SUSU Develops Technologies of Industry 4.0 for the Global Hi-Tech Industry Enterprises

SUSU Develops Technologies of Industry 4.0 for the Global Hi-Tech Industry Enterprises

Implementing innovation production using the Big Data methods (big data mining) for analyzing information obtained from sensor networks is a most important trend in development of global economy. Today the world leading industrial corporations are already using these methods for prompt monitoring and collecting of information on the status of technological processes in production. Scientists believe that the fourth industrial revolution will very soon allow to unite virtual world with the real one.

The concept of a “digital enterprise” as a platform unifying an intellectual network of sensors installed on equipment of a real enterprise, and a virtual image of this enterprise in the form of a “digital twin” can be a solution of several global tasks. First and foremost, it means predicting and preventing accidents:

“The project by the SUSU scientists “Industrial Cloud Platform” studies the possibilities of creating the system of “Digital Twins” of production processes. A digital twin synchronizes with production processes in a real-time mode by means of processing data which it receives from intellectual wireless sensors. By combining digital twins of various equipment and technological processes we can create a digital twin of the whole enterprise. This provides us with a possibility of analyzing the current situation; that is, an engineer at a plant can receive current information on his computer regarding any section in the production chain. Secondly, this allows to predict behavior of certain equipment units and operation of the whole enterprise. For instance, by analyzing data received from sensors a digital twin will allow to assess the status and predict, let’s say, when equipment failure can occur,” explains Gleb Radchenko, Director of the SUSU School of Electrical Engineering and Computer Science.

SUSU already has wide experience in creating digital twins of industrial facilities. As an example we may name 3D models of rolling mills and hydroelectric power plants created by the SUSU’s division, Uctech-Profi Educational Equipment Manufacturer. The University also actively involves the world scientific leaders in the fields of information technologies and measuring systems for solving problems of the Russian enterprises. Thus, under Project 5-100 the Laboratory for Problem-Oriented Cloud Computing Environments was established at the University supervised by Professor Andrei Tchernykh, Director of the Parallel Computing Laboratory at the Center for Scientific Research and Higher Education at Ensenada (Mexico). To solve the tasks related to development of the new generation of the measuring instruments, a Laboratory for Self-Monitoring and Self-Validating Sensors and Systems was established under supervision of the University of Oxford Professor Manus Henry (United Kingdom).

A crucial task of a “digital enterprise” is production control automation and modernization of technological processes. In this field SUSU closely collaborates with the world leading manufacturer of sensor systems for the “Industry 4.0” enterprises, Emerson Corporation, as well as with an industrial giant of the Ural Region in steelworks – Magnitogorsk Iron & Steel Works.

“The first project is a system for assessing the condition of equipment and its influence on the quality of the goods produced by the steelworks factory. You cannot assess it beforehand, without sensors and without data mining based on sensors’ readings,” says Gleb Radchenko. “The second joint project of SUSU and Magnitogorsk Iron & Steel Works (MMK) is related to developing a machine vision system, which analyzes condition of the released goods, and through using mechanisms of artificial neural networks reveals possible defects. An actual example is rolling of steel, when defects have to be revealed on sheets of steel so that they are not delivered to a customer. SUSU is developing a system which could allow for automation of the process of rolling quality analysis through the “deep learning” technologies. Digital vision will allow to reveal various defects of such kind.”

Together with the leading manufacturer of equipment for steelworks automation SMS Group (Germany), SUSU is developing a project on studying the methods of data mining for controlling technological processes at steelworks enterprises. Ten teams are searching for the best solution to this most complicated task with using the technologies of data mining:

“The University teams of research scientists are analyzing information received from a large number temperature sensors (over 500 sensors). Their readings on the process of casting steel are collected 4 times per second. Using the obtained data it is necessary to reveal when the process may deviate from normal operation, detect this moment in time, and slow down the process of casting in order to prevent steel’s overflow and sticking. First results under this project will be received already in November of 2017,” notes Director of the SUSU School of Electrical Engineering and Computer Science.

The SUSU scientists performing these and other high-technology calculations use the help of the Supercomputer Simulation Laboratory, where three powerful supercomputers with the total computing capacity of 606 TFlops are installed. The University is proud of the Laboratory’s most powerful supercomputer, Tornado SUSU supercomputer, which features 29,184 processor cores and is on the 8th place in the top rating of supercomputers with the highest capacity in CIS countries.

Attached files
  • Laboratory Emerson Plantweb

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