IT-technologies in design, operation and maintenance of mining machines
A.S. Ivanov1, V.V. Makarova2,3
1 PAO Sberbank, Moscow, Russian Federation
2 Ural State Mining University, Ekaterinburg, Russian Federation
3 Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation
Russian Mining Industry №2/ 2026 p. 114-119
Abstract: The aim of the research was to systematize information on the main application areas of IT technologies in mining engineering, to analyze the efficiency of the solutions implemented, and to identify the main challenges and prospects for development in this field. The relevance of the research is defined by the need to ensure competitiveness of the Russian mining companies in the global market through implementation of advanced digital technologies. An analysis of modern IT solutions is provided, including computer modelling in designing, equipment health diagnostic systems, integration of the sensor technologies and the Internet of Things (IoT) for predictive maintenance. Problems and barriers to implementing digital technologies at mining enterprises are examined, and promising directions for development are identified. It is demonstrated that a comprehensive approach to digitalization of mining production relevant to the Industry 4.0 paradigm, enables improving equipment reliability, optimizing maintenance schedules, and reducing operating costs by 15-25 %. The research results can be valuable for engineers, designers, and managers of mining companies in making decisions on digital technology implementation.
Keywords: IT technologies, mining machinery, CAD/CAM, IoT, sensor systems, predictive maintenance, Industry 4.0, digitalization
For citation: Ivanov A.S., Makarova V.V. IT-technologies in design, operation and maintenance of mining machines. Russian Mining Industry. 2026;(2):114–119. https://doi.org/10.30686/1609-9192-2026-2-114-119
Article info
Received: 28.12.2025
Revised: 09.02.2026
Accepted: 11.02.2026
Information about the authors
Alexey S. Ivanov – Cand. Sci. (Eng.), Director of Digital Technologies, PAO Sberbank, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Valeria V. Makarova – Cand. Sci. (Eng.), Associate Professor, Department of Mining Machines and Complex Equipment, Ural State Mining University, Ekaterinburg, Russian Federation; Associate Professor, Department of Hoisting and Hauling Machines and Robots, Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation; https://orcid.org/0000-0002-4148-5556; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
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