Graph based automatic process planning system for multi-tasking machine
TL;DR: In this article, an automatic process planning system for multi-tasking machines was developed, which is capable of recognizing manufacturing features and deciding efficient process plan from CAD model automatically, and the CAD model is described as Attributed Adjacency Graph (AAG), and each feature is defined by AAG and its geometrical properties.
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Abstract: Multi-tasking machine is capable of performing both milling and turning operations, it contributes to highly efficient machining and space conservation. However, prior to machining a lot of lead time is consumed in deciding efficient process plan, and generating machining tool path. Although the current CAM systems are highly integrated, the efficiency of the generated tool path is highly relied on the experience of the CAM programmer. In this research, an automatic process planning system for multi-tasking machine was developed. It is capable of recognizing manufacturing features and deciding efficient process plan from CAD model automatically. In this developed system, the CAD model is described as Attributed Adjacency Graph (AAG), and each feature is defined by AAG and its geometrical properties. Totally 8 milling features and 9 turning features can be recognized. The optimal machining plan is calculated based on machining cost evaluation. In addition, in this research a new method based on subfeature combination is proposed in order to recognize intersecting features. Furthermore, in this research the connection relationship of each feature is classified, and machining priority is assigned to adjacent features. It prevents the time consuming evaluation for checking all possible machining sequences. Finally, according to the experiment results, it is confirmed this developed system is capable of obtaining optimal machining plan properly and rapidly.
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