Semantic interoperability of knowledge in feature-based CAD models

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. Regarding CAD models, most of the current CAD systems provide feature-based design for the construction of solid models and to carry, semantically, product information throughout its life cycle. Unfortunately, existing solutions and standards, such as STEP, 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. Moreover, STEP does not provide a sound basis to reason with knowledge. The work described in this paper is part of our approach based on the development of OWL ontologies to preserve semantics associated with product data. In this work, we will focus on the semantic integration of these ontologies by defining axioms and rules. 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 to detect similar design features. Similarity measure integrates all aspects of OWL DL language. Thus, similarity functions are defined for each type of entity to involve all the features that make its definition. However, this will enable data analysis, as well as manage and discover implicit relationships among product data based on semantic modeling and reasoning. (C) 2014 Elsevier Ltd. All rights reserved.