Quantitative Assessment and Forecasting of Control Risks in the Ore-Stream Quality Management System
MukhtarkhanulySoltan A. Kobzhassarov B.T.
2025Science and Information Organization
International Journal of Advanced Computer Science and Applications
2025#16Issue 4921 - 930 pp.
The paper is aimed at organizational and technological optimization of the system of remote control of ore-stream quality according to technical and economic criteria. The ore-stream in the environment of digital transformation of the mining industry is seen as a system where one of the main functions of management is control. The key importance of the control function in ore-stream quality management becomes in ore quality assessment at the stage of ore material technological preparation, where the homogeneity of the ore massif in terms of the content of the useful component from heterogeneous deposits is formed. Such component in the paper is iron. System technological novelty, which is presented in the paper, consists in realization of constant remote control of ore material quality in the form of monitoring. Remote control is technically realized using unmanned vehicles with subsequent digital processing of information by on-board microprocessor technology and special mathematical and software. The iron content of the ore is estimated from the vertical vector of the magnetic field of the ore material. The implementation of such a concept envisaged the solution of the following tasks: development of a structural and functional model of ore-stream quality control; development of mathematical support for the digital system of data processing of ore material magnetic field measurement data, optimization of metrological indicators of the measuring complex of the control system. It is proposed to use control risks as criteria for quantitative assessment of the functional quality of the ore-stream quality management system. The empirical function of the relationship between the cost of magneto metric remote control of iron content and probable control risks is found. A 3D model of the dependence of the cost of magnetometric control of iron content as a function of accuracy and the value of standards of iron content in ore was built.
control , model , Ore-stream , probability , risks , system , technology , unmanned vehicles
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School of Digital Technologies and Artificial Intelligence, EKTU named after D. Serikbayev, Ust-Kamenogorsk, Kazakhstan
School of Digital Technologies and Artificial Intelligence
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