Semantic approach to the automatic recognition of machining features

Machining features contain considerable implicit semantic information on shape and machining processes and are dependent on a specific application domain. It is necessary to research and develop an open, shared, and scalable semantic approach to the automatic recognition of machining features. In this paper, the concepts of machining faces and machining features are analyzed, and a novel semantic approach to the automatic recognition of machining features is proposed. The semantic approach provides an ontology-based concept model for representing the machining faces and machining features. The implicit semantics of machining faces and machining features are defined by a set of explicit Semantics Web Rule Language (SWRL) rules. All of the geometric surfaces to be machined are annotated as a set of instances of the face concept and a set of semantic relationships between them, which constitute the fact base for semantic reasoning. Furthermore, an approach to automatic feature recognition based on semantic query and reasoning is proposed. A case study demonstrates that the presented approach can effectively recognize and interpret interacting features and has good openness and scalability.