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Ontology-based knowledge representation for wire arc additive manufacturing and composite extrusion modeling
Citation Link: https://doi.org/10.15480/882.16467
Publikationstyp
Conference Paper
Date Issued
2025
Sprache
English
TORE-DOI
Citation
32nd International Workshop on Intelligent Computing in Engineering, EG-ICE 2025
Contribution to Conference
Publisher DOI
ISBN of container
978-1-9142-4182-6
Knowledge representation in additive manufacturing (AM) is essential for data management, enabling semantic interoperability and decision-making. Wire arc additive manufacturing (WAAM) and composite extrusion modeling (CEM) are advanced manufacturing methods employed within metal-based additive manufacturing. Although knowledge representation in AM has been widely explored, there is a notable gap in research addressing knowledge representation tailored to WAAM and CEM. Aiming to advance knowledge representation for WAAM and CEM, this paper proposes an ontology-based knowledge representation approach. Two ontologies, the Wire Arc Additive Manufacturing Application Ontology (WAAMAO) and the Composite Extrusion Modeling Application Ontology (CEMAO), are proposed, following a well-known ontology engineering methodology to ensure a rigorous and systematic ontology design process. To validate the proposed approach, a manufacturing information system utilizing both ontologies is presented. The findings highlight the capability of WAAMAO and CEMAO in knowledge representation, enabling efficient data management and supporting semantic interoperability in metal-based AM processes.
DDC Class
670: Manufacturing
658.5: Of Production
Publication version
publishedVersion
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Ahmad-etal-EG-ICE-2025-Ontology-based-knowledge-representation-for-wire-arc-additive.pdf
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1.44 MB
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