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PRANA: Industry Standard of the Future

Economic effect generated by PRANA implementation: Cutting repair costs and reducing market fines by up to 60%

Industrial IoT solution for diagnostics and predictive analytics of industrial equipment to improve equipment performance and cut operating costs.

"PRANA (Predictive Analytics) – Predictive Analytics and Remote Monitoring System – a hardware-software package that enables the identification of deviations in the functioning of industrial equipment 2–3 months before the probable fault.
The PRANA industrial IoT solution combines methods of statistical analysis – the analytical core of the system, machine-learning technologies – an archive of defect symptoms, and big data processing tools – expert modules.
To collect equipment-performance parameters, the lower level of the System is deployed at the industrial site, thereby allowing for the safe collection and transmission of the data to the Situational Center. The PRANA System analyzes the data arriving from the running equipment in real-time and automatically detects any deviations, ranking them by contribution to the emerging defect.
This information is relayed to experts at the Situational Center, who generate the appropriate recommendations for the operating personnel. System-performance information and recommendations on maintaining equipment in good working order are available for customer personnel remotely and in mobile applications. Emergency alerts are sent via SMS, e-mail, phone calls and PUSH-notifications. Customers receive round-the-clock support, scheduled reports and recommendations on optimizing equipment performance and maintenance.

PRANA Economic Efficiency

Economic effect generated by the PRANA System implementation at one of Russia’s largest generating companies:
Incident count
The number of incidents in CCGT units.
Incident loss
Losses from power-unit downtime.
The system's operating principles
  • Mathematical Tools
  • System Architecture
  • Situation Center
  • Our Services

PRANA is based on the Multivariate Vector Statistical Model (MVSM).

An equipment model is created and configured using historical data. Behavioral abnormalities are detected using a single integrated T2 criterion and parameter imbalances, which are ranked automatically based on their contribution to the abnormalities. This approach has been developed specifically for monitoring equipment at nuclear power plants, where the reliability of equipment is considered to be the highest priority.


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The MVSM (Multivariate Vector Statistical Model) core is needed to create and play multidimensional models of the equipment state.

Playing models based on actual operational data makes it possible to identify deviating parameters in the operation of industrial equipment with extremely high sensitivity. This is the case even if they do not yet affect the state of the installation, which means they are not recorded by traditional control and monitoring systems.


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The Situation Monitoring Center provides 24/7 facility monitoring.

The dispatcher is alerted at the slightest deviation. The system automatically identifies the location and time of the incident.

Deviations are reported to the Expert Analysis Center, where the experts prepare their conclusion based on automatically generated recommendations for equipment maintenance.


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The ROTEC Situation Center provides remote monitoring and predictive analytics of industrial equipment.

The Center's team includes experts with many years of experience in both science and practical work in the area of vibration diagnostics and vibration adjustment, turbine, compressor, boiler, thermal and electrical equipment.


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238 accidents
have been prevented
by PRANA continuous monitoring
3 500 000 hours
of equipment digital operating time
have been analyzed
2 500 tags
are processed every second
on each power-generating unit
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© PRANA: Predictive Analytics and Remote Monitoring System, 2024

15 Nikoloyamskaya St., Moscow,
109240, Russia