Integration of distributed cloud computing to improve coal mining efficiency and monitoring of mining processes

Integration of distributed cloud computing (DCC) offers new opportunities to improve the efficiency and safety of coal mining. The research aims to develop a distributed cloud computing architecture for monitoring of the mining processes and optimization of mining operations. The methodology includes Big Data analysis, mathematical modeling and machine learning. The empirical base consisted of indicators from 15 coal mines in the Russian Federation for 2018-2023 (4.5 million records). Implementation of the distributed cloud computing provides a 25-40% increase in labor productivity, a 30-50% reduction in equipment downtime, and a 95% reduction in accident rates. A 20-30% decrease in the mining costs is achieved along with a 15-25% reduction in the carbon footprint. The level of the process automation increases up to 70-85%. Recommendations are developed for upscaling the distributed cloud computing in the coal industry. The results obtained are significant for the digital transformation of the mining industry.

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Publication Details

Journal
Mining Industry Journal (Gornay Promishlennost)
Published
2025-05-04
DOI
https://doi.org/10.30686/1609-9192-2025-2-82-90
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Integration of distributed cloud computing to improve coal mining efficiency and monitoring of mining processes

E. Voronova, A.Zh. Zubets, E.I. Moskvitina, K.V. Kharchenko et al.
Mining Industry Journal (Gornay Promishlennost)
Advanced Computational Techniques and Applications
article

Integration of distributed cloud computing to improve coal mining efficiency and monitoring of mining processes

E. Voronova, A.Zh. Zubets, E.I. Moskvitina, K.V. Kharchenko, E.V. Razumova
article en

Abstract

Integration of distributed cloud computing (DCC) offers new opportunities to improve the efficiency and safety of coal mining. The research aims to develop a distributed cloud computing architecture for monitoring of the mining processes and optimization of mining operations. The methodology includes Big Data analysis, mathematical modeling and machine learning. The empirical base consisted of indicators from 15 coal mines in the Russian Federation for 2018-2023 (4.5 million records). Implementation of the distributed cloud computing provides a 25-40% increase in labor productivity, a 30-50% reduction in equipment downtime, and a 95% reduction in accident rates. A 20-30% decrease in the mining costs is achieved along with a 15-25% reduction in the carbon footprint. The level of the process automation increases up to 70-85%. Recommendations are developed for upscaling the distributed cloud computing in the coal industry. The results obtained are significant for the digital transformation of the mining industry.

Mining Industry Journal (Gornay Promishlennost)(2/2025)
Openalex Percentile: Top 96%
Advanced Computational Techniques and Applications
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