CEO Galaxy Semiconductor, California, United States
In a world of parts shortages and constrained supply, unplanned manufacturing downtime is extremely costly. An advanced statistical method for the evaluation of time series sensor data is proposed for the purpose of predicting equipment failures in Chemical Vapor Deposition systems.
Through the simultaneous evaluation of all available sensor data, the algorithm develops an expected model of the total process' behavior. Deviation from expected behavior may be interpreted as pointing to elevated risk of equipment failure. Examples from recent Industrial Experiments in Wafer CVD processes are shared to demonstrate the efficacy of the method.
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