Planning performance of stoping operations with regard to their complexity: A case-study of Oktyabrsky Mine, Buribaevsky GOK

The article displays an approach to planning output capacity of stopes in underground mines. The approach is based on the studies into complexity of stoping operations in mines of Buribaevsky GOK. The author used a relative duration of auxiliary operations as a stoping complexity indicator, which allowed distinguishing between 3 categories of complexity of stopes in Oktyabrsky Mine. The relative duration of auxiliary operations is calculated as a ratio of the total auxiliary time to the total principal time. The comparison of the stop-watch reading data on stoping operations at the mean-shift output capacity revealed the dependence of the actual work performance in stopes on the relative duration of auxiliary operations. The process variables that govern the values of the relative duration of auxiliary operations are found. The analysis of the process variables which condition increased complexity reveals the factors that greatly reduce attainability of the required output capacity per each category of complexity of stopes. The casestudy of Oktyabrsky Mine illustrates probability of achievement of the planned output per shift per complexity categories of stopes. The recommendations are given to increase probability of achieving the required output capacity in stopes with regard to their complexity categories.

Ablaev R. B. Planning performance of stoping operations with regard to their complexity: A case-study of Oktyabrsky Mine, Buribaevsky GOK. MIAB. Mining Inf. Anal. Bull. 2025;(1-1):234-243. [In Russ]. DOI: 10.25018/0236_1493_2025_11_0_234.

R.B. Ablaev, General Director, JSC «Buribaevsky MPP», Buribay, Russia, e-mail: ok@bgok.ru.

1. Azev V. A. Methodology of comprehensive planning for the development of a coal mining enterprise. MIAB. Mining Inf. Anal. Bull. 2018, no. S40, 50 p. [In Russ].

2. Galkin V. A., Makarov A. M., Zakharov S. I., Poleshchuk M. N. Methodology for calculating the reserve of working time for personnel of a coal mining enterprise for its development. News of the Ural State Mining University. 2019, no. 2, pp. 134—145. [In Russ].

3. Dolzhenko R. A., Malyshev D. S. Digitalization of approaches to labor regulation at industrial enterprises. Herald of Omsk university. Series «Economics». 2021, vol. 19, no. 4, pp. 54—66. [In Russ].

4. Khazhiev V. A. Assessing the impact of factors on the efficiency of using shovel shovels in coal mines. Mining Equipment and Electromechanics. 2009, no. 6, pp. 21—26. [In Russ].

5. Kukarenko A. I. Lomovtsev V. V., Dyakonov A. V., Shestakov I. G., et al. The role of production organization during technical re-equipment. Ugol'. 2011, no. 6, pp. 70—72. [In Russ].

6. Kilin A. B., Azev V. A., Kuznetsov A. N., Senatorov D. S., et al. On the system of continuous improvements in production processes at SUEK-Khakassia LLC. MIAB. Mining Inf. Anal. Bull. 2016, no. S29, 12 p. [In Russ].

7. Greberg J., Salama A. Analysis of the current challenges for deep underground mines: Labour productivity improvement. Tanzania Journal of Engineering and Technology. 2020, vol. 39, no. 1, pp. 32—46.

8. Jeuken R., Forbes M. A. The value of drilling — A chance-constrained optimization approach. Mining Metallurgy & Exploration. 2024, vol. 41. DOI: 10.1007/s42461-024-01061-8. available at: https://link.springer.com/article/10.1007/s42 461-024-01061-8 (accessed 05.09.2024).

9. Dobrovolsky A. I., Feofanov G. L., Lisovsky V. V., Zolotarev N. P. Possibilities of improving the efficiency and safety of production at Urgalugol OJSC. Ugol'. 2011, no. 7, pp. 49—52. [In Russ].

10. Otto T. J., Lindeque G. C. Improving productivity at an open-pit mine through enhanced shortterm mine planning. Journal of the Southern African Institute of Mining and Metallurgy. 2021, vol. 121, no. 11, pp. 1—10.

11. Dobrovolsky A. I., Feofanov G. L., Zhukov A. L. Technological solutions for the preparation of the cleaning front at the Urgalskoye deposit. Vestnik of Nosov Magnitogorsk State Technical University. 2011, no. 3, pp. 46—48. [In Russ].

12. Feofanov G. L. Features of the preparation of the cleaning front in complex hydrogeological conditions. Ugol'. 2010, no. 12, pp. 24—27. [In Russ].

13. Azev V. A., Gartman A. A., Konakova O. V. Project approach to improving production activities and personnel development of enterprises of SUEK-Khakassia LLC. Ugol'. 2021, no. 12 (1149), pp. 21—27. [In Russ]. DOI: 10.18796/0041-5790-2021-12-21-27.

14. Galkin V. A., Makarov A. M., Kravchuk I. L., Sokolovsky A. V. Relationships and interaction at a mining enterprise. Ugol'. 2024, no. 6, pp. 23—27. [In Russ]. DOI: 10.18796/0041-5790-2024-6-23-27.

15. Shapovalenko G. N. An approach to increasing the efficiency of control of production processes in a coal mine. MIAB. Mining Inf. Anal. Bull. 2011, no. 6, pp. 390—396. [In Russ].

16. Emdini S., Crowe K. A network flow model for operational planning in an underground gold mine. Mining. 2022, vol. 2, no. 4, pp. 712—724. DOI: 10.3390/mining2040039.

17. Wang H., Zhang X., Yuan H., Zhou M., Wu Z. A lean scheduling framework for underground mines based on short interval control. Sustainability. 2023, vol. 15, no. 12, article 9195. DOI: 10.3390/ su15129195.

18. Amoako R., Chowdu A., Brickey A. J. A deviation-minimization approach to short-term underground mine schedule optimization. Mining Metallurgy & Exploration. 2023, vol. 40, pp. 1749—1765. DOI: 10.1007/s42461-023-00802-5. available at: https://link.springer.com/article/10.1007/s42461023-00802-V. 40.

19. Dovzhenok A. S., Alekseenko V. B., Khazhiev V. A., Baikin V. S. Methodological tools for the formation and implementation of monitoring of the organization of the operation process of mining and transport equipment at a coal mining enterprise. Izvestia of the Samara Scientific Center of the Russian Academy of Sciences. 2020, vol. 22, no. 4 (96), pp. 48—56. [In Russ]. DOI: 10.37313/1990-5378-2020-22-4-48-56.

20. Aalian Y., Gamache M., Pesant G. Short-term underground mine planning with uncertain activity durations using constraint programming. Journal of Scheduling. 2024, vol. 27, no. 5, pp. 423—439. DOI: 10.1007/s10951-024-00808-x.