MACHINE LEARNING WITH FAST FEATURE GENERATION FOR SELECTIVE LASER MELTING PRINT PARAMETER OPTIMIZATION

A method includes identifying machine process parameters for an additive manufacturing process to produce a part, providing a real-world sensor to sense a characteristic associated with a real-world version of the additive manufacturing process, receiving sensor readings from the real-world sensor while the machine is performing the real-world version of the additive manufacturing process, generating, with a computer-based processor, physics-based features associated with the additive manufacturing process, and training a machine-learning software model based at least in part on the machine process parameters, the sensor readings, and the physics-based features to predict a behavior of the real-world sensor.