Big Data as a Product of the Preparation Plant: Reality and Prospects in the Case of Coal
Abstract and keywords
Abstract (English):
The article examines the current and future flow of preparation’s plant production processes and how they contribute to the generation of Big Data. It is shown that as the level of automation in the plant increases, the data produced becomes more extensive and varied. At the same time, it is possible to achieve a level when the generated information flows meet the criteria of the Big Data. As a basic example, a typical coal processing plant is used. The main sources, volumes, variety and speeds of data transfer to the processing plant are described and analyzed.

big data, preparation plant, coal, mining industry, automation, information technology
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1. Abrarov A. D., Datsiev M. S., Chikildin D. E., et al. Optimization of bulk flotation process at Talnakh Concentrator based on machine learning algorithms // Tsvetnye Metally. 2022. Vol. 2. P. 87-93. DOI: (in Russian).

2. Antipenko L. A., Sarin N. G. Automated Plant - Coal Processing Plant of the Future // Mining information and analytical bulletin. 2017. No. 2. P. 5-13. (in Russian).

3. Approved by order of the Federal Environmental, Industrial and Nuclear Supervision Service No. 428 dated October 28, 2020. Safety rules for processing, enrichment and briquetting of coal. Moscow: Federal Service for Environmental, Technological, Nuclear Supervision, 2020. 149 p. (Federal Industrial Safety Code). (in Russian).

4. Approved by order of the Government of the Russian Federation of June 13, 2020 N 1582-r. Program for the development of the Russian coal industry for the period up to 2035. Moscow: Government of the Russian Federation, 2022. (Development Program). (in Russian).

5. Aslanova I. V. Mes as the basis for the development of enterprise process control systems // Russian entrepreneurship. 2017. Vol. 18, no. 11. P. 1651-1658. (in Russian).

6. Avdokhin V. M. Coal cleaning. Volume 1. Processes and Machines. Gornaya kniga, 2012. P. 424. (in Russian).

7. Barnewold L., Lottermoser B. G. Identification of digital technologies and digitalisation trends in the mining industry // International Journal of Mining Science and Technology. 2020. Vol. 30, no. 6. P. 747-757. DOI:

8. COP26: Glasgow Climate Pact: tech. rep. / UN Climate Change Conference. Great Britain, Glasgow, 2021. (in Russian).

9. Dean J., Ghemawat S. MapReduce: Simplified Data Processing on Large Clusters // Communications of the ACM. 2008. Vol. 51, no. 1. P. 107-113. DOI:

10. Dovgal V., Kuizheva S. Using Big Data Technology to Protect the Environment // Russian Journal of Earth Sciences. 2022. Vol. 22, no. 5. P. 1-5. DOI:

11. Energy Bulletin. Prospects for the global coal market / ed. by A. Golyashev, A. Kurdin, A. Kolomiets, et al. Analytical Center under the Government of the Russian Federation, 2021. (in Russian).

12. Energy Institute. The EI Statistical Review of World Energy 2023. 2023. (date of access 10.07.2023).

13. Flotation Operator Digital Twin Project. 2019. (date of access 01.02.2022), (in Russian).,

14. Global Change Data Lab. Electricity production by source, World. 2022. (date of access 10.07.2023).

15. GOST 17321-2015. Coal. Enrichment. Terms and Definitions. Moscow: Standartinform, 2016. 11 p. (Interstate standard). (in Russian).

16. Gvishiani A. D., Dobrovolsky M. N., Dzeranov B. V., et al. Big Data in geophysics and other geosciences // Izvestiya, Physics of the Solid Earth. 2022. No. 1. P. 3-34. DOI: (in Russian).

17. Gvishiani A. D., Panchenko V. Y., Nikitina I. M. Big Data Systems Analysis for Geosciences // Vestnik RAS. 2023. Vol. 6, no. 93. P. 518-525. DOI: (in Russian).

18. ITS 37-2017 "Coal mining and enrichment". ITS 37-2017 "Coal mining and processing". Moscow: Buro NDT, 2017. 294 p. (Information and Technical Guide to Best Available Techniques). (in Russian).

19. Jones D. Global Electricity Review 2021. 2021. (date of access 04.02.2022).

20. Khasanov M. M., Prokofiev D. O., Ushmaev O. S., et al. Promising Big Data technologies in oil engineering: the experience of Gazprom Neft // Oil industry. 2016. No. 12. P. 76-79. (in Russian).

21. Kondratyev V. B., Popov V. V., Kedrova G. V. Global coal market: current situation and perspectives // Mining Industry Journal (Gornay Promishlennost). 2019. Vol. 144, no. 2/2019. P. 6-12. DOI: 144-6-12. (in Russian).

22. Kuchumova A. Coal cleaning rates. 2021. (in Russian).

23. Lukichev S. V. Digital past, present, and future of mining industry // Mining Industry Journal (Gornay Promishlennost). 2021. No. 4. P. 73-79. DOI: (in Russian).

24. Mayer-Schoenberger V., Kukier K. Big data. A revolution that will change the way we live, work and think. Moscow: Mann, Ivanov, Ferber, 2014. P. 240. (in Russian).

25. Odintsova A., Gvishiani A., Nakicenovic N., et al. The world’s largest oil and gas hydrocarbon deposits: ROSA database and GIS project development // Russian Journal of Earth Sciences. 2018. Vol. 18, no. 3. P. 1-14. DOI:

26. Osipov E. How to make friends between industry and big data. 2019. (date of access 14.04.2022).

27. Petrenko I. E. Russia’s coal industry performance for January - December, 2022 // Ugol’. 2023. No. 03. P. 21-33. DOI: (in Russian).

28. Pure Ore Project. 2019. (date of access 01.02.2022), (in Russian).

29. Ravat F., Zhao Y. Data Lakes: Trends and Perspectives // Lecture Notes in Computer Science. Springer International Publishing, 2019. P. 304-313. DOI:

30. Reinsel D., Gantz J., Rydning J. The Digitization of the World. From Edge to Core. 2018. (date of access 14.02.2022).

31. Rylnikova M. V., Klebanov D. A., Makeev M. A., et al. Application of artificial intelligence and the future of big data analytics in the mining industry // Mining Industry Journal (Gornay Promishlennost). 2022. No. 3/2022. P. 89-92. DOI: (in Russian).

32. Samorodova L., Lyubimov O., Yakunina Y. Application of SCADA Systems in the Coal Mining Industry // Proceedings of the 8th Russian-Chinese Symposium "Coal in the 21st Century: Mining, Processing, Safety". Atlantis Press, 2016. DOI:

33. Schernikau L. Economics of the International Coal Trade. Springer International Publishing, 2016. P. 463. DOI:

34. Soofastaei A. Data Analytics Applied to the Mining Industry. 1st. CRC Press, 2020. P. 272.

35. Reinsel D., Gantz J., Rydning J. The Digitization of the World. From Edge to Core. - 2018. - URL: (visited on 02/14/2022).

36. The International Energy Agency. Coal 2022. Analysis and forecast to 2025. 2022. (date of access 14.02.2023).

37. Zakharov V. N., Gvishiani A. D., Vaisberg L. A., et al. Big Data and sustainable functioning of geotechnical systems // Gornyi Zhurnal. 2021. Vol. 11. P. 45-52. DOI: (in Russian).

38. Zakharov V. N., Kaplunov D. R., Klebanov D. A., et al. Methodical approaches to standardization of data acquisition, storage and analysis in management of geotechnical systems // Gornyi Zhurnal. 2022. No. 12. P. 55-61. DOI: (in Russian).

39. Zhdaneev O. V., Oleneva O. N. Priority trends in the development of Russian software for the coal industry. Part 2 // Ugol’. 2021. Vol. 6, no. 07. P. 18-22. DOI: (in Russian).

40. Ministry of Energy of the Russian Federation. Report of the Ministry of Energy of the Russian Federation on the implementation of the Russian Coal Industry Development Program for the period up to 2035 in 2020: tech. rep. / Letter of the Ministry of Energy of the Russian Federation dated May 28, 2021 No. AYa-6203/22. 2021. (in Russian).

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