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Quo vadis industry 4.0? Position, trends, and challenges

2020Journal article Open access
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dc.contributor.authorLeitão, Paulo
dc.contributor.authorPires, Flávia
dc.contributor.authorKarnouskos, Stamatis
dc.contributor.authorColombo, Armando W.
dc.date.accessioned2023-03-16T09:43:47Z
dc.date.available2023-03-16T09:43:47Z
dc.date.issued2020
dc.description.abstractIndustry 4.0 vision and its mandated digital transformation are radically reshaping the way business is carried out and the way overall industrial processes and collaborations are operating. In this work, the objective is to analyze the current level of adoption of Industry 4.0, via the footprint available in industrial and academic research works. The analysis performed reveals insights on how Industry 4.0 has impacted and is still influencing research and innovation in industrial systems, services, and business approaches. It also reveals pertinent trends on key enabling features, technologies and challenges associated with this 4th industrial revolution, mainly focusing on the pathways for wider industrial adoption of Industry 4.0-compliant technologies and solutions.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationLeitão, Paulo; Pires, Flavia; Karnouskos, Stamatis; Colombo, Armando Walter (2020). Quo vadis industry 4.0? Position, trends, and challenges. IEEE Open Journal of the Industrial Electronics Society. ISSN 2644-1284.1, p. 298-310pt_PT
dc.identifier.doi10.1109/OJIES.2020.3031660pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/27767
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAn Intelligent Decision Support Approach for Industrial Digital Twin
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectIndustry 4.0pt_PT
dc.subjectCyber-physical systemspt_PT
dc.subjectDigital transformationpt_PT
dc.subjectIndustrial digitalizationpt_PT
dc.titleQuo vadis industry 4.0? Position, trends, and challengespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAn Intelligent Decision Support Approach for Industrial Digital Twin
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F143243%2F2019/PT
oaire.citation.endPage310pt_PT
oaire.citation.startPage298pt_PT
oaire.citation.titleIEEE Open Journal of the Industrial Electronics Societypt_PT
oaire.citation.volume1pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPOR_NORTE
person.familyNameLeitão
person.familyNamePires
person.givenNamePaulo
person.givenNameFlávia
person.identifierA-8390-2011
person.identifierhttps://scholar.google.pt/citations?user=an9quSsAAAAJ&hl=pt-PT
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.ciencia-idA119-72AB-6255
person.identifier.orcid0000-0002-2151-7944
person.identifier.orcid0000-0001-7899-3020
person.identifier.scopus-author-id35584388900
person.identifier.scopus-author-id57200412919
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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