Graph machine learning for assembly modeling

  • Assembly modeling refers to the design engineering process of composing assemblies (e.g., machines or machine components) from a common catalog of existing parts. There is a natural correspondence of assemblies to graphs which can be exploited for services based on graph machine learning such as part recommendation, clustering/taxonomy creation, or anomaly detection. However, this domain imposes particular challenges such as the treatment of unknown or new parts, ambiguously extracted edges, incomplete information about the design sequence, interaction with design engineers as users, to name a few. Along with open research questions, we present a novel data set.

Export metadata


Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Author:Carola LenzenORCiDGND, Alexander SchiendorferORCiDGND, Wolfgang ReifORCiDGND
Frontdoor URL
Parent Title (English):LoG 2022: The First Learning on Graphs Conference, 9-12 December 2022, virtual event
Type:Conference Proceeding
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2023/02/02
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht