Intuitive toolpath planning in computer-aided manufacturing systems using artificial intelligence in a virtual reality environment

作     者：Lionel Damtew Philipp Ganser Tommy Venek Thomas Bergs 

作者机构：Fraunhofer-Institute for Production Technology IPT Steinbachstr. 17 52074 Aachen Germany Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University Campus-Boulevard 30 52074 Aachen Germany 

出 版 物：《Procedia CIRP》 

年 卷 期：2024年第126卷

页      面：354-359页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

主　　题：toolpath planning virtual reality artificial intelligence machine learning computer-aided manufacturing milling 5-axis 

摘      要：CAM systems are widely used in many key industries and are essential for many machining processes such as 5-axis milling. For toolpath planning, state-of-the-art CAM systems require the user to enter many abstract parameters, making these systems difficult to use. This paper presents a more intuitive approach to toolpath planning. The approach uses convolutional neural networks to interpret user gestures in a virtual reality environment and predicts the values of the aforementioned parameters. The results show that many of these parameters can be extracted from user gestures with high accuracy, which can be used to greatly simplify toolpath planning.