Method of complex assessment of on-board information and control systems on mining machines

For a full-fledged information interaction of a vehicle with transport infrastructure and management, it is necessary to use intelligent transport systems, this can have a particularly serious impact on the cargo transportation process. To increase the coefficient of technical readiness of quarry excavators, intelligent systems are being implemented – information, diagnostic and telecommunication. Based on a system analysis of the functioning of excavators at a mining enterprise, the possibility of reducing the downtime of quarry excavators spent on maintenance and troubleshooting has been established, which means reducing economic losses. The directions of increasing the productivity of mining machines are determined, taking into account the influence of the technical condition of cargo vehicles. An approach is proposed to increase the coefficient of technical readiness of cargo transport through the introduction of on-board information and control systems. An algorithm for collecting and processing information received from on-board information and control systems of vehicles with the ability to track the technical condition of systems in real time and the subsequent creation of a resource forecasting model is presented. A method of integrated assessment of on-board information and control systems has been developed to select the optimal composition of systems depending on the weight of criteria affecting the efficiency of the vehicle.

Safiullin R. N., Safiullin R. R., Efremova V. A. Method of complex assessment of on-board information and control systems on mining machines. MIAB. Mining Inf. Anal. Bull. 2023;(9-1):49-63. [In Russ]. DOI: 10.25018/0236_1493_2023_91_0_49.

R.N. Safiullin¹, Dr. Sci. (Eng.), Professor, e-mail: safravi@mail.ru, ORCID ID: 0000-0002-8765-6461, 
R.R. Safiullin¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: safiyllin@yandex.ru, ORCID ID: 0000-0003-2315-3678,
V.A. Efremova¹, Graduate Student, e-mail: vikaefr99@gmail.com, ORCID ID: 0000-0002-3981-6061,
¹ Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.

R.N. Safiullin, e-mail: safravi@mail.ru.

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