Accurate Prediction of CNC Machining Time for Milling Operations Using Neural Networks

被引：0

作者：

Chen, Xiao-Xing ^{[1
]}

Lee, Wei-chen ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Mech Engn, Taipei, Taiwan

来源：

2024 IEEE 7TH INTERNATIONAL CONFERENCE ON INDUSTRIAL CYBER-PHYSICAL SYSTEMS, ICPS 2024 | 2024年

关键词：

Machining Time; Milling; Neural Network;

D O I：

10.1109/ICPS59941.2024.10640035

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The prediction of computer numerical control (CNC) machining time critically impacts productivity. Computer-aided manufacturing (CAM) software typically has machining time prediction capabilities, allowing users to know the machining time for parts during toolpath planning. However, CAM software does not consider the kinematics of the CNC machines and the control principle of the CNC controllers. Hence, the predicted machining time is often much shorter than the actual one. To address this problem, we developed two neural network-based machining time prediction models for milling operations using MATLAB and TensorFlow. The results show that using the models proposed in this research could achieve prediction errors within 2%, while the CAM software had about 12% error.

引用

页数：2

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