INTELLIGENT DATA GENERATION FOR THE MACHINING OF 2.5D COMPONENTS

With the ultimate aim at a high level of automation, this paper presents an intelligent approach to generating data from a solid model for machining planning. The solid model used to represent the component contains only generic geometric and topological information of the component design (i.e. without any tagged attributes for feature information). Therefore feature recognition concept and techniques are employed. Because of the high complexity, the work is simplified to 2.5D milled components. Considerations for the analysis and generation of data include machinability assessment, raw stock selection, clamping surfaces and machined features. Component stability is also taken into account.