See material failures before they form.

Simulated material states are connected to secondary process signatures that production tools can measure. Representation learning captures how those states relate to process signatures in a simulated environment. Domain alignment then adapts that relationship to signals measured on the production line. Quality-aware alignment preserves links relevant to product quality while accounting for differences between simulation and production. Available quality measurements calibrate and test the model for a specific process. Once validated, production inference uses incoming signals to update an estimate of the relevant quality outcome as the process runs. The resulting indicator can flag emerging risk for review.