Before
Product failures leading to significant energy and material waste and in turn higher costs and environmental impact.
After
Predict 90% failures before they occur saving over £100k per composite part and reducing energy and material waste.
The How
- Understand the autoclave composite curing process
- Collect data from the machine and other relevant sources (Scheduling, Control Profiles etc…)
- Develop a ML Classifier to predict failures before the process begins
- Using a Neural Network, failures are predicted during the curing process and before the point of no return
