Ahmad, MuhammadMuhammadAhmadPeralta Abadia, JoseJosePeralta AbadiaChmelnizkij, AlexanderAlexanderChmelnizkijReimann, JanJanReimannHildebrand, JörgJörgHildebrandBergmann, Jean PierreJean PierreBergmannSmarsly, KayKaySmarsly2026-01-142026-01-14202532nd International Workshop on Intelligent Computing in Engineering, EG-ICE 2025https://hdl.handle.net/11420/60814Knowledge 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.enhttps://creativecommons.org/licenses/by-sa/4.0/Technology::670: ManufacturingTechnology::658: General Managament::658.5: Of ProductionConference Paperhttps://doi.org/10.15480/882.1646710.17868/strath.0009322010.15480/882.16467Conference Paper