The Department of Artificial Intelligence and Big Data of Al-Farabi KazNU Demonstrated an Industrial Digital Twin at the Shin-Line Plant

On September 2, 2026, a working meeting was held at the Shin-Line production facility between representatives of the Department of Artificial Intelligence and Big Data of Al-Farabi Kazakh National University, SUPCON Central Asia, and the Shin-Line plant.
Digital Twin Demonstration
During the meeting, the KazNU team demonstrated the operational capabilities of a digital twin developed for the facility's refrigeration system. The demonstration featured real-time monitoring of operational data from two ammonia compressors, bearing wear modeling, and an automated alert sequence triggered by equipment failure risks. The system’s energy monitoring capabilities were also highlighted, showcasing the identification of deviations between planned and actual power consumption alongside their financial impact calculated in tenge.
M. O. Isenov, representing SUPCON Central Asia, presented the company’s operations and digital solutions for industrial facilities, emphasizing its platform designed for digital twin development and intelligent manufacturing process management.
Discussion Outcomes
The parties discussed potential avenues for integrating digital twin technology across Shin-Line’s production operations. Following the meeting, plant representatives highlighted the automated robotic warehouse as a priority area, expressing strong interest in digital twin solutions tailored to this facility. The parties agreed to explore opportunities for further collaboration in this direction.
Meeting Participants
The meeting was attended by the Dean of the Faculty of Mechanics and Mathematics of Al-Farabi KazNU, M. E. Mansurova; Director of the Commercialization Department, T. Azatuly; engineers of the Department of Artificial Intelligence and Big Data, N. B. Zhumakhan and A. M. Shakir; SUPCON Central Asia manager, M. O. Isenov; as well as Shin-Line representatives, including Director of the Automated Robotic Warehouse Department, Ms. Assel, and Department Director, Mr. Ulan.
Significance of the Meeting
The meeting reinforced partnerships among the university, the technology vendor, and the manufacturing enterprise, establishing a solid foundation for continued collaborative initiatives aimed at applying artificial intelligence and digital twin technologies to real-world industrial challenges.