Marius Becherer∗, Michael Zipperle†, Achim Karduck‡
Computer Systems Science and Engineering, Vol.35, No.2, pp. 81-89, 2020, DOI:10.32604/csse.2020.35.081
Abstract Machines are serviced too often or only when they fail. This can result in high costs for maintenance and machine failure. The trend of Industry 4.0 and
the networking of machines opens up new possibilities for maintenance. Intelligent machines provide data that can be used to predict the ideal time of
maintenance. There are different approaches to create a forecast. Depending on the method used, appropriate conditions must be created to improve the
forecast. In this paper, results are compiled to give a state of the art of predictive maintenance. First, the different types of More >
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