Collaborative Augmented Digital Twin: A Novel Open-Source Augmented Reality Solution for Training and Maintenance Processes in the Shipyard of the Future

UDC.coleccionInvestigaciónes_ES
UDC.departamentoEnxeñaría de Computadoreses_ES
UDC.grupoInvGrupo de Tecnoloxía Electrónica e Comunicacións (GTEC)es_ES
UDC.issue1es_ES
UDC.journalTitleEngineering Proceedingses_ES
UDC.startPage10es_ES
UDC.volume7es_ES
dc.contributor.authorVidal-Balea, Aida
dc.contributor.authorBlanco, Óscar
dc.contributor.authorFraga-Lamas, Paula
dc.contributor.authorVilar-Montesinos, Miguel A.
dc.contributor.authorFernández-Caramés, Tiago M.
dc.date.accessioned2022-01-18T19:16:29Z
dc.date.available2022-01-18T19:16:29Z
dc.date.issued2021
dc.descriptionPresented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.es_ES
dc.description.abstract[Abstract] Large companies use a lot of resources on workshop operator training and industrial machinery maintenance since the lack of this practice or its poor implementation increases the cost and risks of operating and handling sensitive and/or hazardous machinery. Industrial Augmented Reality (IAR), a major technology in the Industry 4.0 paradigm that may enhance worker performance, minimize hazards and improve manufacturing processes, could be beneficial in this situation. This paper presents an IAR solution that allows for visualizing and interacting with the digital twin of a critical system. Specifically, the augmented digital twin of an industrial cooler was developed. The proposed IAR system provides a dynamic way to perform operator training with a full-size model of the actual equipment and to provide step-by-step guidance so that maintenance processes can be performed more safely and efficiently. The proposed system also allows several users to use devices at the same time, creating a new type of collaborative interaction by viewing the model in the same place and state. Performance tests with many simultaneous users have been conducted, with response latency being measured as the number of connected users grows. Furthermore, the suggested IAR system has been thoroughly tested in a real-world industrial environment.es_ES
dc.description.sponsorshipThis work was supported by the Plant Information and Augmented Reality research line of the Navantia-UDC Joint Research Unit (IN853B-2018/02). The authors would like to thank CITIC for its support. CITIC, a research center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidades from Xunta de Galicia”, with 80% of funds coming from ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% from “Secretaría Xeral de Universidades” (Grant ED431G 2019/01).es_ES
dc.description.sponsorshipXunta de Galicia; IN853B-2018/02es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.identifier.citationVidal-Balea, A.; Blanco-Novoa, O.; Fraga-Lamas, P.; Vilar-Montesinos, M.; Fernández-Caramés, T.M. Collaborative Augmented Digital Twin: A Novel Open-Source Augmented Reality Solution for Training and Maintenance Processes in the Shipyard of the Future. Eng. Proc. 2021, 7, 10. https://doi.org/10.3390/engproc2021007010es_ES
dc.identifier.doi10.3390/engproc2021007010
dc.identifier.urihttp://hdl.handle.net/2183/29423
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.urihttps://doi.org/10.3390/engproc2021007010es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectIndustrial augmented realityes_ES
dc.subjectCollaborative augmented realityes_ES
dc.subjectMixed realityes_ES
dc.subjectIndustry 4.0es_ES
dc.subjectMaintenancees_ES
dc.subjectTraininges_ES
dc.titleCollaborative Augmented Digital Twin: A Novel Open-Source Augmented Reality Solution for Training and Maintenance Processes in the Shipyard of the Futurees_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication44f0a9cb-1f7a-4b62-8e02-4129b587f12f
relation.isAuthorOfPublicationcaa923d2-cf88-405e-9025-759d06cf3799
relation.isAuthorOfPublication79dbfabd-7261-41ff-9667-2f774d5f341e
relation.isAuthorOfPublication.latestForDiscovery44f0a9cb-1f7a-4b62-8e02-4129b587f12f

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