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.

翻译：本文描述了DeepMachining，一个基于深度学习的AI系统，用于在线预测车床操作中的加工误差。我们利用工厂的制造数据构建并评估了DeepMachining。具体而言，我们首先针对给定车床的操作预训练一个深度学习模型，以学习加工状态的关键特征。随后，我们对预训练模型进行微调，使其适应特定的加工任务。我们证明，DeepMachining在涉及不同工件和切削刀具的多个任务中均能实现高预测精度。据我们所知，本工作是首批使用预训练深度学习模型预测车床加工误差的工厂实验之一。