Automatic recognition of machining features from computer aided design part models

This paper presents an innovative method for recognizing manufacturing feat ures from computer aided design (CAD) part models. The proposed method is t o integrate the graph-based approach and the volume approach, in order to c ombine the positive aspects of both strategies. Feature edge sequence, a ne w graph-based feature recognition approach, is used to recognize and extrac t surface features from the part design data. The extracted features are th en clustered into the machining volumes by the volume-based approach. The m ain drawback of conventional feature recognition systems is their limitatio ns in handling feature interactions and arbitrary shape features. In the pr oposed system, the graph-based method is able to recognize interacting feat ures, the volume-based approach can generate alternative interpretations of machining volumes and an artificial intelligence (AI)-based algorithm, est ablished with a neural network, is used to handle the arbitrary features.