Data analysis as a basis for improving the efficiency of mining equipment in open pit operations

DOI: https://doi.org/10.30686/1609-9192-2023-1-52-56
Читать на русскоя языкеM.V. Rylnikova, D.A. Klebanov, E.A. Knyazkin
Institute of Comprehensive Exploitation of Mineral Resources of Russian Academy of Sciences, Moscow, Russian Federation
Russian Mining Industry №1 / 2023 р. 52-56

Abstract: The paper analyzes data from an automatic dispatching system to assess the utilization efficiency of the mining transport equipment. Ranking of excavator operators in terms of the dump truck loading quality in both mining and overburden operations is made, which demonstrates the degree of personnel's personal professional skills impact on the process of rock mass transportation. As the result of the performed investigation, it was found that when assessing the impact of personnel on performance indicators of mining and transportation equipment in isolation from the overall technological process, errors can be made in interpretation of the company's performance results. Principles to organize automated systems within the mining operation are proposed, which include the end-to-end integration of automated systems using a unified communication standard.

Keywords: rock mass transportation, big data, automated systems, complex mine transport system, system integration

Acknowledgments: The research was supported by the Russian Science Foundation Grant No.22-17-00142, https://rscf.ru/project/22-17-00142/

For citation: Rylnikova M.V., Klebanov D.A., Knyazkin E.A. Data analysis as a basis for improving the efficiency of mining equipment in open pit operations. Russian Mining Industry. 2023;(1):52–56. https://doi.org/10.30686/1609-9192-2023-1-52-56

Article info

Received: 14.12.2022

Revised: 19.01.2023

Accepted: 20.01.2023

Information about the authors

Marina V. Rylnikova – Dr. Sci. (Eng.), Professor, Deputy Head of the Department of Subsoil Development Design Theory, Institute of Comprehensive Exploitation of Mineral Resources of Russian Academy of Sciences, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Dmitry A. Klebanov – Cand. Sci. (Eng.), Head of Laboratory of Intelligent Systems and Digital Technologies, Institute of Comprehensive Exploitation of Mineral Resources of Russian Academy of Sciences, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Egor A. Knyazkin – Cand. Sci. (Eng.), Research Associate of Laboratory of Intelligent Systems and Digital Technologies, Institute of Comprehensive Exploitation of Mineral Resources of Russian Academy of Sciences, Moscow, Russian Federation

References

1. Shibanov D.A., Ivanova P.V., Ivanov S.L. Tariffing of the influencing factors on the work of the modern mine excavators at actual cost of rock mass. Mining Informational and Analytical Bulletin. 2015;(S1-2):24–33. (In Russ.)

2. Zykov P.A., Zvarych E.B., Karasev A.N. Maximizing of open-pit mining efficiency. Bulletin of the Kuzbass State Technical University. 2020;(3):70–79. https://doi.org/10.26730/1999-4125-2020-3-70-79 (In Russ.)

3. Menegaki M., Michalakopoulos T., Roumpos C. Exploring the effect of physical, human and technical factors on bucket wheel excavators’ efficiency: a fuzzy cognitive map approach. International Journal of Mining and Mineral Engineering. 2019;10(2–4):189–204. https://doi.org/10.1504/ijmme.2019.104447

4. Litvin O., Litvin Ya. Evaluation of Effect of the Excavator Cycle Duration on its Productivity. E3S Web of Conferences. 2020;174:01010. https://doi.org/10.1051/e3sconf/202017401010

5. Temkin I., Klebanov D., Deryabin S., Konov I. Predictive Analytics in Mining. Dispatch System Is the Core Element of Creating Intelligent Digital Mine. Communications in Computer and Information Science. 2020;1201:365–374.