Autonomous drilling and blasting operations in open-pit mining: automation of the process cycle, drilling accuracy and management of blast fragmentation of rocks
Ilya V. Samarin
National University of Oil and Gas “Gubkin University”, Moscow, Russian Federation
Mining Industry Journal (Gornaya Promyshlennost) №5/ 2026 p. 127-134
Summary: Drilling and blasting is a basic stage of open-pit mining that governs the particle-size distribution in the muck pile and, consequently, the costs of excavation, haulage and processing. Blasting accounts for 20–35% of the mining cost and up to 90% of the rock breaking by volume. Manual operations cause drilling inaccuracy, excessive consumption of explosives, an increased oversize yield, higher seismicity and risks to personnel. The paper systematizes directions of drilling and blasting robotization across the following five process stages: drilling, pattern and charge design, charging, initiation and fragmentation diagnostics. It also introduces a unified five-level automation-maturity scale, i.e. manual → mechanized → automated → robotic → autonomous operations. An integral robotization efficiency index is proposed, with process weights normalized by their contribution to the effects. Fragmentation forecast is made using the Kuznetsov–Rammler model and the Swebrec function. The median fragment size shifts from 420 to 350 mm and the oversize yield drops from 7.8 to 2.9% for a model block (250 mm hole diameter). Industry effects of automation are generalized including a 50–75% reduction in the hole deviation, a 40–65% drop in oversize, a 5–12% decrease in the specific explosive consumption, a 10–20% gain in the drilling productivity and a 15–30% reduction in seismicity. In the typical and target scenarios the integral index equals 56% and 88%. Implementation barriers and a roadmap for drilling and blasting robotization within the process-control system and the digital twin of the pit are outlined.
Keywords: drilling and blasting, open-pit mining, robotization, autonomous drill rig, drilling accuracy, particle size distribution, Kuznetsov–Rammler model, Swebrec function, electronic initiation, specific explosive consumption, oversize yield, digital twin of open-pit mine
For citation: Samarin Ilya V. Autonomous drilling and blasting operations in open-pit mining: automation of the process cycle, drilling accuracy and management of blast fragmentation of rocks. Mining Industry Journal (Gornaya Promyshlennost). 2026;(5):127–134. https://doi.org/10.30686/1609-9192-2026-5-127-134
Article info
Received: 12.06.2026
Revised: 22.07.2026
Accepted: 27.07.2026
Authors info
Samarin Ilya V. – Dr. Sci. (Eng.), Associate Professor, Head of the Department of Automation of Technological Processes, National University of Oil and Gas “Gubkin University”, Moscow, Russian Federation; https://orcid.org/0000-0003-2430-5311; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
References
1. Afanasev P.I. Methodological framework for rock blasting in open pit mining. Mining Informational and Analytical Bulletin . 2025;(12):28–41. (In Russ.) Available at: https://giab-online.ru/files/Data/2025/12/12_2025_28-41.pdf (accessed: 22.03.2026).
2. Vokhmin S.A., Kurchin G.S., Shevnina E.V., Kirsanov A.K., Kostylev S.S. Granulometric composition predicting models after explosion in open-pit mining. Izvestiya Vysshikh Uchebnykh Zavedeniy. Gornyy Zhurnal. 2020;(1):14–24. (In Russ.) https://doi.org/10.21440/0536-1028-2020-1-14-24
3. Marinin M.A., Rakhmanov R.A., Alenichev I.A., Afanasyev P.I., Sushkova V.I. Effect of grain size distribution of blasted rock on WK-35 shovel performance. Mining Informational and Analytical Bulletin. 2023;(6):111–125. (In Russ.) https://doi.org/10.25018/0236_1493_2023_6_0_111
4. Marinin M.A., Marinina O.A., Rakhmanov R.A. Methodological approach to assessing influence of blasted rock fragmentation on mining costs. Gornyi Zhurnal. 2023;(9):28–34. (In Russ.) https://doi.org/10.17580/gzh.2023.09.04
5. Shigin A.O., Gilyov A.V., Shigina A.A. Automation of rotary blasthole drilling in open pit mines. Gornyi Zhurnal . 2017;(2):82–86. https://doi.org/10.17580/gzh.2017.02.16
6. Nikitenko M.S., Khudonogov D.Y., Kizilov S.A. Alternative frameworks for equipment positioning in mining operations. Journal of Mining Institute . 2025;275:167–178. Available at: https://pmi.spmi.ru/pmi/article/view/16718 (accessed: 22.03.2026).
7. Cheshchin D.O., Plokhikh V.V. Automation in the mining industry and impact machine for a robotic complex. Problems of Subsoil Use . 2022;(1):46–54. (In Russ.) https://doi.org/10.25635/2313-1586.2022.01.046
8. Коваленко В.С., Зырянов И.В. Автоматизация и роботизация горного производства – современный этап перехода к высокопроизводительному и безопасному ведению открытых горных работ. Горная промышленность. 2025;(5):124–
9. Marinin M.A. Drill&blast design for preset grain-size composition of broken rocks in open pit mineral mining. Gornyi Zhurnal. 2025;(3):79–86. (In Russ.) https://doi.org/10.17580/gzh.2025.03.11
10. Sakhapova T.S., Protsenko K.Yu., Tikhonova E.A., Ipatova M.A. Overview of foreign manufacturers of mixing and charging Russian Mining Industry . 2022;(3):79–83. (In Russ.) https://doi.org/10.30686/1609-9192-2022-3-79-83
11. Zhulikov V.V., Knyazev K.A., Nazarov S.S. Justification of blasting efficiency using electronic systems in comparison with non-electric primers. Russian Mining Industry. 2022;(5):64–68. (In Russ.) https://doi.org/10.30686/1609-9192-2022-5-64-68
12. Sher E.N. Modeling rock fracture in closely spaced perimeter blasting. Journal of Mining Science. 2023;59(5):763–769. https://doi.org/10.1134/S1062739123050083
13. Dremin A.V., Sitdikova S.V., Velikanov V.S., Stozhkov D.S., Grishin I.A. Real-time analysis of particle size distribution of rocks using a domestic software and hardware complex. Russian Mining Industry. 2025;(3):118–123. (In Russ.) https://doi.org/10.30686/1609-9192-2025-3-118-123
14. Velikanov V.S., Dremin A.V., Chernukhin S.A., Lomovtseva N.V. Neural network technologies in mining data on particle size distribution of muck pile rocks. Russian Mining Industry. 2024;(4):90–94. (In Russ.) https://doi.org/10.30686/1609-9192-2024-4-90-94
15. Marinin M.A., Afanasyev P.I., Sushkova V.I., Ustimenko K.D., Akhmetov A.R. The experience of using the Kuz-Ram model in describing of grain size distribution of blasted rock mass. Mining Informational and Analytical Bulletin . 2023;(9-1):96–109. (In Russ.) https://doi.org/10.25018/0236_1493_2023_91_0_96
16. Rakishev B.R., Orynbay A.A., Auezova A.M., Kuttybaev A.E. Grain size composition of broken rocks under different conditions of blasting. Mining Informational and Analytical Bulletin. 2019;(8):83–94. (In Russ.) https://doi.org/10.25018/0236-1493-2019-08-0-83-94
17. Ouchterlony F. The Swebrec© function: linking fragmentation by blasting and crushing. Mining Technology: Transactions 2005;114(1):29–44. https://doi.org/10.1179/037178405X44539
18. Saadoun A., Fredj M., Boukarm R., Hadji R. Fragmentation analysis using digital image processing and empirical model (KuzRam): a comparative study. Journal of Mining Institute. 2022;257:822–832. https://doi.org/10.31897/PMI.2022.84
19. Gavrilkovich E.G., Onika S.G., Gets A.K., Zhukov S.A. Fragment size distribution and its probability distribution in blasted rock mass in a natural stone quarry. Gornyi Zhurnal . (In Russ.) 2022;(4):52–56. https://doi.org/10.17580/gzh.2022.04.08
20. Klebanov A.F., Eremkin I.V., Gabusu P.A. Digital twins of control processes for highly automated mining transport complexes. Russian Mining Industry . 2025;(4):61–70. (In Russ.) https://doi.org/10.30686/1609-9192-2025-4-61-70
21. Zhdaneev O.V., Vlasova I.M. Digital transformation of the coal industry. Ugol’. 2023;(1):62–69. (In Russ.) https://doi.org/10.18796/0041-5790-2023-1-62-69



