EPSRC Supported EngD: Closing the Loop - Enabling More Sustainable Operations with Machine Learning Based Advanced Process Control

The use of Artificial Intelligence/Machine Learning methods in process optimisation and control is one of the key strategies the formulation industry has adopted to reduce resource and energy wastage. However, the current state of the art relies on human intervention. To increase responsiveness to dynamically varying inputs and get the most value from these next-generation process models, it is necessary to move to direct process control (‘closing the loop’).

Despite the significant published work in the field of machine learning for formulations unit operations, there is very little published on direct control. This is a challenging step, where new approaches to human/machine interfaces, control system integrity and process safety will need to be developed.

This project will seek to build a framework using hands-on implementation of direct control in a safe test-bed environment at Johnson Matthey’s research facilities, as part of Johnson Matthey Technology Centre’s Process Measurement and Control team. This will give the student the opportunity to develop skills in software and hardware development, process control, and the freedom to push the boundaries and explore failure modes as well as successful operation. The successful candidate will work alongside other CDT students and experienced professionals at Johnson Matthey, catalysing the net zero transition.

Supervisors: Dr Estefania Lopez-Quiroga and Professor Mark Simmons.

Funding notes: Tax free bursary of £25,737 per annum plus fees paid. To be eligible for EPSRC funding candidates must have at least a 2(1) in an Engineering or Scientific discipline or a 2(2) plus MSc. To apply please email your cv to cdt-formulation@contacts.bham.ac.uk. Open to UK nationals only due to funding restrictions.