Predictive wafer scheduling for multi-chamber semiconductor equipment

Abstract

A method includes identifying, by at least one processing device from a set of wafers, an idle wafer that is idle for a duration that exceeds a predefined threshold value, wherein each wafer of the set of wafers is associated with a respective start time of a set of start times, and initiating, by the at least one processing device, a computer simulation forecasting processing of the set of wafers using a wafer modification chamber and a wafer movement chamber based on a modified set of start times, wherein the computer simulation uses a machine learning model trained to perform a first manufacturing task using the wafer modification chamber and to perform a second manufacturing task using the wafer movement chamber, and wherein the modified set of start times is obtained by modifying at least one start time of the set of start times.

Dependencies are inferred from the claim text.