Paper ID: 2403.16451

DeepMachining: Online Prediction of Machining Errors of Lathe Machines

Xiang-Li Lu, Hwai-Jung Hsu, Che-Wei Chou, H. T. Kung, Chen-Hsin Lee, Sheng-Mao Cheng

We describe DeepMachining, a deep learning-based AI system for online prediction of machining errors of lathe machine operations. We have built and evaluated DeepMachining based on manufacturing data from factories. Specifically, we first pretrain a deep learning model for a given lathe machine's operations to learn the salient features of machining states. Then, we fine-tune the pretrained model to adapt to specific machining tasks. We demonstrate that DeepMachining achieves high prediction accuracy for multiple tasks that involve different workpieces and cutting tools. To the best of our knowledge, this work is one of the first factory experiments using pre-trained deep-learning models to predict machining errors of lathe machines.

Submitted: Mar 25, 2024