APPLICATION OF COMPUTATIONAL GEOMETRY IN OPTIMIZING 2.5D AND 3D NC SURFACE MACHINING

To machine a part from the CAD data, machining information has to be extracted from the design model. In the planning stage, the machining information such as the cutting area, removal volume, estimated machining time, etc., is important for the generation of a ''good'' process plan. This machining information is typically not readily available from the design. This paper discusses a methodology of applying computational geometry techniques to extract machining information of geometric constraints from a given complex surface design to support the process planning activity. The machining process is determined by part surface classification based on surface geometry interrogation. An application of convex hulls is also presented to improve the machining productivity by preprocessing the object geometry for machining. The proposed methodology can be applied in the automation of planning and manufacturing of complex surface parts. Some practical examples and testing results are presented to show the application in solving manufacturing problems.