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Advisor(s)
Abstract(s)
The present paper describes the state of the art related to IIoT Devices
and Cyber-Physical systems and presents a use case related to predictive maintenance.
Industry 4.0 is the boost for smart manufacturing and demands flexibility
and adaptability of all devices/machines in the shop floor. The machines must
become smart and interact with other machines inside and outside the industries/factories.
The predictive maintenance is a key topic in this industrial revolution.
The reason is based on the idea that smart machines must be capable to
automatically identify and predict possible faults and actuate before they occur.
Vibrations can be problematic in electrical motors. For this reason, we address
an experimental study associated with an automatic classification procedure, that
runs in the smart devices to detect anomalies. The results corroborate the applicability
and usefulness of this machine learning algorithm to predict vibration
faults.
Description
“This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Electrical Engineering. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-91334-6_40"
Keywords
Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance
Citation
RÚBIO, E.M. ; DIONÍSIO, R.P. ; TORRES, P.M.B. (2019) - Industrial IoT devices and cyber-physical production systems: review and use case. In: MACHADO, J. ; SOARES, F. ; VEIGA, G. (eds) - Innovation, Engineering and Entrepreneurship. HELIX 2018. Lecture Notes in Electrical Engineering. Cham: Springer. ISBN 978-3-319-91334-6. Vol. 505, p. 292-298
Publisher
Springer