Saint-Petersburg Mining University, Saint-Petersburg, Russia:

Beloglazov I. I., Associate Professor of Department for Automation of Production Process Flows, Candidate of Engineering Sciences, beloglazov@spmi.ru
Petrov P. A., Dean of Mineral Processing Faculty, Candidate of Engineering Sciences
Bazhin V. Yu., Head of Department for Automation of Production Process Flows, Doctor of Engineering Sciences, Associate Professor

According to the top-priority trends and challenges in the mineral sector, and as per the mining science strategy, it is highly critical to arrange enhanced control, prediction and safety of production objects and their functioning for the preservation of automation sustainability. Improved control of databases, regulatory bonds, management, logistics and principles of sustainable development in mining makes it possible to reduce technological deviations and accidents at large mining and processing plants. Most procedural violations and accidents in surface and underground mines occur because of the unskilled actions of process flow operators. Damage in this case can be considerable, especially as compared with the expenses connected with qualitative training and persistent development of personnel engaged with supervisory control and data acquisition for the efficient operation of SCADA-systems within the automation framework of mining and processing plants. Definition of digital systems and their interrelation with multilevel automated control can be incorrect. The review of new principles can awaken interest in the conceptual assessment of digitalization processes using such notions as: numerical models, simulator, and artificial intelligence. Often applied formulations and principles of a digital model are substituted without justification of functional connections. On the other hand, a digital system today can be assumed as robotic lines and other numerical models and smart technologies, for instance, machining stations with numerical program control. It is necessary to define the practical significance of conceptual modifications and digital transformation regarding objects of the mineral sector, using Big Data; to understand how a digital twin can influence a changeable process situation; to provide prompt prediction; to eliminate an accident; and to preserve the physical balance in the whole production system. Such intelligent and flexible productions particularly need computerbased simulators and digital twins based on technologies of Industry 4.0–extended and virtual reality on the basis of digital twins. Digital twins allow maximal simulation of real-life activity of process flow operators. The skills acquired by personnel after such simulation training enable operators to master the optimized procedure for functioning in emergency situations in mineral mining and processing. This paper exemplifies the remote training and control of process flows, which is of concern in the current international situation.

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