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Extractive industry
10:47, 02 March 2026
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Underground Digital Shift in Norilsk

In Norilsk, a new digital system for shift-by-shift inspection of underground mining equipment has been deployed. The initiative marks a transition from traditional visual checks to structured digital monitoring and IT-based control, signaling a broader modernization of mining operations in one of Russia’s most strategically important resource regions.

Moving to a New Operational Level

The program is being implemented at the Oktyabrsky mine, part of the Zapolyarny Branch of Norilsk Nickel. Introducing digital tools in a traditionally conservative mining sector carries particular weight, given the historical dominance of low-automation processes. This deployment represents an initial step toward wider use of IT automation, predictive analytics and digital twins for mining equipment.

Operators access inspection data through a mobile application. Previously, routine technical inspections required extensive paperwork. Now, completing the process involves capturing a series of photographs of the equipment. This approach not only saves significant working time but also improves inspection quality by standardizing data capture and documentation.

Information is available not only to operators but also to management teams. Eliminating paper-based records enables creation of a fully integrated digital ecosystem. Within months, this model is expected to reduce equipment downtime. The system retains comprehensive statistics and a digital production footprint, including repair histories and breakdown timelines, allowing engineers to identify patterns and build predictive maintenance models.

At the pilot stage, approximately 70 units of equipment are being integrated into the platform. In the long term, the remaining machines will also transition to electronic tracking. Ultimately, the system will unify a fleet of approximately 250 underground mining units.

The site has also introduced a machine vision system that enables a video analytics module to detect foreign objects during ore transport on conveyor belts. Wooden supports, metal reinforcement and oversized ore fragments that accidentally enter the flow are identified and removed promptly. This reduces the risk of crusher damage and unplanned production stoppages. The system continues to improve through iterative learning. By April, developers expect operational accuracy to reach 90 percent.

Our company has long invested successfully in projects based on artificial intelligence, recognizing them as practical tools for improving efficiency and safety. Joining the Alliance and participating in industry working groups is a logical continuation of this strategy and an important step to ensure Norilsk Nickel’s interests are considered in the review of legislative initiatives in the field of AI. We intend not only to adopt best practices but also to share our own successful experience, working with partners to strengthen the country’s technological capacity
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Regional in Scope, Global in Significance

Although the deployment is regional, it forms part of a larger digital transformation of traditional resource industries, with potential evolution into a platform-based IT service for processing and analyzing mining enterprise data.

Norilsk Nickel’s experience in developing the concept of digital mines, featuring real-time monitoring and simulation of mining operations, dates back to 2019. The program Tekhnologichesky proryv (Technological Breakthrough) increased production efficiency, enhanced workplace safety and optimized management processes. The first operational dispatch centers were launched at mines within the Zapolyarny Branch. As part of the program, underground infrastructure was established, including 189 kilometers of fiber-optic cable and more than 1,400 Wi-Fi access points. The company also developed a simulation modeling system unique in Russia and the CIS, generating digital mine models. The platform incorporated data on underground workings, geometry and both active and reserve transport fleets to calculate optimal equipment volumes required to meet production targets.

Subsequently, the company developed software known as Dekadno-smenny grafik (Ten-Day Shift Schedule), which allocates workloads and equipment across workings and shifts based on process cycles and predefined parameters. An Automated Mining Operations Management System processes real-time data on shift performance. The Tekhnologichesky proryv program set objectives to increase productivity of mining units by up to 10 percent, ensure mined ore quality meets established standards and prepare feedstock for downstream processing. By 2020, the company had completed baseline automation of its production assets under this program.

Scaling Digital Solutions

Today, automation of mining equipment in Russia is expanding at scale. Autonomous drilling rigs and other machinery equipped with digital passports are becoming more common. The transition is supported by adjacent sectors. For example, municipal service fleets are integrating GLONASS tracking and AI-enabled systems while shifting to digital monitoring platforms.

Government programs and industry initiatives are guiding this process, promoting digital transformation across the economy, including AI and big data development strategies. Digital oversight of mining equipment therefore represents part of a broader structural shift toward data-driven industrial management.

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