Engineering Education and Cloud-Based Digital Twins for Electric Power Drive System Diagnostics

Abstract

Industry 4.0 concept is associated with introducing the new digital technologies to increase the competitiveness of an industrial enterprise or of an industry sector where it is being implemented. One of the important technologies improving the competitiveness are those used for diagnostics before and after a failure occurs - predictive maintenance and fault diagnosis. These enable to increase reliability of the equipment by efficiently planning and scheduling service and this way reducing or even eliminating the downtime at minimal service costs. For this purposes the advanced simulation techniques - Digital twin technologies along with Cloud services and Big data processing are increasingly implemented. The paper focuses on introducing these technologies into the educational process of the electrical engineers. The demand on industry digitalization and the rapid developments of digital technologies require the academia to keep up and introduce the basics of the technologies into the training process of the future electrical engineers. In modern world the competitiveness of the national industry as well as the engineers themselves is based on the interdisciplinary competences in the sphere of electrical engineering and the emerging digital technologies.