Optimizing manufacturing processes using one or more machine learning models

This invention describes a system that uses machine learning to find the best settings for a manufacturing process. It works by repeatedly trying different settings, feeding them into a trained machine learning model (which could be a neural network) to predict an outcome, and then using that prediction to refine the search for even better settings. The goal is to identify a recommended set of values that optimizes a specific characteristic of the product or process.