The goal of this project is to be able to predict the changes which occur in the grain structure of aluminium and nickel superalloy components when they undergo a forging process.
Forging is a method of deforming a metal at high temperatures into a component shape.
At present, no reliable model exists for determining the final microstructure. Thus proper optimisation of the forging process normally demands a combination of experience and expensive trials. Part of my research is to investigate and develop suitable neural network architectures implementing Bayesian methods which are appropriate for this metallurgical application. Such an approach will not only provide a predictive capability for the process but will also provide a rigorous assessment of the reliability of these predictions. This is both a very interesting and important project, because it lies at the boundary between practical industrial problems and academic information analysis theory.