workers, which takes into account the occurrence of unexpected stops and downtime for both equipment and workers; O4—the level of implementation of proposals, which takes into account the number of proposals, their effectiveness, and the levels of implementation and rejection; and O5—the quality of finished products, which takes into account planned and unplanned work and measures to improve the quality of finished products.

A similar definition of indicators for assessing the level of managerial activity and the levels of managers themselves allows us to visualize the structure of their influence (Figure 5).

The values and weights presented in

Table 1. Indicators for the mineral exploration subsystem.

No.	Complex Indicator	Components of the Complex Indicator	Value/ Weight	Rexp
1	Level of exploration costs, R1, units	Cost of exploration	0.9/0.3	0.885
	Level of total costs from the extraction of minerals
2	Level of preliminary exploration, R2, units	Exploration level	0.8/0.7
	Ratio of mineral exploration to production for the year

,

Table 2. Indicators for the equipment productivity subsystem.

No.	Complex Indicator	Components of the Complex Indicator	Value/ Weight	Ceq
1	Extraction of minerals, C1, units	Productivity of mining operations	0.8/0.3	0.421
	Efficiency of using mining equipment for the main technology
2	Carrying out preparatory work, C2, units	Productivity of preparatory works	0.7/0.2
	Effectiveness of the use of drilling equipment during mining operations for the main technology
3	Transportation of minerals, C3, units	Productivity of transport vehicles	0.7/0.1
	Efficiency of using the transport network for the main technology with an average transport length of 4500 m
4	Massif drilling, C4, units	Productivity of drilling machines	0.7/0.2
	Effectiveness of using drilling machines for additional technology
5	Pumping through pipelines, C5, units	Pumping through pipelines	0.7/0.2
	Efficiency of using mineral transportation through pipelines for additional technology

,

Table 3. Indicators for the technological subsystem.

No.	Complex Indicator	Components of the Complex Indicator	Value/ Weight	Tth
1	Preparation for opening and carrying out mine workings, T1, units	Preparation for opening and carrying out mine workings	0.7/0.1	0.332
	Effectiveness of the use of the technological subsystem before opening and production using the main technology
2	Extraction of rock mass, T2, units	Mining productivity	0.8/0.2
	Efficiency of mineral extraction using the main technology
3	Efficiency of transportation technology within the enterprise, T3, units	Congestion of the transport network	0.6/0.2
	Load of the transport network according to the main technology
4	Mineral extraction, T4, units	Technological efficiency of mineral extraction	0.8/0.1
	Efficiency of mineral extraction by the additional technology
5	Gas pumping of the transport network, T5, units	Level of use of technological parameters in the transport network	0.6/0.2
	Efficiency of using the transport network for the additional technology
6	Enrichment of the obtained raw materials, T6, units	Amount of gas obtained after purification	0.7/0.2
	Efficiency of gas purification by additional technology

,

Table 4. Indicators for the economic subsystem.

No.	Complex Indicator	Components of the Complex Indicator	Value/ Weight	Eec
1	Economic efficiency of geological exploration works, E1, units	Expenditures for geological exploration work, which are determined by the costs of work and attributed to the unit of volume of mineral in the massif	0.7/0.1	0.274
	Ratio of costs to the maximum in the industry
2	Economic efficiency of mining and capital works, E2, units	Expenditures for mining and capital works, which are determined by the costs of carrying out production over a unit of mine working length and are added to general costs	0.9/0.1
	Ratio of costs to the maximum in the industry
3	Economic efficiency of mining and preparatory works, E3, units	Expenditures for mining preparatory work, which is determined by the costs of excavation work and maintenance over a unit length of production, added to the general costs	0.8/0.1
	Ratio of costs to the maximum in the industry
4	Economic efficiency of cleaning works, E4, units	Expenditures for clean mining at the expense of materials, current repairs, electricity, transportation within the mining area	0.8/0.2
	Ratio of costs to the maximum in the industry
5	Economic efficiency of mining mass movement, E5, units	Costs for the movement of rock mass, storage, and separation of the movement of rock mass into streams attributed to the unit of the length of production, added to the general costs	0.8/0.1
	Ratio of costs to the maximum in the industry
6	Economic efficiency of gas pumping, E6, units	Costs for moving the mixture of gases from the coal seam to the surface, per unit length	0.8/0.2
	Ratio of costs to the maximum in the industry
7	Economic efficiency of gas purification, E7, units	Costs for cleaning the resulting mixture of gases from non-combustible impurities per unit volume of the final product	0.4/0.2
	Efficiency of gas purification after enrichment compared to the maximum in the industry

and

Table 5. Indicators for the management activity level subsystem.

No.	Complex Indicator	Components of the Complex Indicator	Value/ Weight	Oorg
1	Level of compliance with the rules, O1, units	Compliance with the rules of mineral extraction and labor protection is taken into account	0.9/0.3	0.472
	Level of compliance with the rules of mineral extraction and labor protection is among the best enterprises in the industry
2	Level of assigned tasks performance, O2, units	Number of issued and completed tasks is taken into account	0.8/0.2
	Ratio of the number of issued to the number of completed tasks
3	Level of continuous operation, O3, units	Occurrence of unplanned downtime of equipment and workers that affects continuous work	0.9/0.1
	Ratio of continuous work of equipment and workers
4	Level of proposal implementation, O4, units	Implementation of rational proposals and new technology, which includes a corresponding increase in work efficiency	0.7/0.2
	Effectiveness of implementation of rational proposals regarding technologies and new equipment
5	Grade of finished products, O5, units	Work on improving the quality of finished products, which includes the number of defects from the total number of products	0.9/0.2
	Effectiveness of work on improving the quality of finished products

are derived from data obtained from the “Heroiv Kosmosu” mine. These data were collected through operational records and technical assessments conducted at the enterprise. The analysis included key performance metrics such as production output, geological reserves, equipment utilization, process planning, and financial performance, ensuring a comprehensive evaluation of the mine’s operations.

Indicators were categorized into technical, economic, technological, and operational groups, with a weighted scoring system reflecting their relative importance. Normalization techniques were used to ensure comparability, and weighted aggregation methods were applied to derive integral indicators for each group.

To validate the reliability of the indicators, a consistency coefficient was introduced, linking the total number of complex indicators in each subsystem to the final integral indicator. The results of these calculations provided valuable insights into the mine’s performance, allowing for the formulation of recommendations aimed at enhancing operational efficiency, technological advancement, and economic sustainability.

To adjust the obtained integral indicators, we apply the consistency coefficient, which connects the total number of complex indicators in each subsystem to the final integral indicator within that subsystem. The consistency coefficient is calculated based on the number of complex indicators in each table. It reflects the degree of agreement between different evaluation criteria, ensuring a balanced assessment of mining conditions. The calculated values of the consistency coefficients and the final integral indicators are presented in

Table 6. Adjustment of calculated integral indicators taking into account the number of parameters in each subsystem.

No.	Integral Indicator Name	Calculated Value of the Integral Indicator	Coefficient of Consistency	Integral Indicator Value
1	Mineral exploration, Rexp	0.885	1.0	0.885
2	Equipment productivity, Ceq	0.421	1.4	0.589
3	Technological subsystem indicators, Tth	0.332	2.5	0.831
4	Economic subsystem indicators, Eec	0.274	3.0	0.823
5	Organizational subsystem indicators, Oorg	0.472	1.7	0.802

.

According to the approaches used in mining enterprises and generally known mathematical principles of analysis, the coefficients presented above in the table vary within the range of 0.0 to 1.0. The characteristic economic attractiveness of a mining enterprise can be classified as follows:

-

0.0–0.3—The mine does not invest funds and primarily utilizes existing technologies. Such enterprises are relatively stable but have been practically closed to innovation. In Ukraine, this situation is typical for state-owned mining enterprises.

-

0.31–0.60—These enterprises fall into the category of mines with a moderate level of adoption of technical and technological innovations. Financially, such mining enterprises are also of a medium level. They focus their improvements primarily on implementing, and in many cases purchasing, used equipment from more stable mines, including foreign ones.

-

0.61–1.0—Mines that rank among the top 10 in the national ranking. These are economically independent enterprises. They involve the most advanced mining equipment for production processes. Additionally, they invest in acquiring innovative solutions and services from leading global consulting firms.

For the mineral exploration subsystem, the integral indicator has a value of Rexp = 0.885. With this value, the indicator characterizes favorable mining and geological conditions for the extraction and of high-quality minerals with the possibility of the simultaneous application of two mineral extraction technologies within one mine field.

For the subsystem, the equipment performance integral indicator Ceq = 0.589. With this value, the indicator is characterized by using a sufficiently large number of low-performance machines and mechanisms, and there is a partial load of transport and logistics chains for the first technology and relatively greater efficiency for the additional technology, since it is less demanding and technological. For the technology subsystem, the integral indicator Tth = 0.831. With such value, this indicator is characterized by high efficiency and synthesis of technologies for coal extraction with longwall face equipment and the geotechnological degassing of fuel gases.

For the economic subsystem, the integral indicator Eec = 0.823. With this value, the indicator is characterized by balanced costs, and the introduction of additional technology will require significant investments in the enterprise, which will subsequently increase its competitiveness and overall efficiency.

For the organizational subsystem, the integral indicator Oorg = 0.802. With this value, the indicator is characterized by a high level of performance by management personnel in their functions, but at the same time, the complexity of management increases due to the synthesis of two technologies. However, such a high level of performance should compensate for management difficulties that may arise during work.

Thus, for each subsystem, a wide list of indicators was considered, and complex indicators were determined among them. Accordingly, it becomes possible to use them for further determination and conducting appropriate modeling both for the subsystem separately and for the entire enterprise operating or preparing for the introduction of additional technology. In future work, with the help of complex indicators, it is planned to use machine learning methods to balance factors and determine the parameters for effective mineral extraction. The following goals are proposed:

-

To identify negative trends in the qualitative and quantitative indicators of the activity of the mining enterprise;

-

To establish the main groups of factors affecting the efficiency of the enterprise;

-

To justify development scenarios for the technological improvement of the company’s activity;

-

To determine the sequence of measures aimed at increasing the efficiency of the equipment at the enterprise;

-

To justify tactical and strategic management decisions to regulate the work of the enterprise.

4. Conclusions

The paper analyzes the work of scientists who researched the indicators of manufacturing enterprises and developed their own methods for determining the parameters that can be used to calculate the efficiency of industrial enterprises. Based on this and their own experience, the authors of this article developed an individual methodology for determining indicators for the simultaneous extraction of a mineral using several technologies within the limits of one production enterprise. The methodology was verified by calculations using the example of the traditional technology of longwall coal mining extraction and the borehole gasification of the coal seam for the conditions of the “Heroiv Kosmosu” mine. Such a choice of technologies made it possible to describe the equipment that can be used, to determine the features of the mining method for each technology, and to highlight the parameters of the necessary organizational measures that ensure the safe conduct of mining operations. This helps to elucidate the prospects of transferring such an approach to analysis considering the simultaneous operation of several technologies to different types of enterprises. Due to the selected technologies, it was possible to take into account a number of features, identify a specific number of influencing factors, and calculate the initial integral indicators, and due to the introduction of the consistency coefficient, it was possible to take into account the values of complex indicators for each subsystem and adjust the final values of the integral (enlarged) indicators, which can finally reflect their degree of qualitative homogeneity. This approach offers modern possibilities for classification using machine learning methods for the successful use of technology synthesis at mining enterprises. In addition, each indicator was described within all subsystems, and while the number of indicators was different in each, within the subsystem, they form a more concise list of complex indicators that can be used to calculate the effectiveness of the functioning of separate technologies during synthesis.