Predictive process control for a manufacturing process

A system comprising:

• one or more processors;
• and
• a non-transitory memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving a first set of control values from a first processing station, at a deep learning controller, wherein the first set of control values are generated at the first processing station deployed in a manufacturing process and wherein the first set of control values are attributes of the first processing station of a plurality of stations in the manufacturing process;
• predicting, by the deep learning controller, an expected value for an intermediate value at a downstream processing station or a final output of an article of manufacture, based on the first set of control values;
• determining, by the deep learning controller, that the expected value for the intermediate value or the final output for the article of manufacture is not in-specification;
• based on the determining, generating, by the deep learning controller, one or more control inputs, wherein the one or more control inputs are configured to cause the intermediate value or the final output for the article of manufacture to be in-specification;
• after the generating, causing direct transfer of the article of manufacture from the first processing station to the downstream processing station for a further step in the manufacturing process in accordance with the one or more control inputs;
• receiving a second set of control values, at the deep learning controller, wherein the second set of control values are generated at the downstream processing station deployed in the manufacturing process, wherein the second set of control values are attributes of the downstream processing station;
• predicting, by the deep learning controller, a second expected value for a second intermediate value at a second downstream station or an updated final output of the article of manufacture, based on the first set of control values and the second set of control values;
• determining, by the deep learning controller, that the second expected value for the article of manufacture is not in-specification;
• and
• based on the determining, generating, by the deep learning controller, a second set of control inputs, wherein the second set of control inputs are configured to cause the second intermediate value or the updated final output for the article of manufacture to be in-specification.

A non-transitory computer-readable storage medium comprising instructions stored therein, which when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving a first set of control values from a first processing station, at a deep learning controller, wherein the first set of control values are generated at the first processing station deployed in a manufacturing process and wherein the first set of control values are attributes of the first processing station of a plurality of processing stations in the manufacturing process;
• predicting, by the deep learning controller, an expected value for an intermediate value at a downstream processing station or a final output of an article of manufacture, based on the first set of control values;
• determining, by the deep learning controller, that the expected value for the article of manufacture is not in-specification;
• based on the determining, generating, by the deep learning controller, one or more control inputs, wherein the one or more control inputs are configured to cause the intermediate value or the final output for the article of manufacture to be in-specification;
• after the generating, causing direct transfer of the article of manufacture from the first processing station to the downstream processing station for a further step in the manufacturing process in accordance with the one or more control inputs;
• receiving a second set of control values, at the deep learning controller, wherein the second set of control values are generated at the downstream processing station deployed in the manufacturing process, wherein the second set of control values are attributes of the downstream processing station;
• predicting, by the deep learning controller, a second expected value for a second intermediate value at a second downstream station or an updated final output of the article of manufacture, based on the first set of control values and the second set of control values;
• determining, by the deep learning controller, that the second expected value for the article of manufacture is not in-specification;
• and
• based on the determining, generating, by the deep learning controller, a second set of control inputs, wherein the second set of control inputs are configured to cause the second intermediate value or the updated final output for the article of manufacture to be in-specification.