Equipment parameter management at a manufacturing system using machine learning

Abstract

A method includes receiving first data associated with an equipment parameter. The first data is indicative of an equipment setting of a process tool of a plurality of process tools at a first manufacturing system. The method further includes providing the first data as input to a trained machine learning model. The trained machine learning model is trained using historical data pertaining to equipment parameters of the plurality of process tools at the first manufacturing system. The method further includes obtaining, as output of the trained machine learning model, a predicted value of a metric corresponding to the equipment parameter. The method further includes comparing the predicted value of the metric with the first data, and performing a corrective action based on the comparing.

CPC Classifications