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dc.contributor.authorCorcho, Juan Camilo Parejaen_US
dc.contributor.authorAcosta, Oscar Mauricio Betancuren_US
dc.contributor.authorRuiz, Oscar E.en_US
dc.contributor.authorCadavid, Carlosen_US
dc.contributor.editorCasas, Dan and Jarabo, Adriánen_US
dc.date.accessioned2019-06-25T16:20:48Z
dc.date.available2019-06-25T16:20:48Z
dc.date.issued2019
dc.identifier.isbn978-3-03868-093-2
dc.identifier.urihttps://doi.org/10.2312/ceig.20191205
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/ceig20191205
dc.description.abstractIn the context of Computer-Aided Design and Manufacturing, the problem of feature recognition plays a key role in the integration of systems. Until now, compromises have been reached by only using FACE-based geometric information of prismatic CAD models to prune the search domain. This manuscripts presents a feature recognition method which more aggressively prunes the search space with reconfigurable geometric tests. This reconfigurable approach allows to enforce arbitrary confluent tests which are topologic and geometric, with enlarged domain. The test sequence is itself a graph (i.e. not a linear or total-order sequence). Unlike the existing methods which are FACE-based, the present one permits combinations of topologies whose dimensions are 2, 1 or 0. This system has been implemented in an industrial environment. The industrial incarnation allows industry-based customization and is faster when compared to topology-based feature recognition. Future work is required in improving robustness of search conditions and improving the graphic input interface.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectApplied computing
dc.subjectComputer
dc.subjectaided design
dc.subjectComputer
dc.subjectaided manufacturing
dc.titleUser-reconfigurable CAD Feature Recognition in 1- and 2-topologies with Reduction of Search Space via Geometry Filtersen_US
dc.description.seriesinformationSpanish Computer Graphics Conference (CEIG)
dc.description.sectionheadersShort Papers
dc.identifier.doi10.2312/ceig.20191205
dc.identifier.pages69-72


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  • CEIG19
    ISBN 978-3-03868-093-2

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