Rosneft Rolls Out Fully Automated Maintenance Planning Software
Engineers at a Rosneft research institute have developed Russia’s first software system to automate maintenance and repair planning for industrial equipment, aiming to cut costs, reduce errors, and streamline plant operations.
Specialists at a Rosneft research institute in Volgograd have developed the first Russian software solution for automating maintenance and repair planning at industrial enterprises.
The new system optimizes repair costs, saves time, and eliminates the risk of errors while significantly reducing the workload of office staff by automating the creation of defect reports and cost estimates. It relies on a database covering equipment, materials, and operational procedures. According to the company, the solution reduces document preparation time by an average of sixfold while eliminating documentation errors entirely.
The System Plans Itself
The common rule of thumb “if it isn’t broken, don’t fix it” does not apply to oil refining and petrochemical operations, where the cost of oversight can reach millions. At the same time, preparing for scheduled maintenance is a complex process. Planning a major overhaul requires compiling a detailed defect report that includes the sequence of repair operations, required materials, and technical equipment. The accompanying cost estimate must account not only for materials and machinery but also for labor time. Notably, only qualified personnel can prepare such documentation.
With automation, documentation tasks are completed without errors and up to six times faster. Importantly, automation extends beyond defect reports and estimates. The system includes a detailed database of all plant equipment. To plan a major overhaul, a user simply selects the required asset from the list, after which the software automatically determines the optimal set of repair operations and materials.
Optimizing the Most Expensive Repairs
The significance of this development lies at the intersection of IT, oil refining, and maintenance management. The solution targets one of the most expensive and sensitive processes in industrial operations – major equipment overhauls. This improves safety, reduces downtime, and helps companies manage production costs more effectively. At the same time, the product is a fully independent industrial software solution.
In 2026, Rosneft PJSC emphasized that it has already developed a portfolio of domestic, science-intensive software for key processes. In absolute terms, this includes 24 software products, 17 of which have already been deployed in production. This shows not a one-off success but a long-term strategy to build an in-house industrial digital toolkit. Additional value comes from the accumulation of proprietary Russian data, operational practices, and repair libraries within internal systems rather than external software platforms.
Industry Benchmarks and Market Shift
In August 2024, Kazanorgsintez implemented a solution to improve turnaround maintenance efficiency, providing a comparable example. During a scheduled shutdown at a polycarbonate plant, 2,500 units of equipment were serviced, with digital tools used to improve repair efficiency.
Also in 2024, SIBUR publicly described its use of AI to monitor equipment condition, predict failures, and support decisions on repair, modernization, and replacement. Across the industry, this reflects a shift from manual and reactive maintenance toward digital lifecycle management of industrial assets.
The Industrial Competence Center, established by the Russian government for priority sectors, includes 16 high-maturity projects in the oil and gas, petrochemical, and subsoil use segment. Many of these are already ready for commercialization and are being used by multiple participants. In this environment, maintenance and repair software has the potential to move beyond corporate use and become a broader industrial product. By 2027, the sector is expected to fully transition to domestically developed solutions.
A logical next step is to move beyond automating repair documentation toward a broader ecosystem that integrates equipment diagnostics, predictive analytics, digital twins, mobile tools for maintenance teams, and resource planning systems. This shift – from digitizing individual operations to end-to-end asset and maintenance management – mirrors the direction taken by global industrial solution providers.
