Real Time Characteristic Prediction for Unconsolidated Composite Materials

A characteristic prediction system comprising:

• a computer system;
• and
• prediction manager located in the computer system, wherein the prediction manager is configured to:
• receive sensor data in real time from a sensor system for a composite material manufacturing system during manufacturing of an unconsolidated composite material;
• generate initial predictions for a number of characteristics of the unconsolidated composite material in a completed form in real time during manufacturing of the unconsolidated composite material in the composite material manufacturing system using a number of physics-based models and a number of machine learning models trained to generate the initial predictions using the sensor data;
• and
• determine a final prediction in real time for the number of characteristics based on the initial predictions.

A method for predicting a number of characteristics of an unconsolidated composite material, the method comprising:

• generating initial predictions for a number of characteristics of the unconsolidated composite material in a completed form in real time during manufacturing of the unconsolidated composite material in the composite material manufacturing system using sensor data received in real time from a sensor system for a composite material manufacturing system during manufacturing of the unconsolidated composite material, a number of physics-based models, and a number of machine learning models, wherein the number of machine learning models is trained to generate a number of the initial predictions using the sensor data;
• determining uncertainties for the initial predictions for the number of characteristics of the unconsolidated composite material in the completed form from the number of physics-based models and the number of machine learning models in real time during manufacturing of the unconsolidated composite material;
• associating weights with the initial predictions for the number of characteristics using the uncertainties;
• and
• determining a final prediction for the number of characteristics based on the initial predictions and the weights associated with the initial predictions.

A method for predicting a number of characteristics of an unconsolidated composite material, the method comprising:

• receiving sensor data in real time from a composite material manufacturing system during manufacturing of an unconsolidated composite material;
• generating initial predictions for a number of characteristics of the unconsolidated composite material in a completed form in real time during manufacturing of the unconsolidated composite material in the composite material manufacturing system using a number of physics-based models and a number of machine learning models trained using data;
• and
• determining a final prediction in real time for the number of characteristics based on the initial predictions.