Methodology of planning excavator operations in open pit mines based on computer modeling
V.D. Kantemirov, A.M. Yakovlev, R.S. Titov , A.V. Timokhin
Institute of Mining of Ural branch of the Russian Academy of Sciences, Ekaterinburg, Russian Federation
Russian Mining Industry №6 / 2023 р. 75-80
Abstract:
Introduction. In-pit excavators, which provide removal and loading of muck piles, are one of the main process links in the system of complex mechanization of open-pit mines. The level of mining operation intensity is determined by the arrangement of excavators in the open pit. Research objective. The research aims to develop a method of automated positioning of excavators at the production benches of the open pit mine. Methodology. Arrangement of in-pit excavators excavators at the production benches of the open pit mine is based on calculations, computer modeling and ia made with account of technical and operational parameters of the excavators, as well as estimation of the active front of mining operations. The main stage of solving the formulated problem is the construction of block models of the ore body, modeling of mining operations, and building a model of the open pit mine by the stages of the deposit development. Based on the results of block modeling, the optimal length of the excavator block at the production bench for the selected model of the face excavator is determined.
Results. The article proposes a methodology for planning excavator operations in the open pit mine and positioning of the face excavators based on computer modeling of the mining operations progress with due account of the volume of rock mass handling on the open pit bench, the length of the active front, the mineral grade, the given rate of development, the accepted models of excavators and other attributive computer data. Based on the block model, the excavators are positioned on the production benches of the open pit mine. The proposed approach allows a prompt consideration of many options to arrange face excavators in the open pit ore mine in a semi-automatic mode and select the best option to increase the mining efficiency.
Conclusions. The proposed methodology allows to promptly solve in a semi-automatic mode the issues of opening the lower levels of deep pits, to consider many options for placing face excavators in the ore pit and choose the best option, contributes to minimizing the operational risks in the development of complex-structured deposits and complex extraction of raw materials.
Keywords: positioning of open pit excavators, block modeling, length of the mining front, production levels of the open pit mine
For citation: Kantemirov V.D., Yakovlev A.M., Titov R.S., Timokhin A.V. Methodology of planning excavator operations in open pit mines based on computer modeling. Russian Mining Industry. 2023;(6):75–80. (In Russ.) https://doi.org/10.30686/1609-9192-2023-6-75-80
Article info
Received: 29.09.2023
Revised: 24.10.2023
Accepted: 31.10.2023
Information about the authors
Valery D. Kantemirov – Cand. Sci. (Eng.), Quality Management Sector Chief, Institute of Mining of Ural branch of the Russian Academy of Sciences, Ekaterinburg, Russian Federation; https://orcid.org/0000-0001-6486-2740; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Andrei M. Yakovlev – Cand. Sci. (Eng.), Senior Researcher, Quality Management Sector, Institute of Mining of Ural branch of the Russian Academy of Sciences, Ekaterinburg, Russian Federation; https://orcid.org/0000-0001-8285-6387; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Roman S. Titov – Senior Researcher, Quality Management Sector, Institute of Mining of Ural branch of the Russian Academy of Sciences, Ekaterinburg, Russian Federation; https://orcid.org/0000-0002-3569-2743; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Alexander V. Timokhin – Research Associate, Mineral Raw Material Quality Management Sector, Institute of Mining of Ural branch of the Russian Academy of Sciences, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
References
1. Kantemirov V.D. Technological features of development of new raw-material bases. Mining Informational and Analytical Bulletin. 2014;(6):369–373. (In Russ.) Available at: https://www.giab-online.ru/files/Data/2014/06/369-373_Kantemirov.pdf
2. Nelis G., Morales N. A mathematical model for the scheduling and definition of mining cuts in short-term mine planning Optimization and Engineering. 2022;23(1):233–257. https://doi.org/10.1007/s11081-020-09580-1
3. Blom M., Pearce A.R., Stuckey P.J. Short-term planning for open pit mines: A review. International Journal of Mining, Reclamation and Environment. 2019;33(5):318–339. https://doi.org/10.1080/17480930.2018.1448248
4. Mousavi A., Kozan E., S.Q. Liu Open-pit block sequencing optimization: A mathematical model and solution technique. Engineering Optimization. 2016;48(11):1932–1950. https://doi.org/10.1080/0305215X.2016.1142080
5. Kozan E., Liu S.Q. A new open-pit multi-stage mine production timetabling model for drilling, blasting and excavating operations. Mining Technology. 2016;125(1):47–53. https://doi.org/10.1179/1743286315Y.0000000031
6. Askari -Nasab H., Awuah-Offei K., Eivazy H. Large-scale open pit production scheduling using Mixed Integer Linear Programming. International Journal of Mining and Mineral Engineering. 2010;2(3):185–214. https://doi.org/10.1504/IJMME.2010.037624
7. Kantemirov V.D., Titov R.S., Iakovlev A.M. The analysis of mining equipment performances in the leading iron-ore open pits of Russia. Izvestiya Vysshikh Uchebnykh Zavedenii. Gornyi Zhurnal. 2019;(2):40–50. (In Russ.) https://doi.org/10.21440/0536-1028-2019-2-40-50
8. Kantemirov V.D. Comparative assessment of productivity and quantity of process equipment in large open pit mines. In: Scientific and technical support of mining production. Proceedings of the D.A. Kunaev Mining Institute. Almaty: Institute of Mining named after D.A. Kunaeva; 2009. Vol. 78, pp. 187–193. (In Russ.)
9. Shcheglov V.I. Geostatistical methods of analysis and assessment of deposits. Novocherkassk: Platov South-Russian State Polytechnic University; 2012. 167 p. (In Russ.) Available at: https://www.geokniga.org/books/10480
10. Demyanov V.V., Savelieva E.A., Arutyunyana R.V. Geostatistics: Theory and Practice. Moscow: Nauka; 2010. 327 p. (In Russ.) Available at: http://ibrae.ac.ru/docs/109/geostatistikai_sq_cover.pdf
11. Polovko A.M., Butusov P.N. Interpolation. Methods and computer technologies of their implementation. St. Petersburg: BKhV-Peterburg; 2004. 320 p. (In Russ.) Available at: http://physics.gov.az/book_I/interpolyatsiya_metody.pdf
12. Nagovitsyn O.V., Lukichev S.V. Mining and geological information systems, areas of application and features of building. Mining Informational and Analytical Bulletin. 2016;(7):71–83. (In Russ.) Available at: https://giab-online.ru/files/Data/2016/7/71_83_7_2016.pdf
13. Rakishev B.R. Technological complexes of surface mining operations. Almaty; 2015. 313 p. (In Russ.)
14. Gavrishev S.E., Burmistrov K.V., Kolonyuk A.A. Intensity of work zone formation in deep pit mines. Magnitogorsk: Nosov Magnitogorsk State Technical University; 2013. 187 p. (In Russ.) Available at: https://www.elibrary.ru/rqjtcv
15. Trubetskoy K.N., Krasnyansky G.L., Khronin V.V., Kovalenko V.S. Designing of surface mines. 3th ed. Moscow: Vysshaya shkola; 2009. 694 p. (In Russ.) Available at: https://www.geokniga.org/bookfiles/geokniga-proektirovanie-karerov.pdf
