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dc.contributor.authorAzkarate, Igor
dc.contributor.authorAguirre, Aitor
dc.contributor.authorUranga Andrés, Josu
dc.contributor.authorEciolaza, Luka
dc.date.accessioned2021-06-03T10:59:33Z
dc.date.available2021-06-03T10:59:33Z
dc.date.issued2020
dc.identifier.isbn978-1-7281-8956-7en
dc.identifier.issn1946-0759en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=162592en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5307
dc.description.abstractIn an automated industrial environment, a large volume of data and signals is available, both from sensors and actuators in machinery and from the interaction with operators and users. Operation diagnosis can have multiple applications from a learning point of view (e.g. staff training) or in terms of process assessment. This work proposes a methodology for implementing an Intelligent System by means of any interactive system connected through OPC UA standard. A digital twin of the process supports configuration and validation, prior to commissioning. Activity is interpreted and diagnosed according to the context in which it occurs. Step order in sequence, step duration and sequence duration are analyzed in a use case based on a PLC-controlled robotic cell in which it is operated both in automatic and manual mode for adjusting a linear table’s positioning.es
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectArtificial Intelligence algorithmsen
dc.subjectcontext awarenessen
dc.subjectdigital twinen
dc.subjectemulationen
dc.subjectFault diagnosisen
dc.subjectmanufacturing automationes
dc.subjectActivity recognitionen
dc.titleADAPT: an Automatic Diagnosis of Activity and Processes in auTomation environmentsen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceIEEE International Conference on Emerging Technologies and Factory Automation (ETFA)en
local.contributor.groupRobótica y automatizaciónes
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.1109/ETFA46521.2020.9211996en
local.source.detailsViena. 8-11 de Septiembre. Pp. 945-951, 2020en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen


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Registro sencillo