The introduction of a self-isolation regime, along with measures to prevent the rapid spread of coronavirus infection, has affected many businesses, and has brought some to a complete halt. However, IIoT solutions have revealed new opportunities for responding to the changing situation. The PRANA hardware and software complex has made it possible to minimize the negative consequences of the ongoing situation. One of its new modules – ‘Operations Log’ – is now the main mode of communication between operational personnel of power stations.
The functionality of the distributed expert community implemented in PRANA a year ago brought together more than 140 professionals from the energy and oil and gas sectors of eight regions of Russia and Kazakhstan in a digital office. Under the conditions of self- isolation and remote work, monitoring and forecasting the technical condition of equipment connected to PRANA, worth more than 5 billion USD, is not interrupted for a second.
In the ‘Event Log’, users will see prompt notifications, generated automatically by the PRANA complex, about any changes and deviations in the operation of technological equipment. Through the system’s ‘Operations Log’, on-site personnel can exchange the necessary information with the Situation Center in real time and receive the necessary recommendations for correcting deviations. The PRANA interface allows users to visualize all the necessary graphs of parameter variances and to record the response actions of operational personnel on site.
When introducing new modules, some Users considered their functionality redundant, but the current situation has confirmed their practicality and effectiveness when deploying remote workstations and coordinating more than a hundred specialists interacting around the clock in different time zones.
The PRANA hardware and software complex (https://prana-system.com) – is an industrial IoT solution which identifies defects in the operation of industrial equipment 2-3 months prior to potential accidents. The system combines methods of statistical analysis, digital product imaging, an instrumental technique for working with big data and machine-learning technologies. The total cost of the connected equipment is about 5 billion USD, with a total capacity of more than 3.5 GW.