AI as the Technician of the Future
Predict, not react – artificial intelligence is reshaping the rules of the game in Russia’s machine-building industry.
A Digital Medical Record for Machines
A project launched in Russia’s Nizhny Novgorod region could mark a turning point for the country’s machine-building sector. A joint development by the R.E. Alekseev Nizhny Novgorod State Technical University and EMG LLC has moved beyond the laboratory stage and is now operating in live production. The company has deployed an AI-based system for real-time diagnostics and monitoring of its machine-tool fleet. This is not a routine software update or a simple sensor upgrade – it represents a fundamental shift in how industrial equipment is managed.
The system operates around the clock, analyzing hundreds of parameters, including vibration, temperature, spindle load, energy consumption, and more. Its defining feature, however, is predictive capability. AI algorithms detect latent anomalies and flag potential failures weeks or even months before they surface. This allows manufacturers to schedule maintenance without emergency downtime, save millions of rubles, and extend the service life of high-value machinery. Each machine is now assigned a “digital passport” – a unified record of its operational history, technical condition, and performance forecasts. In effect, it is an electronic medical record for industrial equipment.
A Domestic Digital Platform Without Import Dependence
The solution has already been deployed at EMG facilities, but its implications extend well beyond a single plant. It serves as a pilot example of a Russian-built predictive maintenance platform developed entirely within the country. At a time when technological sovereignty and import substitution have become strategic priorities, reducing reliance on foreign software and services is no longer just a competitive advantage but a matter of national security.
The economic impact of such systems is tangible at both regional and federal levels. Reduced downtime directly translates into higher output, improved margins, and greater operational resilience. Russia’s ministries responsible for digital development and industrial policy actively support these initiatives, incorporating them into national programs focused on domestic software development and industrial digitalization.
Russian Industry Moves Toward Predictive Maintenance
Predictive Maintenance (PdM) is a well-established concept among global industrial leaders. General Electric developed its Predix platform, Siemens introduced MindSphere, and Schneider Electric rolled out EcoStruxure Asset Advisor. All rely on IoT and AI to anticipate failures, minimize losses, and extend equipment lifecycles.
Russia is keeping pace with these global trends. One notable example is PRANA, a system developed by Rotek JSC, the country’s first domestic IIoT platform for fault prediction. Registered in Russia’s national software registry and in the United States, PRANA identifies defects two to three months before they reach a critical stage. Since 2015, it has been operating at power facilities including the Perm CHPP-9 and Kazan CHPP-1, as well as industrial sites in Kazakhstan. Today, the system is used at power plants, oil refineries, chemical and nuclear reactors, and metallurgical facilities.
In recent years, Russian industry has increasingly embraced artificial intelligence as a practical tool for improving reliability and economic efficiency. Leading companies are deploying AI-driven systems for maintenance and repair management, shifting from reactive responses to predictive strategies.
Gazprom Neft uses big data analytics to forecast equipment wear, with algorithms identifying anomalies in real time and recommending preventive actions that reduce downtime and costs. Rosatom applies AI to nuclear plant diagnostics, where neural networks process data from thousands of sensors and cameras to minimize accident risks. Norilsk Nickel plans maintenance proactively using AI monitoring, cutting costs and accelerating equipment recovery. Lukoil has developed its own system to pinpoint which components of oilfield equipment require urgent replacement, extending asset lifecycles and preventing unexpected shutdowns.
AI Redefines the Philosophy of Manufacturing
In Russia, artificial intelligence is no longer an experiment but a working tool that enhances safety, reduces costs, and strengthens technological independence across critical industries.
The Nizhny Novgorod development fits squarely into this national trajectory while focusing specifically on machine building. In the coming years, the system is expected to expand to other enterprises and be adapted for different types of machine tools and production lines. Over the medium term, such solutions could become standard components of national digital economy programs. With successful certification and scaling, the platform may also evolve into an export product, as demand for predictive maintenance solutions is growing across CIS countries, Asia, and the Middle East.
The launch of this technology symbolizes a shift from emergency repairs to proactive management. It is not merely about “smart sensors,” but about a new manufacturing philosophy – one in which people no longer wait for failures but rely on machines to take care of other machines, with good reason.
