Automatic recognition of machining features from computer aided design part models

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.