From a Magnifying Glass to a Neural Network

A Second to Decide

A quiet but consequential transformation has taken place at the Murashinsky Plywood Mill, one of the largest wood-processing facilities in Russia’s Volga region. Dozens of inspectors armed with magnifying glasses and notebooks are no longer needed to spend hours examining veneer sheets for cracks, knots, or resin pockets. They have been replaced by a high-precision robotic line that can analyze a veneer sheet measuring 1,400 × 2,600 mm in seconds, identify up to 29 types of defects, and decide whether the material should be repaired, regraded, or scrapped.

Behind this technological leap is the Russian company Robotech, a resident of the Skolkovo innovation center. Over the past three years, the company’s revenue has grown more than sevenfold, surpassing 380 million rubles (about $4 million).

A New Standard of “Smart” Manufacturing

The new system, built around a LineScan scanning platform and Synetra software that incorporates artificial intelligence and machine vision, goes well beyond basic automation. It functions as a full-scale quality management solution. The system not only detects defects but also predicts how a sheet will look after repair, selects the optimal remediation method, and assigns tasks to industrial robots.

The smallest detectable defect measures just 1.5 mm, while recognition accuracy reaches 98%. At the same time, the line processes up to 15 sheets per minute and fully eliminates heavy manual labor. Veneer stacks weighing up to three tons are fed automatically, removing one of the most physically demanding stages of production.

Deep integration with the plant’s ERP and MES systems is a key advantage of the solution. This enables remote monitoring and detailed analytics across every stage of production, while allowing operating parameters to be adjusted flexibly to meet specific customer requirements. Automation, in this case, is no longer a standalone module but part of a unified digital ecosystem spanning the entire enterprise.

While implementing this project, we took a new approach to automation. We acted not simply as an equipment supplier but as a technology partner that assumed full responsibility for design and integration of all systems into a single automated complex. We believe the future of industrial robotics lies in intelligent, flexible, turnkey solutions that do more than replace manual labor – they fundamentally change how production is managed

Denis Khudyakov

Chief Executive Officer, Robotech

A New Paradigm for Industrial Digitalization

The impact of deployment has been tangible. Defect rates have dropped sharply, productivity has increased, and reliance on human judgment has been reduced to a minimum. Notably, the Russian-developed system has outperformed foreign alternatives in accuracy and has proven more cost-effective both in implementation and ongoing operation.

Robotech’s project illustrates how AI and robotics are moving into traditional industries and shaping a new model of industrial digitalization. It also highlights Russia’s growing technological independence. Domestic solutions are no longer limited to replacing imports; they are increasingly offering more intelligent and economically efficient alternatives.

With only about 19% of Russian enterprises currently using robotic production lines, the potential for scaling is significant. Similar systems could be applied not only in timber processing but also in metallurgy, mechanical engineering, and the chemical industry. Full ERP and MES integration also makes these solutions more attractive for export, particularly to CIS countries, Eastern Europe, and Asia.

How AI Is Improving Profitability in Forestry

Russia’s timber sector is steadily entering the digital era. For more than five years, the industry has been adopting AI, robotics, and advanced IT solutions across the entire value chain, from logging to finished products. Import substitution has been a central focus. One early mover was Segezha Group, which in 2019 launched an AI system at its Segezha pulp and paper mill to predict defects and equipment downtime.

Similar technologies are now widely used to optimize operations. At Karelia Pulp, for example, an automated load-planning module cut the time required to prepare a full train-loading scheme from two days to just 40 minutes.

After Western vendors have left the Russian market, critically important MES systems that ensure production transparency and efficiency are now being developed domestically. Karelia-based companies Neosistemy Severo-Zapad LTD and Opti-Soft began this work well before 2022 and today offer solutions tailored specifically to the needs of Russia’s timber industry.

Novosibirsk-based NeuroLumber is counting on AI scanners such as BarkScan, KnotScan, and LogScan, which analyze wood and control cutting without human involvement, increasing yields of high-quality output. Ilim Group is going further by creating digital twins of its equipment. Deployment of this technology on a soda recovery boiler in Ust-Ilimsk is already delivering annual savings of $1 million. The company also uses drones for raw-material inventories, photo scanners to track timber volumes, and a WSO system to optimize logging operations.

Automation 2.0, Powered by Russian AI

In the coming years, the share of automated lines in traditional industries such as timber processing, chemicals, and metallurgy could rise to 30–40%. At the same time, Russia is actively developing its own AI-based production management platforms fully adapted to local conditions. Combining accessible pricing, deep localization, and growing technological maturity, Russian automated systems are increasingly viewed as competitive export products. As the experience of companies like Robotech shows, Russian developers are not just following global trends but beginning to shape them.