Systems, methods, and media for manufacturing processes

A manufacturing system, comprising:

• a plurality of stations, each station configured to perform at least one step in a multi-step manufacturing process for a component;
• and
• a control module configured to dynamically adjust processing parameters of a step of the multi-step manufacturing process to achieve a desired final quality metric for the component, the control module configured to perform operations, comprising:
• receiving image data of tooling of a first station of the plurality of stations;
• identifying a set of keypoints from the image data, the set of keypoints corresponding to position information of the tooling during processing at the first station;
• determining, by a machine learning model, a final quality metric for the component, based on the set of keypoints, wherein the final quality metric is a metric associated with the component that cannot be measured until processing of the component in the multi-step manufacturing process is complete;
• determining that the final quality metric is not within a threshold tolerance from a nominal final quality metric;
• based on determining that the final quality metric is not within the threshold tolerance from the nominal final quality metric, inferring positional information corresponding to the component at the first station;
• based on determining that the final quality metric is not within a threshold tolerance from the nominal final quality metric, generating an updated instruction set to be performed by a downstream station;
• predicting, by the machine learning model, a new final quality metric for the component based on the updated instruction set, wherein the new final quality metric is a metric associated with the component that cannot be measured until processing of the component in the multi-step manufacturing process is complete;
• and
• based on the new final quality metric, providing the updated instruction set to the downstream station.