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

Abstract

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.