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.

DeepMachining 是一个基于深度学习的人工智能系统，用于在线预测车床加工操作中的加工误差。通过预训练深度学习模型来学习加工状态的显著特征，并通过微调预训练模型来适应具体的加工任务，我们证明了 DeepMachining 在涉及不同工件和切削工具的多项任务中具有较高的预测准确性。据我们所知，这项工作是使用预训练的深度学习模型来预测车床加工误差的最早的工厂实验之一。