论文信息 - Decision Tree Induction of 3-D Manufacturing Features

Decision Tree Induction of 3-D Manufacturing Features

Computer-aided design (CAD) systems describe engineering parts in terms of surfaces, edges, and vertices. However, computer-aided manufacturing (CAM) systems typically represent parts in terms of higher-level features such as slots, holes, pockets, and chamfers. The successful development of an automated manufacturing system relies on the integration of CAD and CAM. Machine learning may help to bridge the gap between these two technologies. We present preliminary results of using a structural decision tree algorithm, STRUCT, to induce manufacturing features from CAD solid models.

Sudhakar Yerramareddy | Larry Watanabe

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