Join us to find out how machine learning methods are being applied to solve key problems in the design, characterization, and processing of metal alloys and other advanced materials, with a case study from an additive manufacturing (AM) project involving Intellegens, Boeing, and the AMRC.
What you will learn:
- Typical data analysis challenges for advanced materials (alloys, composites, ceramics), and AM - what constrains machine learning methods?
- How you can use Alchemite deep learning to gap-fill data and build models, enabling more effective characterization of materials
- How deep learning has been successfully used to design experiments and in computational design of alloys
- How you can monitor and optimise process parameters to ensure quality
- How these approaches are being applied in an aerospace AM project
Gareth Conduit (CTO at Intellegens)
Ian Brookes (Technical Fellow at AMRC North West)