Regarding the particle-size composition of blasted rocks
A.V. Dremin1, V.S. Velikanov1,2
1 DAVTECH LLC, Ekaterinburg, Russian Federation
2 Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation
Russian Mining Industry №4 / 2023 р. 73-78
Abstract: Decreasing ore grades combined with increasing pit depths call for the development of solutions to ensure efficient interaction within the mine-to-mill concept, which should be adapted to each specific mining operation and will optimize the production costs. The aim of the study was to develop a methodological approach to assess the particle size distribution of material within the mine-to-mill process. The study applied a comprehensive approach, which includes scientific analysis and generalization of previously published research results. From the methodological point of view, the study was based on the system analysis methods, as well as on the use of information technologies. A conclusion is made that a mathematical apparatus needs to be created and implemented, which would allow formalizing the nature of statistical data on the particle size distribution. The solution of this problem is extremely important to obtain a time series describing the dynamics of the process over time, since most of the data have a different format of representation. The authors believe that a promising approach is to use predictive analytics, i.e. a tool for analyzing statistically significant and objective data, which helps to make accurate forecasts for decisionmaking.
Keywords: useful mineral, particle size distribution, open pit mining
For citation: Dremin A.V., Velikanov V.S. Regarding the particle-size composition of blasted rocks. Russian Mining Industry. 2023;(4):73–78. https://doi.org/10.30686/1609-9192-2023-4-73-78
Article info
Received: 03.07.2023
Revised: 24.07.2023
Accepted: 24.07.2023
Information about the authors
Aleksandr V. Dremin – Director General, DAVTECH LLC, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Vladimir S. Velikanov – Dr. Sci. (Eng.), Academic Adviser, DAVTECH LLC, Professor, Department of Hoisting and Hauling Machines and Robots, Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation, Professor, Department of Automatics and Computer Technologies, Ural State Mining University, Ekaterinburg, Russian Federation; ORCID https://orcid.org/0000-0001-5581-2733; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
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