Reconfigurable 3D CAD Feature Recognition Supporting Confluent n-Dimensional Topologies and Geometric Filters for Prismatic and Curved Models

Juan Pareja-Corcho, Oscar Betancur-Acosta, Jorge Posada, Antonio Tammaro, Oscar Ruiz-Salguero and Carlos Cadavid
Additional contact information
Juan Pareja-Corcho: Laboratory of CAD CAM CAE, Universidad EAFIT, Cra 49 no 7-sur-50, 050022 Medellín, Colombia
Oscar Betancur-Acosta: Integration and Engineering Construction Services S.A. de C.V., Av. Eugenio Garza Sada Sur 427, Alta Vista, 64840 Monterrey, Mexico
Jorge Posada: Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastian, Spain
Antonio Tammaro: Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastian, Spain
Oscar Ruiz-Salguero: Laboratory of CAD CAM CAE, Universidad EAFIT, Cra 49 no 7-sur-50, 050022 Medellín, Colombia
Carlos Cadavid: Mathematics and Applications Group, Department of Mathematical Sciences, Universidad EAFIT, Cra 49 no 7-sur-50, 050022 Medellín, Colombia

Mathematics, 2020, vol. 8, issue 8, 1-22

Abstract: Feature Recognition (FR) in Computer-aided Design (CAD) models is central for Design and Manufacturing. FR is a problem whose computational burden is intractable (NP-hard), given that its underlying task is the detection of graph isomorphism. Until now, compromises have been reached by only using FACE-based geometric information of prismatic CAD models to prune the search domain. Responding to such shortcomings, this manuscript presents an interactive FR method that more aggressively prunes the search space with reconfigurable geometric tests. Unlike previous approaches, our reconfigurable FR addresses curved EDGEs and FACEs. This reconfigurable approach allows enforcing arbitrary confluent topologic and geometric filters, thus handling an expanded scope. The test sequence is itself a graph (i.e., not a linear or total-order sequence). Unlike the existing methods that are FACE-based, the present one permits combinations of topologies whose dimensions are two (SHELL or FACE), one (LOOP or EDGE), or 0 (VERTEX). This system has been implemented in an industrial environment, using icon graphs for the interactive rule configuration. The industrial instancing allows industry based customization and itis faster when compared to topology-based feature recognition. Future work is required in improving the robustness of search conditions, treating the problem of interacting or nested features, and improving the graphic input interface.

Keywords: Computer-aided Design; Computer-aided Manufacturing; feature recognition; 3D CAD (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/8/1356/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/8/1356/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:8:p:1356-:d:398469

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().