Conference Paper Research on Feature Recognition from STEP model for Automatic Process Planning of Multi-tasking Machine

朱, 疆  ,  ZHU, JIANG  ,  加藤, 雅人  ,  kato, masato  ,  吉岡, 勇人  ,  Yoshioka, Hayato  ,  齋藤, 義夫  ,  SAITO, YOSHIO  ,  田中, 智久  ,  TANAKA, TOMOHISA

Multi-tasking machines which are capable of performing both milling and turning operations contribute to highly efficient machining and space conservation. However, prior to machining, a lot of time is consumed in identifying a set of surfaces called “feature” and deciding efficient process sequence. Especially in high-mix low-volume production it is more important to reduce the cycle time. In this research, a feature recognition system for process planning is developed. It is able to automatically recognize manufacturing features for the down streaming process planning from a CAD model in the format of STEP file. In this system, the CAD model given by user is described as Attributed Adjacency Graph (AAG) consisting of nodes and arcs. This simple description of CAD model enables efficient feature recognition. In order to recognize features properly, every feature is defined by topology, geometry and AAG. In the developed system, totally 8 milling features and 9 turning features are predefined. From the experimental results, it is shown that this developed system can recognize features for multi-tasking machine properly and efficiently.

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