Process variability simulator for manufacturing processes

A method of optimizing process parameters in a multi-step manufacturing process, comprising:

• characterizing, by a computing system, a process variation for each of a plurality of stations as a range of variation of station parameters over time, each station configured to perform at least one step in the multi-step manufacturing process for a product, each station having an inherent variability due to one or more of external conditions or control algorithms associated with the station;
• receiving, by the computing system, one or more process parameters to be optimized during the multi-step manufacturing process;
• initiating, by the computing system, a process prediction model in accordance with the one or more process parameters and the characterized process variation;
• simulating, by the computing system using the process prediction model, the multi-step manufacturing process using a plurality of sets of different setpoints, wherein the process prediction model simulates based on the range of variation of each of the plurality of stations;
• identifying, by the computing system, a first set of setpoints from the plurality of sets of different setpoints that optimized the one or more process parameters;
• and
• applying, by a station controller communicating with the plurality of stations, the first set of setpoints to the plurality of stations.

A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause a computing system to perform operations comprising:

• characterizing a process variation for each of a plurality of stations as a range of variation of station parameters over time, each station configured to perform at least one step in a multi-step manufacturing process for a product, each station having an inherent variability due to one or more of external conditions or control algorithms associated with the station;
• receiving one or more process parameters to be optimized during the multi-step manufacturing process;
• initiating a process prediction model in accordance with the one or more process parameters and the characterized process variation;
• simulating, using the process prediction model, the multi-step manufacturing process using a plurality of sets of different setpoints, wherein the process prediction model simulates based on the range of variation of each of the plurality of stations;
• identifying a first set of setpoints from the plurality of sets of different setpoints that optimized the one or more process parameters;
• and
• commanding a station controller communicating with the plurality of stations to apply the first set of setpoints to the plurality of stations.