20 January 2020 year ROTEC and Siemens to Develop Joint Projects

ROTEC and Siemens have signed a cooperation agreement to build a unified information environment in the energy sector. The document was signed by Ivan Panasyuk, General Director of ROTEC JSC, and Zhanna Shalygina, Director of Siemens Digital Industries in Russia.

The agreement provides for cooperation between the parties in the field of automation, dispatching energy facilities and developing systems for predictive analytics in Russia using solutions which are already in use in both companies. The partners intend to support each other in scientific and research activities, share information on their ideas and developments in the field of automation and dispatching, carry out marketing research and other undertakings.

“Cooperating with Siemens is an excellent opportunity for ROTEC to scale up our solutions, which already ensure the reliable operation of facilities generating 3.5 GW in Russia and Kazakhstan. I’m sure that through combining our efforts and using the unique expertise of ROTEC in the field of predictive analytics and monitoring of all types of power-generating turbines and an extensive range of industrial equipment, we will be able to establish a new dynamic in the processes of industrial digitization, to achieve safer and more effective operation,” noted Ivan Panasyuk.

“The implementation of predictive programs and analytic tools by companies in recent years has become a noticeable trend, and demand is growing steadily. They are especially important for infrastructural facilities where the cost of fault, error or downtime is extremely high. The signed agreement is an extension of our collaboration with ROTEC JSC. Together, we shall strive to create systems for predictive analytics, primarily for large industrial and energy facilities. The advanced technical solutions offered by Siemens and the experience of ROTEC will help companies to move from the concept of problem solving to the idea of problem prevention, which allows for considerable cost saving and production process optimization”, said Zhanna Shalygina.

The PRANA Predictive-Analytics and Remote-Monitoring System ( – is an industrial IoT solution that identifies defects in the operation of industrial equipment 2-3 months prior to possible accidents. The system combines methods of statistical analysis, digital product imaging, an instrumental technique for working with big data and machine-learning technologies. The cost of connected equipment is over $4 billion.

Siemens AG (headquartered in Berlin and Munich) – is a leading global technology concern that has stood for engineering excellence, innovation, quality, reliability and internationality for more than 170 years. The company is active in more than 200 countries, focusing on the areas of electrification, automation and digitalization. Siemens is one of the world's largest suppliers of energy-efficient, resource-saving technologies. The company is a leading supplier of gas and steam turbine plants for effective power generation, a provider of power transmission solutions, and a pioneer in the field of infrastructure solutions, automation technologies and software solutions for industry. Siemens is a major manufacturer of medical equipment for visualization (computer and magnetic resonance imaging units) and laboratory diagnostics. In the 2019 fiscal year, which ended on 30 September 2019, Siemens generated revenue of 86.8 billion euros and a net income of 5.6 billion euros. For more details, please visit: or

Siemens LLC is the parent company of Siemens AG in Russia, Belarus, and Central Asia. In these countries the concern works in all the traditional fields of activity, is present in more than 40 cities and is one of the leading suppliers of products, services, and complete solutions for modernizing key sectors of the economy and infrastructure. Siemens LLC has around 3,400 employees. In the 2019 fiscal year (as of 30 September), the company generated revenue of 1.1 billion euros. For more details, please visit company website:

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