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dc.contributor.authorPascual Molero, Alejandro ORCID
dc.contributor.authorOrtega Rodríguez, Naiara
dc.contributor.authorPlaza Pascual, Soraya ORCID
dc.contributor.authorHolgado García, Ibon
dc.contributor.authorArrizubieta Arrate, Jon Iñaki
dc.date.accessioned2020-12-10T12:09:27Z
dc.date.available2020-12-10T12:09:27Z
dc.date.issued2020-11-12
dc.identifier.citationMetals 10(11) : (2020) // Article ID 1508es_ES
dc.identifier.issn2075-4701
dc.identifier.urihttp://hdl.handle.net/10810/48883
dc.description.abstractThe scope of this work is to present a reverse engineering (RE) methodology to achieve accurate polygon models for 3D printing or additive manufacturing (AM) applications, as well as NURBS (Non-Uniform Rational B-Splines) surfaces for advanced machining processes. The accuracy of the 3D models generated by this RE process depends on the data acquisition system, the scanning conditions and the data processing techniques. To carry out this study, workpieces of different material and geometry were selected, using X-ray computed tomography (XRCT) and a Laser Scanner (LS) as data acquisition systems for scanning purposes. Once this is done, this work focuses on the data processing step in order to assess the accuracy of applying different processing techniques. Special attention is given to the XRCT data processing step. For that reason, the models generated from the LS point clouds processing step were utilized as a reference to perform the deviation analysis. Nonetheless, the proposed methodology could be applied for both data inputs: 2D cross-sectional images and point clouds. Finally, the target outputs of this data processing chain were evaluated due to their own reverse engineering applications, highlighting the promising future of the proposed methodology.es_ES
dc.description.sponsorshipThis research was funded by the he Department of Economic Development, Sustainability and Environment of the Basque Government for funding the KK-2020/00094 (INSPECTA) research project and the Spanish Ministry of Science and Innovation for funding the ALASURF project (PID2019-109220RB-I00).es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/MCIU/PID2019-109220RB-I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectreverse engineeringes_ES
dc.subjectX-ray computed tomographyes_ES
dc.subjectlaser scanneres_ES
dc.subjectpolygon model (STL)es_ES
dc.subjectNURBSes_ES
dc.subjectdata processinges_ES
dc.titleA RE Methodology to achieve Accurate Polygon Models and NURBS Surfaces by Applying Different Data Processing Techniqueses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2020-11-26T14:09:39Z
dc.rights.holder2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2075-4701/10/11/1508/htmes_ES
dc.identifier.doi10.3390/met10111508
dc.departamentoesIngeniería mecánica
dc.departamentoeuIngeniaritza mekanikoa


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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).