Application of Hidden Markov Model to Fault Diagnostics of Glass De-chuck System

Abstract

De-chuck operation which attaches object to glues and detaches object from glues has been used in production line to convey materials in vacuum state. The de-chuck operation for glasses or wafers in production line sometimes causes damages on product in detaching it from glues. Since most of failures in de-chuck operation results from abnormal states of glues such as aged states or strong adhesive states, diagnostics of abnormal glues and a timely replacement of glues are the issues of the de-chuck system. In this study, a testbed simulated de-chuck system is devised and a hidden Markov model (HMM) is applied for diagnostics of the problematic glues in de-chuck system of a testbed. As a result, it was measured quantitatively to the rate of accuracy detecting the area of abnormal glues including aged stateglue and strong adhesive state-glue, and the maximum detection accuracy rate was approximately 82%.