Causal relational artificial intelligence and risk framework for manufacturing applications

A computer-implemented method for manufacturing process control, the computer-implemented method comprising:

• identifying, by one or more computer processors, an intervention;
• collecting, by the one or more computer processors, process dependency data;
• creating, by the one or more computer processors, an intervention model;
• combining, by the one or more computer processors, the process dependency data and the intervention model to create a combined process dependency graph;
• training, by the one or more computer processors, a causal relational artificial intelligence (CRAI) model with the combined process dependency graph using a Graph Neural Network;
• determining, by the one or more computer processors, whether a causal relationship exists between the intervention and an outcome based on the CRAI model;
• and
• responsive to determining that the causal relationship exists between the intervention and the outcome, determining, by the one or more computer processors, an Intervention Efficacy Estimate for manufacturing process control based on the combined process dependency graph and the CRAI model.