Hybrid feature recognition method for setup planning from STEP AP-203

For seamless automation, computer-aided design and manufacturing activities have to be linked by computer-aided process planning (CAPP). An important subtask in CAPP is setup planning, in which a setup plan must be generated ideally from a given 3-D model of the component. In this paper, a hybrid approach that effectively uses volume subtraction and face adjacency graph is proposed to recognize manufacturing features from 3-D model data in STEP AP-203 format. The proposed feature recognition is generic in nature and is capable of recognizing intersecting features also with relative ease. The manufacturing features are clustered based on preferential base for machining and a setup sequence is obtained by alternative rating and ranking. Finally, locating and clamping for each setup are determined considering intermediate shapes of the workpiece. This setup planning method reduces the number of alternatives for evaluation and thereby the computational effort.