A major issue in product development is the exchange and sharing of product knowledge among many actors. This knowledge includes many concepts such as design history, component structure, features, parameters, constraints, and more. Heterogeneous tools and multiple designers are frequently involved in collaborative product development, and designers often use their own terms and definitions to represent a product design. Thus, to efficiently share design information among multiple designers, the design intent should be persistently captured and the semantics of the modeling terms should be semantically processed both by design collaborators and intelligent systems. Regarding CAD models, most of the current CAD systems provide feature-based design for the construction of solid models. Features are devised to carry, semantically, product information throughout its life cycle. Consequently, features should be maintained in a CAD model during its migration among different applications. However, existing solutions for exchanging product information are limited to the process of geometrical data, where semantics assigned to product model are completely lost during the translation process. Current standards, such as ISO 10303, known as STEP have attempted to solve this problem, but they define only syntactic data representation so that semantic data integration is not possible. Moreover, STEP does not provide a sound basis to reason with knowledge. Our research investigates the use of Semantic Web technologies, such as ontologies and rule languages; e.g. SWRL, for the exchange of “intelligent” CAD models among different systems, while maintaining the original relations among entities of the model. Thus, we have proposed an ontological approach based on the construction of a common design features ontology, used as an Interlingua for the exchange of product data. This ontology is represented formally with OWL DL. Furthermore, axioms and mapping rules are defined to achieve the semantic integration between the applications ontologies and the common ontology. The integration process relies basically on reasoning capabilities provided by description logics in order to recognize automatically additional mappings among ontologies entities. Furthermore, the mapping process is enhanced with a semantic similarity measure in order to detect similar design features. However, this will enable data analysis, as well as manage and discover implicit relationships among product data based on semantic modeling and reasoning.
Semantic interoperability of knowledge in feature-based CAD models