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Industrial Data Services for Quality Control in Smart Manufacturing - the i4Q Framework

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Industrial Data Services for Quality Control in Smart Manufacturing - the i4Q Framework

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dc.contributor.author Karakostas, Anastasios es_ES
dc.contributor.author Poler, R. es_ES
dc.contributor.author Fraile Gil, Francisco es_ES
dc.contributor.author Vrochidis, Stefanos es_ES
dc.date.accessioned 2022-12-14T11:46:57Z
dc.date.available 2022-12-14T11:46:57Z
dc.date.issued 2021-06-09 es_ES
dc.identifier.isbn 978-1-6654-1980-2 es_ES
dc.identifier.uri http://hdl.handle.net/10251/190666
dc.description.abstract [EN] This paper presents a new innovative framework to support smart manufacturing quality assurance. More specifically, the i4Q framework provides an IoT-based Reliable Industrial Data Services (RIDS), a complete suite consisting of 22 innovative Solutions, able to manage the huge amount of industrial data coming from cheap cost-effective, smart, and small size interconnected factory devices for supporting manufacturing online monitoring and control. The i4Q Framework guarantees data reliability with functions grouped into five basic capabilities around the data cycle: sensing, communication, computing infrastructure, storage, and analysis-optimization. i4Q RIDS includes simulation and optimization tools for manufacturing line continuous process qualification, quality diagnosis, reconfiguration and certification for ensuring high manufacturing efficiency, leading to an integrated approach to zero-defect manufacturing. This paper presents the main principles of the i4Q framework and the relevant industrial case studies on which it will be evaluated. es_ES
dc.description.sponsorship This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 958205 es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.relation.ispartof 2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Product quality es_ES
dc.subject Process quality es_ES
dc.subject Data quality es_ES
dc.subject Data reliability es_ES
dc.subject Blockchain es_ES
dc.subject Virtual sensors es_ES
dc.subject Digital twins es_ES
dc.subject Process simulation es_ES
dc.subject Process optimization es_ES
dc.subject Zero-defect manufacturing es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Industrial Data Services for Quality Control in Smart Manufacturing - the i4Q Framework es_ES
dc.type Comunicación en congreso es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1109/MetroInd4.0IoT51437.2021.9488490 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/958205/EU es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi es_ES
dc.description.bibliographicCitation Karakostas, A.; Poler, R.; Fraile Gil, F.; Vrochidis, S. (2021). Industrial Data Services for Quality Control in Smart Manufacturing - the i4Q Framework. IEEE. 454-457. https://doi.org/10.1109/MetroInd4.0IoT51437.2021.9488490 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename IEEE International Workshop on Metrology for Industry 4.0 & IoT 2021 es_ES
dc.relation.conferencedate Junio 07-09,2021 es_ES
dc.relation.conferenceplace Online es_ES
dc.relation.publisherversion https://doi.org/10.1109/MetroInd4.0IoT51437.2021.9488490 es_ES
dc.description.upvformatpinicio 454 es_ES
dc.description.upvformatpfin 457 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\447966 es_ES


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