An ontology of eco-design for additive manufacturing with informative sustainability analysis

Design for Additive Manufacturing (DfAM) offers a unique opportunity to consider the sustainability of industrial components fabricated by additive manufacturing in the early stage of product development. This leads to the emergence of a novel cross -subject field known as Eco-Design for AM (EcoDfAM). Sustainability analysis of industrial components is critical in EcoDfAM but demands substantial domain knowledge not yet modeled within existing DfAM knowledge. This paper addresses the gap by developing an EcoDfAM ontology using the Web Ontology Language (OWL). This ontology aims to enable knowledge reuse for sustainability analysis in AM design by structurally organizing life cycle process information of industrial components and then semantically modeling Sustainable Design Knowledge (SDK). SDK captures implicit knowledge from AM, design, and sustainability domains, highlighting the correlation of design and sustainability in EcoDfAM through introducing a novel concept, the Material-Process-Structure-ecoProperty (MPSeP) relationships, to extend knowledge in the AM domain for considering sustainability. A six -step ontology development process was employed to create the EcoDfAM ontology which comprises three important concepts: eco-parameters, eco-property, and performance. The representation of SDK focused on the Laser Powder Bed Fusion (LPBF) process in the developed ontology. Implementation of the ontology is carried out using the Prote<acute accent>ge<acute accent> tool, and reasoning and queries within EcoDfAM are accomplished through the Semantic Web Rule Language (SWRL) and Semantic Query -enhanced Web Rule Language (SQWRL). The proposed EcoDfAM ontology is demonstrated through a case study on a hydraulic manifold to be fabricated by SLM, showcasing its effectiveness in retrieving key inventory data related to carbon emission and cost, eco-parameters used in DfAM, and recommending eco-design recommendations, facilitating the development of an eco-friendly and economical AM solution for the hydraulic manifold. In conclusion, this study contributes a structured knowledge model, serving as a professional, reusable, and upgradable knowledge base for sustainability analysis in AM design, empowering designers to fully leverage AM's potential for sustainable outcomes