Process Failure Prediction


Product failures leading to significant energy and material waste and in turn higher costs and environmental impact.


Predict 90% failures before they occur saving over £100k per composite part and reducing energy and material waste.

The How

  1. Understand the autoclave composite curing process
  2. Collect data from the machine and other relevant sources (Scheduling, Control Profiles etc…)
  3. Develop a ML Classifier to predict failures before the process begins
  4. Using a Neural Network, failures are predicted during the curing process and before the point of no return