Methodical support for corporate operational planning of an excavator-truck-conveyor complex based on simulation modeling

In the article the methodical support for corporate operational planning of the excavator-truck-conveyor complex using simulation modeling methods is represented. The main difficulty with traditional planning methods lies in the need to align mining-geometric and mining-geological parameters with the production capacity of the mining and transport equipment used, as well as the lack of sufficient optimization efficiency when these parameters change. Assessing the potential of the mining and transport system should be carried out using methods that allow for an objective and accurate consideration of the impact of such factors. The proposed approach to planning the operation of the mining and transport system is implemented within technologically stable periods using simulation modeling methods. This contributes to increased planning reliability and the achievement of maximum economic efficiency in the open pit's geotechnical system. Simulation modeling of complex mining and transport systems ensures a detailed and consistent accounting of all operations within the modeled process. The status of each system element is recorded step by step, and their operation and downtime are monitored. In addition, data characterizing the functioning of the system as a whole is collected. This approach allows for the identification of the qualitative and quantitative impact of individual elements on the final results of the system's operation and the evaluation of the effectiveness of the chosen option for organizing the interaction of mining and transport equipment from a technological perspective. The system will enable efficient planning of mining and transport operations in real-time, with full capacity utilization, taking into account a large number of interrelated factors that significantly impact the operation of open pit mining and transport systems, and will also ensure prompt evaluation of the effectiveness of the resulting planning options.

Keywords: geotechnology, surface mining, simulation modeling, optimization, corporate planning, excavator-truck-conveyor, methodical support, efficiency, mining and transport complex.
For citation:

Boyandinova A. A., Adilkhanova Zh. A., Tkachenko O. N. Methodical support for corporate operational planning of an excavator-truck-conveyor complex based on simulation modeling. MIAB. Mining Inf. Anal. Bull. 2025;(12-2):71-83. [In Russ]. DOI: 10.25018/0236_1493_2025_122_0_71.

Acknowledgements:
Issue number: 12-2
Year: 2025
Page number: 71-83
ISBN: 0236-1493
UDK: 622.012:658.5:622.68
DOI: 10.25018/0236_1493_2025_122_0_71
Article receipt date: 20.10.2025
Date of review receipt: 10.11.2025
Date of the editorial board′s decision on the article′s publishing: 17.11.2025
About authors:

A.A. Boyandinova1, Dr. Sci. (Eng.), Associate Professor,  Scientific Secretary, e-mail: A.Boyandinova@mail.ru, ORCID ID: 0009-0001-5197-4599,
Zh.A. Adilkhanova1, Cand. Sci. (Eng.), Head of Laboratory, e-mail: Zhanna_mark10@mail.ru, ORCID ID: 0000-0002-2637-4006,
O.N. Tkachenko1, Cand. Sci. (Eng.), Junior Researcher, e-mail: oksananecolaevna@gmail.com, ORCID ID: 0000-0003-1372-7113,
1 Institute of Mining named after D.A. Kunayev, Branch of the «NC CPMS RK» RSE of the Ministry of Industry and Construction of the Republic of Kazakhstan, 050046, Almaty, Kazakhstan.

 

For contacts:

Zh.A. Adilkhanova, e-mail: Zhanna_mark10@mail.ru.

Bibliography:

1. Boyandinova A., Adilkhanova Z. Methodological provisions for the evaluation of economic efficiency for calendar planning of technological processes taking into account flexible rationing. 19th International Multidisciplinary Scientific GeoConference SGEM 2019. 2019, vol. 19, pp. 415—422. DOI: 10.5593/sgem2019/1.3/S03.053.

2. Tomašková M., Sinay J. The use of screw conveyors in practical applications. Applied Mechanics and Materials. 2014, vol. 683, pp. 225—231.

3. Parreiras T. M., Rocha A. V., Justino J. C. G., de Cardoso Filho B. J. True unit power factor active front end for high capacity belt conveyor systems. IEEE Transactions on Industry Applications. 2016, vol. 52, no. 3. DOI: 10.1109/TIA.2016.2533499.

4. Gavrishev S. E., Burmistrov K. V., Tomilina N. G. Increasing the work scope of conveyor transport at mining companies. Procedia Engineering. 2016, vol. 150, pp. 1317—1321. DOI: 10.1016/j.proeng.2016.07.306.

5. Glebov A. V. Methodological principles of equipment selection for cyclical-andcontinuous technology mechanization. MIAB. Mining Inf. Anal. Bull. 2021, no. 5-2, pp. 296—308. [In Russ]. DOI: 10.25018/0236_1493_2021_52_0_296.

6. Lucio J. C., Senra C. T., Souza A. Paving the future — A case study replacing truck-and-shovels by shovel-and-conveyor continuous mining at Carajas open pit mines. Iron Ore 2009 Conference. Perth, WA, 2009, pp. 269—276.

7. Rocha A. V., de Paula H., dos Santos M. E., de Cardoso Filho B. J. Increasing long belt-conveyors availability by using fault-resilient medium voltage AC drives. Part II. Reliability and maintenance assessment. 2012 IEEE Industry Applications Society Annual Meeting. 2012, pp. 1—8. DOI: 10.1109/IAS.2012.6374079.

8. Vera-Burau A., Alvárez-Ramírez D., Sanmiquel-Pera L., Bascompta M. A Comparison of the fuel consumption and truck models in different production scenarios. Applied Sciences. 2023, vol. 13, no. 9, article 5769. DOI: 10.3390/app13095769.

9. Li Z. A methodology for the optimum control of shovel and truck operations in open-pit mining. Mining Science and Technology. 1990, vol. 10, no. 3, pp. 337—340. DOI: 10.1016/0167-9031(90)90543-2 

10. Adams K. K., Bansah K. J. Review of operational delays in shovel — Truck system of surface mining operations. 4th UMaT Biennial International Mining and Mineral Conference. 2016, pp. 60—65.

11. Nieto A., Medina J. F. Development of a socio-economic strategic risk index as an aid for the feasibility assessment of mining projects and operations. Journal of the Southern African Institute of Mining and Metallurgy. 2020, vol. 120, no. 7, pp. 433—450. DOI: 10.17159/2411-9717/711/2020.

12. Mariz J. L. V., Peroni R., de Abreu Silva R. M., Badiozamani M. M., Askari-Nasab H. A multi-objective constraint programming approach to address clustering problems in mine planning. Engineering Computations. 2024, vol. 41, no. 3, pp. 2682—2706. DOI: 10.1108/EC-01-2024-0046.

13. Sobczyk E. J., Galica D., Kopacz M., Sobczyk W. Selecting the optimal exploitation option using a digital deposit model and the AHP. Resources Policy. 2022, vol. 78, article 102952.

14. Aquino E. D. R., Girao Sotomayor J. M., Navarro-Torres V. F. Qualification of geotechnical parameters with 3D geotechnical modelling to improve mine planning reliability. Mining Technology Transactions of the Institutions of Mining and Metallurgy. 2024, vol. 133, no. 1, pp. 74—85.

15. Tyurin A., Kuvataev I. Improving the efficiency of a mining enterprise by coordinating production processes. E3S Web of Conference. 2020, vol. 174, article 01059. DOI: 10.1051/e3sconf/202017401059.

16. Zyryanov I. V., Kornyakov M. V., Nepomnyashchikh K. A., Trufanov A. I., Khramovskikh V. A., Shevchenko A. N. Network platform for automating the prediction of failures of quarry dump trucks. Russian Mining Industry Journal. 2024, no. 3, pp. 56—63. [In Russ]. DOI: 10.30686/1609-9192-2024-3-56-63.

17. Zakharov V. N., Kubrin S. S. Digital transformation and intellectualization of mining systems. MIAB. Mining Inf. Anal. Bull. 2022, no. 5-2, pp. 31—47. [In Russ]. DOI: 10.25018/0236_1493_2022_52_0_31.

18. Adilkhanova Zh., Boyandinova A. Concept of management system of technological processes at open pits. Proceedings of the 18th International Multidisciplinary Scientific GeoConference SGEM 2018. Albena, Bulgaria, 2018, pp. 191—196. DOI: 10.5593/sgem2018/1.3/S03.025.

19. Boyandinova A. A., Adilkhanova Z. A. An information support for management system of technological processes at open pits. Proceedings of the 20th International Multidisciplinary Scientific GeoConference SGEM 2020. 2020, pp. 441—448. DOI: 10.5593/sgem2020/2.1/s08.057

20. Čech J., Sofranko M. Economic projection and evaluation of mining venture. E+M Ekonomie a Management. 2018, vol. 21, no. 2, pp. 38—52.

21. Topal E., Ramazan S. Mining truck scheduling with stochastic maintenance cost. Journal of Coal Science and Engineering (China). 2012, vol. 18, no. 3. DOI: 10.1007/s12404-012-0316-4.

22. Zhuravlev A. G. The issues of optimization parameters of quarry transport systems. MIAB. Mining Inf. Anal. Bull. 2020, no. 3-1, pp. 583—601. [In Russ]. DOI: 10.25018/0236-1493-2020-31-0-583-601. 

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