DIGITAL TWINS OF INDUSTRIAL FACILITIES AND URBAN INFRASTRUCTURE
Key laboratories carrying out the project are
– Educational and scientific laboratory «Artificial intelligence and cybersecurity»
– Educational and scientific laboratory «Mining»
– Educational and scientific laboratory «Construction»
Project description:
The project is focused on creating digital twins of industrial equipment, production complexes, energy facilities, warehouse logistics and urban infrastructure. The digital twin is a virtual model of an object that receives real-time data from sensors, automated control systems and enterprise information platforms.
Unlike traditional monitoring systems, a digital twin not only displays the current state of the facility, but also allows you to predict its behavior, assess the consequences of various operating scenarios, identify hidden defects and make informed management decisions before emergency situations occur.
The project is developing digital twins of turbine units and steam boilers of thermal power plants, ball mills of processing plants, methodical furnaces of metallurgical enterprises, tailings dumps of mining companies, warehouse complexes and urban infrastructure facilities, including digital twins of urban areas for modeling traffic congestion, etc.
For tailings dumps and large infrastructure facilities, integration with unmanned aerial vehicles and remote monitoring systems is provided, which makes it possible to obtain up-to-date information about the condition of structures and predict the development of potentially dangerous processes.
Digital models of districts are being created for urban infrastructure with the ability to analyze traffic flows, the environmental situation and prospects for the development of the urban environment.
Key technological solutions:
Digital power equipment twins;
Digital twins of enrichment complexes;
Intelligent monitoring of equipment technical condition;
Integration with industrial sensors and control systems;
Forecasting accidents and failures;
Simulation of technological processes;
Digital models of tailings;
Integration with UAVs and geoinformation systems;
Analytical panels for production control.
Practical impact and results:
The project allows us to move on to a proactive model of equipment operation and to predictive control of production processes. Due to the early detection of deviations, repair and maintenance costs are significantly reduced, emergency downtime is reduced and the reliability of technological complexes is increased.
For energy and metallurgy enterprises, an additional advantage is the optimization of equipment operating modes and reduction of energy consumption. For mining companies, the ability to constantly monitor the condition of tailings dumps and increase the level of industrial safety is of particular value.
The digital twin at enterprises of the Kyrgyz Republic is becoming the basis for further digital transformation and implementation of intelligent technologies in Industry 4.0.