Repository logo
 
Publication

Advanced sensor-based maintenance in real-world exemplary cases

2020Journal article Open access
Simple item page
dc.contributor.authorAlbano, Michele
dc.contributor.authorLino Ferreira, Luis
dc.contributor.authorOrio, Giovanni Di
dc.contributor.authorMaló, Pedro
dc.contributor.authorWebers, Godfried
dc.contributor.authorJantunen, Erkki
dc.contributor.authorGabilondo, Iosu
dc.contributor.authorViguera, Mikel
dc.contributor.authorPapa, Gregor
dc.date.accessioned2021-10-13T13:16:28Z
dc.date.available2021-10-13T13:16:28Z
dc.date.issued2020
dc.description.abstractCollecting complex information on the status of machinery is the enabler for advanced maintenance activities, and one of the main players in this process is the sensor. This paper describes modern maintenance strategies that lead to Condition-Based Maintenance. This paper discusses the sensors that can be used to support maintenance, as of different categories, spanning from common off-the-shelf sensors, to specialized sensors monitoring very specific characteristics, and to virtual sensors. This paper also presents four different real-world examples of project pilots that make use of the described sensors and draws a comparison between them. In particular, each scenario has unique characteristics requiring different families of sensors, but on the other hand provides similar characteristics on other aspects.pt_PT
dc.description.sponsorshipThis work was partially supported by National Funds through FCT/MEC (Portuguese Foundation for Science and Technology), Slovenian Research Agency (research core funding No. P2-0098), Finnish Funding Agency for Innovation Tekes, and co-financed by ERDF (European Regional Development Fund) under the PT2020 Partnership, within the CISTER Research Unit (PCEC/04234); also by the EU ECSELJU under the H2020 Framework Programme, within project ECSEL/0004/2014, JU grant no. 662189 (MANTIS); also by EU ECSEL JU under the H2020 Framework Programme, JU grant no. 737459 (Productive4.0 project).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1080/00051144.2020.1794192pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/18705
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relationPCEC/04234pt_PT
dc.relationCyber Physical System based Proactive Collaborative Maintenance
dc.relationCyber Physical System based Proactive Collaborative Maintenance
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/00051144.2020.1794192pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectCondition-based maintenancept_PT
dc.subjectPredictive maintenancept_PT
dc.subjectVirtual sensorspt_PT
dc.subjectUse casespt_PT
dc.subjectDemonstratorspt_PT
dc.subjectPilotspt_PT
dc.titleAdvanced sensor-based maintenance in real-world exemplary casespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCyber Physical System based Proactive Collaborative Maintenance
oaire.awardTitleCyber Physical System based Proactive Collaborative Maintenance
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/ECSEL%2F0004%2F2014/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/662189/EU
oaire.citation.titleAutomatikapt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStreamH2020
person.familyNameLino Ferreira
person.givenNameLuis
person.identifier2014958
person.identifier.ciencia-id4715-3F5B-EFAE
person.identifier.orcid0000-0002-5976-8853
person.identifier.scopus-author-id55421891300
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication1db060b0-52ff-4a6b-9eaa-4d8a2030942b
relation.isAuthorOfPublication.latestForDiscovery1db060b0-52ff-4a6b-9eaa-4d8a2030942b
relation.isProjectOfPublicationdd10c795-20cf-4bdc-a2b9-d45ea6a9ca12
relation.isProjectOfPublication8435e6ed-21dc-4690-a4fc-6de25ecf071a
relation.isProjectOfPublication.latestForDiscoverydd10c795-20cf-4bdc-a2b9-d45ea6a9ca12

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ART_CISTER_LFerreira_2020.pdf
Size:
4.26 MB
Format:
Adobe Portable Document Format
Download

Collections

ISEP – CISTER – Artigos