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AI based geometric similarity search supporting component reuse in engineering design

Krahe, Carmen ORCID iD icon 1; Marinov, Milan; Schmutz, Theresa 1; Hermann, Yannik 1; Bonny, Mike; May, Marvin 1; Lanza, Gisela 1
1 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)


Today, companies are faced with the challenge to develop and produce individualized products in the shortest possible time at very low cost in order to remain attractive under strong competitive pressure. For reasons of efficiency, products are therefore often developed in generations. Proven components are adopted in a new product generation and only some of the components are newly developed to meet new customer requirements. Many companies, therefore, have a large database of 3D CAD product models containing years of engineering experience. Nevertheless, it is often difficult to execute database queries to find which products or components already exist and could be reused or adapted for a new product generation or variant. As a result, many duplicates are created, which are associated with high effort and costs, and the risk of introducing design errors increases.

Therefore, the aim of this paper is to develop an automated approach for geometric similarity search that also takes company-specific features of components into account. Machine learning methods are capable of automatically extracting relevant geometric features by learning a suitable representation of the corresponding 3D object. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000148974
Veröffentlicht am 26.07.2022
DOI: 10.1016/j.procir.2022.05.249
Zitationen: 3
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000148974
Erschienen in 32nd CIRP Design Conference (CIRP Design 2022) - Design in a changing world. Ed.: N. Anwer
Veranstaltung 32nd CIRP Design Conference (2022), Online, 28.03.2022 – 30.03.2022
Verlag Elsevier
Seiten 275–280
Serie Procedia CIRP ; 109
Schlagwörter Artificial Intelligence; Pattern Recognition; Design; Similarity Search; Product Development
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