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Industrial IoT devices and cyber-physical production systems: review and use case

2019Book part Open access
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dc.contributor.authorRubio, Eva Masero
dc.contributor.authorDionísio, Rogério Pais
dc.contributor.authorTorres, Pedro
dc.date.accessioned2018-06-11T16:17:32Z
dc.date.available2020-12-31T01:30:21Z
dc.date.issued2019
dc.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"pt_PT
dc.description.abstractThe 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.citationRÚBIO, 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. 292-298pt_PT
dc.identifier.doi0.1007/978-3-319-91334-6_40pt_PT
dc.identifier.isbn978-3-319-91334-6
dc.identifier.urihttp://hdl.handle.net/10400.11/6097
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-319-91334-6_40pt_PT
dc.subjectCyber-physical systemspt_PT
dc.subjectIndustrial IoTpt_PT
dc.subjectSmart factoriespt_PT
dc.subjectMachine learningpt_PT
dc.subjectPredictive maintenancept_PT
dc.titleIndustrial IoT devices and cyber-physical production systems: review and use casept_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage298pt_PT
oaire.citation.startPage292pt_PT
oaire.citation.titleLecture Notes in Electrical Engineeringpt_PT
oaire.citation.volume505pt_PT
person.familyNamePAIS DIONÍSIO
person.familyNameBAPTISTA TORRES
person.givenNameROGÉRIO
person.givenNamePEDRO MIGUEL
person.identifier30skvuAAAAAJ
person.identifierK-5331-2015
person.identifier.ciencia-id2F1A-414F-368B
person.identifier.ciencia-id2711-E707-519C
person.identifier.orcid0000-0002-6810-2447
person.identifier.orcid0000-0003-4835-5022
person.identifier.scopus-author-id56261515100
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublicationfa3cfc92-0ec0-412b-9441-d657fc131926
relation.isAuthorOfPublication9d9ad49f-3c45-4a99-be21-7f13965c2628
relation.isAuthorOfPublication.latestForDiscoveryfa3cfc92-0ec0-412b-9441-d657fc131926

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