Abstract: A computer-implemented method for recommending a recipe to produce a product in a manufacturing process is disclosed. The computer-implemented method includes steps of: obtaining experimental data from a machine; generating a physics-based-simulation model based on the experimental data obtained from the machine; generating synthetic data for a first plurality of recipes using the physics-based-simulation model; determining an optimized physical range from physical ranges of each parameter by analyzing the experimental data and the synthetic data using a trained AI model; generating a second plurality of recipes when the optimized physical range of each parameter creating the second plurality of recipes is valid; validating the second plurality of recipes to extract an optimized recipe using the physics-based-simulation model; and recommending the optimized recipe for producing the product in the machine.

Abstract: A computer-implemented method for recommending a recipe to produce a product in a manufacturing process is disclosed. The computer-implemented method includes steps of: obtaining experimental data from a machine; generating a physics-based-simulation model based on the experimental data obtained from the machine; generating synthetic data for a first plurality of recipes using the physics-based-simulation model; determining an optimized physical range from physical ranges of each parameter by analyzing the experimental data and the synthetic data using a trained AI model; generating a second plurality of recipes when the optimized physical range of each parameter creating the second plurality of recipes is valid; validating the second plurality of recipes to extract an optimized recipe using the physics-based-simulation model; and recommending the optimized recipe for producing the product in the machine.