Mining Institute of Kola Science Center of RAS (Apatity, Russia):
Nikitin R. M., Senior Researcher, Candidate of Engineering Sciences, remnik@yandex.ru
Lukichev S. V., Director, Doctor of Engineering Sciences
Opalev A. S., Leading Researcher, Candidate of Engineering Sciences, Associate Professor
Biryukov V. V., Researcher, Candidate of Engineering Sciences, Associate Professor

In order to improve mineral separation efficiency, new adaptive process monitoring, predicting, and management systems are required. These may be developed through the creation of digital twins of respective processes, stages, and plants. Simulation models are a special type of mathematical models that reproduce the behavior of actual systems in time over a wide range of parameter values. The authors have developed a simulation model of a section segment in the processing of ferruginous quartzites and implemented it in the form of a computer application. The results of pilot tests conducted at section No. 9 of the crushing and processing plant of JSC «Olcon» were used as the initial data for its development. The objective was to predict distribution characteristics for the design size class (–0.071 mm) by process stages when producing magnetite concentrate. The paper presents the identified dependencies between process indicators of distributed mass flows under cyclic loads, the results of statistical processing of the sampling data, and their comparison with the simulation results. The example of modeling the classification and screening processes is used to demonstrate the feasibility of rapidly predicting process efficiency using the Hancock–Luiken criterion. It has been shown that the model may be paired with the enterprise monitoring system, the probability of deviation from the specified conditions may be identified for each section, step-by-step predictions of process indicators and decision-making recommendations may be issued, and direct equipment operation via the automated control system may be performed. It is assumed that the model will be complemented with functions to record distribution of the product mineral composition for each processing operation.

1. Tikhonov O. N. Theoretical foundations of separation processes of mineral beneficiation. Leningrad: LMI, 1978. 98 p.
2. Tikhonov O. N. Automation of production processes at processing plants. Moscow: Nedra, 1985. 272 p.
3. Shupov L. P. Modeling and computer calculation of beneficiation schemes. Moscow: Nedra, 1980. 288 p.
4. Leonov S. B., Petrov A.V. Simulation modeling of technological processes of mineral beneficiation. Irkutsk: IrSTU, 1996. 242 p.
6. Vaisberg L. A., Rubisov D. G. Vibrational screening of bulk materials. Process modeling and technological calculation of screens. St. Petersburg: «Mekhanobr-Tekhnika», 1994. 45 p.
7. Liu J., Wang F., Chen J., Xu L., Cao Q. Insights into the effect of magnetic interactions on the magnetization process of matrices in high gradient magnetic separation. Minerals Engineering. 2021. Vol. 174. DOI: 10.1016/j.mineng.2021.107269
8. Osipova N. V. Stabilization model of quality of iron ore concentrate in process of magnetic separation using optimizing control. Metallurg. 2018. No. 4. pp. 11–16.
9. Prosvirnin V. I., Masyutkin E. P., Masyutkin D. E. Refined mathematical model of coagulation of magnetic particles in curvilinear motion. Sovremennye Naukoyemkie Tekhnologii. 2017. No. 9. pp. 58–63.
10. Yamashita A. S., Thivierge A., Euzebio T. A. M. A review of modeling and control strategies for cone crushers in the mineral processing and quarrying industries. Minerals Engineering. 2021. Vol. 170. DOI: 10.1016/j.mineng.2021.107036
11. Mandakini Padhi, Narasimha Mangadoddy, Aubrey N. Mainza, Mohan Anand. Study on the particle interaction in a hydrocyclone classifier with multi-component feed blend at a high solids content. Powder Technology. 2021. Vol. 393. pp. 380–396.
12. Li Zh., Tong X., Zhou B., Wang X. Modeling and parameter optimization for the design of vibrating screens. Minerals Engineering. 2015. Vol. 83. pp. 149–155.
13. Markauskas D., Kruggel-Emden H. Coupled DEMSPH simulations of wet continuous screening. Advanced Powder Technology. 2019. Vol. 30, Iss. 12. pp. 2997–3009.
14. Shen G., Chen Zh., Wu X., Li Zh., Tong X. Stepwise shape optimization of the surface of a vibrating screen. Particuology. 2021. Vol. 58. pp. 26–34.
14. Nikitin R. M., Biryukov V. V., Kameneva Yu. S., Vishnyakova I. N. The use of a simulation model for reducing the size of mineral particles in the modeling of crushing and grinding processes. Obogashchenie Rud. 2020. No. 2. pp. 3–8. DOI: 10.17580/or.2020.02.01
15. Lukichev S., Nikitin R., Birukov V., Oleinik A. Simulation modeling concept of disintegration of minerals based on Gauss–Laplace and B (beta) distributions. Proc. of the 20^th International multidisciplinary scientific geoconference SGEM. 2020. Vol. 20, Iss. 1.1. pp. 847–854.
16. Lee D., Je J., Kim K., Kwon J., Cho H. Prediction of iron ore mineral liberation behavior using the Andrews–Mika diagram and beta distribution. Advanced Powder Technology. 2022. Vol. 33, Iss. 5. DOI: 10.1016/j.apt.2022.103558