This article is devoted to the issues of processing and analysis of heterogeneous information related to the functioning of mining transport equipment, which becomes available for analysis within the framework of modern technological operations control systems in open-pit mines. These issues are very relevant to robotized technological operations. The paper gives a brief overview of the modern landscape of the autonomous haulage systems management problems, the features of the platform approach to solving the problem of managing unmanned transport and technological processes in open pits are considered. The concept of an agent-based approach to the modeling of an open-pit mining is described in detail on the basis of the interaction of three systems: technical, infrastructural–technological, and geostructural. Some features of the developed platform architecture integration of heterogeneous information are discussed. The principles of information integration are considered in detail when constructing a dynamic 3D model (digital twin) of infrastructure and technological system elements using large arrays of telemetric data. The results of building digital models of open-pit technological roads are presented. The resulting models are comparatively analyzed in the process of optimizing of the interaction of technical autonomous mobile agents and elements of technological infrastructure.

This work is devoted to the construction and analysis of the functioning of energy efficiency management systems for the technological processes of mining industries. The main idea of this work is to substantiate and describe an approach to the intellectualization of data processing methods and tools used in the operation of energy efficiency management systems. This paper provides a brief overview of the problems of implementing the ISO 50001 standard and provides a justification for the need to bring the energy efficiency management systems prescribed by the standard to an automated form. Functional requirements for the construction of such automated systems for mining industries, considering the use of Industry 4.0 technologies, are formulated. A structural–functional model of the conceptual architecture of the proposed system is given. The problems of the direct integration of computational methods of data mining for the implementation of the required functions are shown. A statistical analysis of the technological information of 11 enterprises is presented, confirming the described problems and the validity of the stated requirements for building the system. Based on the results of the work, steps to eliminate problems and further plans for the modernization of energy efficiency management systems in the industry have been identified.

This article considers one of the approaches to solving the problem of improving the efficiency of the functioning of unmanned open pit transport. The actual data on the movements of robotic dump trucks within the framework of a continuous transport and technological cycle at one of mining sites of a coal mine are analyzed. During the study, the movement times in the loaded and empty states are recorded. In addition, the time of passing by dump trucks of individual sections of the transport route is monitored, in order to empirically determine the speed reserves for each robot. As a result, several options have been obtained to increase the target performance of an autonomous dump truck by changing the speed modes of movement in certain sections. One of the variants is presented in the paper as an illustrative example. The paper also briefly discusses possible approaches to formalizing the procedure for determining the optimal driving modes of robotic dump trucks, depending on the terrain and features of the route as well as the roadbed condition.

The article is devoted to methods and models of designing systems for the digital transformation of industrial enterprises within the framework of the Industry 4.0 concept. The purpose of this work is to formalize a new notation for graphical modeling of the architecture of complex large-scale systems with data-centric microservice architectures and to present a variant of the reference model of such an architecture for creating an autonomously functioning industrial enterprise. The paper provides a list and justification for the use of functional components of a data-centric microservice architecture based on the analysis of modern approaches to building systems and the authors’ own results obtained during the implementation of a number of projects. The problems of using traditional graphical modeling notations to represent a data-centric microservice architecture are considered. Examples of designing a model of such an architecture for a mining enterprise are given.

This article is devoted to the study of the possibilities for improvAzing the quality of energy management systems adopted at open-pit mining enterprises in the Russian Federation. The main idea of the work is to apply stochastic boundary value analysis methods using the production function for individual and integral estimates of the performance of energy-consuming objects when performing various types of technological work. It is shown that mining enterprises are experiencing problems in the field of rational energy consumption due to the lack of strictly formalized ways to determine the frontiers of the efficiency value of the parameter of specific energy consumption (SEC). A justification is given for the need to apply stochastic frontier analysis (SFA) methods and use the Cobb–Douglas production function to account for the nonlinearity and stochasticity of the operating conditions of energy-consuming mining objects. The results of a statistical analysis of the data on the operation of EKG-10 excavators at operating enterprises in Siberia are presented, as well as an assessment of their energy efficiency using the adopted approach based on planning the target value of SEC. The results of computational experiments on constructing an energy efficiency model using the SFA/Cobb–Douglas function for various data segmentation options are presented. Computational experiments have been conducted to compare variants based on the Cobb–Douglas production function and translog function with semi-normal and exponential distribution forms for the same data set. A comparative assessment is given of the approaches to the complex analysis of activities adopted at enterprises and proposed in this study, characterizing potential hidden energy losses in the range from 4.53% to 20.73%.