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Manufacturing industry tends toward high-mix low-volume production in recent years. Therefore, in the field of machining, the ratio of preparation in the lead-time becomes higher because the preparation takes a great deal of time and labor to decide suitable machining method, allocate target parts, select cutting tools and generate tool paths. As a result, it is strongly required to develop a computer aided process planning (CAPP) system to shorten the preparation time and to generate NC program. Feature recognition has been considered as a key technology to develop a CAPP system, and a lot of researches have been tackling the technology for a long time. In authors’ previous study, novel machining features for multi-tasking machine tools have been proposed. The machining features can correspond to several alternative machining methods. However, complex target shapes of practical mechanical parts have not been considered. In order to solve this problem, special shapes such as chamfer part and freeform surface are firstly approximated and machining features are recognized by simplifying machining primitives such as complicated groove or taper shape. The machining primitives are finally restored to original complex shapes for CAM system in this study. From the results of conducted case study, it is recognized that the proposed feature recognition method has a potential to deal with complex target shapes of practical mechanical parts.

Proposal of a recognition method of machining features in computer aided process planning system for complex parts machining