DeepMachining：车床加工误差的在线预测
DeepMachining: Online Prediction of Machining Errors of Lathe Machines
AI总结：
本文提出基于深度学习的车床加工误差在线预测系统DeepMachining，通过预训练加微调的流程适配不同加工任务，在多类工件、刀具场景下取得高预测精度，是相关方向首批工厂落地实验之一。
摘要：
本文介绍了DeepMachining，这是一款基于深度学习的AI系统，用于在线预测车床作业的加工误差。我们基于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作业预训练深度学习模型，以学习加工状态的显著特征，随后对预训练模型进行微调，使其适配特定加工任务。我们证明，DeepMachining在涉及不同工件和切削刀具的多项任务中均实现了较高的预测准确率。据我们所知，本研究是首批采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。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
