Authors: F.N. Abu-Abed, L.G. Naumova

Title of the article: IT-technologies in technological process automation in mining

Year: 2019, Issue: 3, Pages: 21-35

Branch of knowledge: 25.00.22 Geotechnology (underground, open and construction)

Index UDK: 622.248.5:004.896

DOI: 10.26730/2618-7434-2019-3-21-35

Abstract: Automation of technological processes in industry and in production is becoming more and more actualized with an increasing risk of failure of industrial equipment as a result of resource exhaustion or wear. The issues of developing automated technical and diagnostic systems based on artificial neural networks contribute in real time, regardless of the equipment operation strategy, to monitor and manage stocks and accessories, as well as optimize the placement of components in replenishment sources for spare parts; the results of the work of the developed neural network classifier of drilling anomalies underlie the minimization of the objective function of the waiting time for the start of repair in case of failures or breakdowns arising in the process of industrial drilling of mining deposits. Ensuring the planned production levels and increasing the efficiency of coal production will be based on scientific and technological progress in the industry, improvement of drilling methods, impact on the seam, increasing the depth of extraction of reserves and the introduction of other advanced technologies of coal production, which will make the use of hard-to-recover reserves economically viable. In this article the developed structure of system of monitoring of a condition of installations and supply of spare parts is offered, allowing to provide in an operative mode monitoring of a condition of installations and to improve economic indicators of work not only a complex of installations as a whole, but also the mining enterprise.

Key words: automation pre-emergency situations neural networks spare parts and components trouble-free operation mining production industry

Receiving date: 06.09.2019

Approval date: 01.01.1970

Publication date: 30.12.2019

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