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FDC Based on Neural Network with Harmonic Sensor to Prevent Error of Robot

机译:基于谐波传感器的神经网络的FDC防止机器人误差

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In order to further improve the productivity of manufacturing equipment, it is indispensable to monitor the conditions of all the manufacturing equipment and not just the processing chambers. In this paper, we present a robust machine learning based degradation diagnosis technology with harmonic sensor. The example of wafer transfer robots in the ion implanter and the LP-CVD and the coater/developer show that wear degradation of machine components can be detected from the level of degradation output and it is possible to prevent errors of the wafer transfer robots because of maintenance based on increases in the level of degradation.
机译:为了进一步提高制造设备的生产率,可以监控所有制造设备的条件,而不仅仅是加工腔室是必不可少的。在本文中,我们展示了一种基于谐波传感器的鲁棒机学习的降解诊断技术。离子注入机和LP-CVD和涂布机/显影剂中的晶片传送机器人的例子表明,可以从降解输出水平检测机器组件的磨损劣化,并且可以防止由于晶片传输机器人的误差基于劣化水平的增加,维护。

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