Operation Principles of PRANA System

The local server receives data on equipment operation from the automatic process control system and through other interfaces. Then the server software analyzes, archives, and transfers data to ROTEC or the Client's Situational Center. PRANA can be embedded in any control and management system without requiring any changes to the system.

The mathematical apparatus of PRANA's system works on the Situational Center server. To identify defects and deviations, the system creates a 'digital portrait' of serviceable equipment based on technological data on its operation in various modes. This model is then regularly updated online. As such, its accuracy increases every day.


Running the model on incoming online data allows you to identify deviations at an early stage of their manifestation, 2-3 months before their uncontrolled development leads to an emergency situation

Today’s traditional control and monitoring systems determine the threat of reliable equipment operation by one or several parameters immediately before an incident, when the number of causes of failure increases sharply, as well as damage from equipment damage. PRANA brings suspicious deviations to experts' attention ahead of time to avoid accidents.

The results of data analysis are transmitted to management's mobile apps and Situational Center experts and client terminals. Emergency alerts are sent via text messages, e-mails, calls, and push notifications. The client receives 24/7 support, advanced reporting, and recommendations for optimizing equipment operation.


In addition, PRANA has the functionality to create cloud expert teams

Authorized experts can remotely process, share, and comment on technological data. Joint work with remote experts allows the company's intellectual capital to be fully used. This is especially the case if the production structure is distributed, as is the case in the energy, oil and gas, and mining industries.

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© PRANA: Predictive Analytics and Remote Monitoring System, 2023

15 Nikoloyamskaya St., Moscow,
109240, Russia