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Maintenance 4.0: intelligent and predictive maintenance system architecture

2018Conference paper Restricted access
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dc.contributor.authorCachada, Ana
dc.contributor.authorBarbosa, José
dc.contributor.authorLeitão, Paulo
dc.contributor.authorGeraldes, Carla A.S.
dc.contributor.authorDeusdado, Leonel
dc.contributor.authorCosta, Jacinta Casimiro da
dc.contributor.authorTeixeira, Carlos
dc.contributor.authorTeixeira, João Manuel
dc.contributor.authorMoreira, Antonio H.J.
dc.contributor.authorMoreira, Pedro Miguel
dc.contributor.authorRomero, Luís
dc.date.accessioned2020-03-31T09:36:35Z
dc.date.available2020-03-31T09:36:35Z
dc.date.issued2018
dc.description.abstractIn the current manufacturing world, the role of maintenance has been receiving increasingly more attention while companies understand that maintenance, when well performed, can be a strategic factor to achieve the corporate goals. The latest trends of maintenance leans towards the predictive approach, exemplified by the Prognosis and Health Management (PHM) and the Condition-based Maintenance (CBM) techniques. The implementation of such approaches demands a well structured architecture and can be boosted through the use of emergent ICT technologies, namely Internet of Things (IoT), cloud computing, advanced data analytics and augmented reality. Therefore, this paper describes the architecture of an intelligent and predictive maintenance system, aligned with Industry 4.0 principles, that considers advanced and online analysis of the collected data for the earlier detection of the occurrence of possible machine failures, and supports technicians during the maintenance interventions by providing a guided intelligent decision support.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCachada, Ana; Moreira, Pedro Miguel; Romero, Luis; Barbosa, José; Leitão, Paulo; Geraldes, Carla A.S.; Deusdado, Leonel; Costa, Jacinta; Teixeira, Carlos; Teixeira, Joao; Moreira, Antonio H.J. (2018). Maintenance 4.0: intelligent and predictive maintenance system architecture. In 23rd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’18). Politecnico di TorinoTorino; Italy. p.139-146pt_PT
dc.identifier.doi10.1109/ETFA.2018.8502489pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/21251
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPredictive maintenancept_PT
dc.subjectIntelligent maintenancept_PT
dc.subjectIoTpt_PT
dc.subjectData analysispt_PT
dc.titleMaintenance 4.0: intelligent and predictive maintenance system architecturept_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9876 - Politécnicos/SAICT-POL%2F23725%2F2016/PT
oaire.citation.conferencePlacePolitecnico di TorinoTorino; Italypt_PT
oaire.citation.endPage146pt_PT
oaire.citation.startPage139pt_PT
oaire.citation.title23rd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’18)pt_PT
oaire.fundingStream9876 - Politécnicos
person.familyNameCachada
person.familyNameBarbosa
person.familyNameLeitão
person.familyNameGeraldes
person.familyNameDeusdado
person.familyNameCosta
person.givenNameAna
person.givenNameJosé
person.givenNamePaulo
person.givenNameCarla A.S.
person.givenNameLeonel
person.givenNameJacinta Casimiro da
person.identifier609187
person.identifierA-8390-2011
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person.identifier.ciencia-id641A-C527-2050
person.identifier.ciencia-idD11B-A19D-97CF
person.identifier.orcid0000-0003-0936-1817
person.identifier.orcid0000-0003-3151-6686
person.identifier.orcid0000-0002-2151-7944
person.identifier.orcid0000-0003-0187-1281
person.identifier.orcid0000-0002-9944-4386
person.identifier.orcid0000-0001-8916-0585
person.identifier.ridA-5468-2011
person.identifier.ridV-4290-2017
person.identifier.scopus-author-id57200413375
person.identifier.scopus-author-id48360905400
person.identifier.scopus-author-id35584388900
person.identifier.scopus-author-id25122283900
person.identifier.scopus-author-id37561352100
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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