Optimize

Apply a set of goals and constraints to a trained neural network and solve process optimization problems.

Evaluate a trained model against a set of constraints to solve an optimization problem. For example, optimizing an Additive Manufacturing process for target material properties based on data from previous builds.In MI AI+, the process for solving an optimization problem is as follows:
  1. Create a Criteria Set based on a trained model.
  2. Enter constraints for all input variables. Choose between any value (Full range) or greater than or less than a set value.
  3. Enter goals and target values for all output variables. Use Full range for outputs with no specific target.
  4. Send the Criteria Set and model to the engine for evaluation, and track progress with the Job Queue.
  5. View the results returned by the engine in a table, or go to Visualize to plot them.