American management consulting company McKinsey included Russia in the top 5 most digitally developed countries. The report shows that from 2011 to 2015, the volume of digital economy in the country increased by 59 % (8.5 times faster than in any other sector). In 2025, its share of GDP could potentially triple and hit 10 trillion rubles.
ROTEC – a Russian energy turbine maintenance company – has built up the largest information database on rotary generators in the country. In 2011, they began developing systems that would allow them to use this information to its full potential. Four years later, Russian R&D developers launched the PRANA hardware-software package, the first of its kind, commercially available, IIoT solution independent of OEM that monitors and predicts the condition of energy systems, 2–3 months before a possible incident may occur. The company claims that the name PRANA was formed by combining syllables of two Russian words for "PRedictive ANAlytics". This facility is much like a high-tech oil refinery, processing tremendous amounts of big data to make high-precision predictions about the behaviour of various types of industrial equipment, constructing a digital infrastructure that integrates all the systems of the enterprise and monitors technical and technological relationships.
The PRANA facility is much like a high-tech oil refinery, processing tremendous amounts of big data to make high-precision predictions about the behaviour of various types of industrial equipment.
"Any complex machine, be it a turbine or energy converter, will break down occasionally. And the control panel reacts only after something has malfunctioned. What do we do? We go out and look for the signals long before the breakdown occurs or when it is "set to happen", and we warn the experts about it. In reality, the depth of our prognosis is approximately 3 months for power generating facilities". - Mikhail Lifshitz, Chairman of the Board of Directors of ROTEC JSC.
The PRANA ecosystem allows us to combine various types and models of industrial equipment within a single expert environment.
Since 2015, this facility has been operating on a 24/7 basis and allows us to prevent unforeseen malfunctions and breakdowns of industrial equipment, making the entire production chain transparent, and thus predictable and highly effective. After 5 years of the PRANA facility being in operation, the Russian energy industry has made remarkable progress. Having started with one thermal power plant in Perm, by 2020, ROTEC has digitised and secured 22 electrical power units under the protection system in 9 regions across Russia and Kazakhstan with total capacity of 3.5 GW. Experts have highlighted that PRANA has now virtually become the industry standard for power generating companies, and insurance companies provide more favorable conditions to those whose equipment is under the control of the System. These power engineering
Mnemonic diagram of a gas turbine in the interface of the PRANA hardware-software package benchmarks seemed appropriate in other enterprises that included crucially important infrastructure, mainly in the oil and gas sector. Back in 2019, the System found its way into the equipment of Gazpromneft's oil production facility. Gazpromneft-Vostok LLC and ROTEC JSC implemented a project to digitise the oil production companies' equipment at the Shinginsk field. The PRANA prognostics system was connected to four 6-megawatt gas-turbine units (GTU-6PM) manufactured by
UEC-GT-R&D Saturn, three booster compression units of type TAKAT 77.3-23M3 MCC1 manufactured by Kazankompressormash JSC, and two compressor units of type JGF/4 manufactured by ARIEL, USA. Generally speaking, as of today, the PRANA package is integrated into equipment with a total value of 5 billion USD.
Hardware-software packages can be briefly described as follows. Based on the analysis of historical data, a mathematical model of the equipment’s operating condition is created. When operating in real-time, the package continuously monitors the status of the connected equipment and informs the operating personnel about detected trends in developing emergency modes with recommendations for the maintenance of normal operations. Mathematical models, machine learning and artificial intelligence determine the interdependence of operational parameters that cannot be determined by existing local control systems. The PRANA package reveals long-term changes in the technical conditions of the equipment and provides additional time to locate and liquidate a problem at an early stage, whilst the local APCS (automated process control system) protects the equipment from fast-developing dysfunctions. PRANA has already been integrated into practically every APCS on the market: I&C Tekon, I&C ALSPA ControGaz, I&C KVINT 7, I&C KRUG, I&C Mark VIe, I&C PCS7, I&C OC6000e, I&C Ovation, I&C SPPA-T3000.
Various monitoring systems, predominantly operated by equipment manufacturers, have extensive industrial applications. However, it is necessary to highlight two important aspects. Firstly, every manufacturer uses their own personal solutions and interface for their equipment. This means that control over the parameter settings will have to be monitored intermittently on various devices. Whereas PRANA combines all the indicators within one ecosystem. Secondly, it might be somewhat difficult to be objective when speaking of a control system provided by the manufacturer interested in the supply of spare parts and providing maintenance services... just as difficult as it would be having to rely on a fox for the security of a chicken coop.