Generative CAPP through projective feature recognition

A feature is a local shape of a product directly related to the manufacturing process. In the computer aided process planning, information on manufacturing is essential. To get the manufacturing related information from CAD data, features should be recognized. In this paper, we thoroughly investigate the composite features, which consist of interacting simple features. The simple features in the composite feature usually have precedence relations in terms of processing sequence. The composite features are directly recognized from CAD data by our proposed projective feature recognition algorithm. Once features are recognized, they are used as input for the process planning. In the process planning, the number of set-up orientations is minimized while process sequence for the features are generated. We propose an algorithm for process planning based on the topological sorting and breadth-first search of graphs.