A Bayesian network based approach for root-cause-analysis in manufacturing process

We describe an Early Warning System (EWS) which enables the root-cause-analysis for initiating quality improvements in the manufacturing shop floor and process-engineering departments, at product OEMs as well as their tiered suppliers. The EWS combines the use of custom-designed domain ontology of manufacturing processes and failure related knowledge, innovative application of domain knowledge in the form of probability constraints and a novel two-step constrained optimization approach to causal network construction. Probabilistic reasoning is the main vehicle for inference from the causal network. This inference engine provides the capability to do a root-cause-analysis in manufacturing scenarios, and is thus a powerful weapon for an automotive EWS. This technique is widely applicable and can be used in various contexts in the broader manufacturing industry as well.