Graph based automatic process planning system for multi-tasking machine

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. IntroductionMulti-tasking machines have the capability to perform a variety of machining processes, such as turning, milling, drilling, et al., in a single setup. By using multi-tasking machine, it significantly reduces the setup time, and improves the machining accuracy and quality, because there is no need to move the workpiece across multiple machines. However, due to the complexity of multi-tasking machine, a lot of time is necessary for processing planning before actual machining. Usually, after a 3D model is designed in CAD (Computer Aided Design) system, CAM (Computer Aided Manufacturing) system is used to generate the NC (Numerical Control) data for machining. Although the current CAM systems are highly integrated, how to determine the machining feature, cutting tool, cutting condition and machining sequence is still a labor intensive task (Oba et al., 2010). For each single product, a long lead time is consumed to generate the cutting tool path, and the efficiency of the tool path is highly relied on the CAM programmer's experience. It leads to low productivity in high-mix and low-volume production. Therefore, a CAPP (Computer Aided Process Planning) system, which can automatically extract the manufacturing features from the CAD model and plan the machining process, has long been expected.Feature recognition and process planning are two of the most important components in CAPP system. Feature recognition is a process of reinterpreting a solid model as sets of manufacturing features, and process planning is a process to determine the optimal machin...

Geometric feature extraction in manufacturing based on a knowledge graph

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