Abstract
Abstract
This paper presents an innovative method for recognizing manufacturing features from computer aided design (CAD) part models. The proposed method is to integrate the graph-based approach and the volume approach, in order to combine the positive aspects of both strategies. Feature edge sequence, a new graph-based feature recognition approach, is used to recognize and extract surface features from the part design data. The extracted features are then clustered into the machining volumes by the volume-based approach. The main drawback of conventional feature recognition systems is their limitations in handling feature interactions and arbitrary shape features. In the proposed system, the graph-based method is able to recognize interacting features, the volume-based approach can generate alternative interpretations of machining volumes and an artificial intelligence (AI)-based algorithm, established with a neural network, is used to handle the arbitrary features.