University of Birmingham experts have recently won funding from the UK Government’s Engineering and Physical Sciences Research Council (EPSRC), to enhance productivity and efficiency across the healthcare and manufacturing sectors.
Part of a multidisciplinary collaboration including Imperial College London, University of Cambridge, UCL, and the Alan Turing Institute, academics from Birmingham’s School of Chemical Engineering will participate in a five-year programme called PREMIERE. PREMIERE stands for PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems.
Birmingham’s Mark Simmons, Professor in Fluid Mechanics and Liam Grover, Professor in Biomaterials Science will lead on the manufacturing and healthcare research. Their aim is to create the next generation of models for multiphase flow systems – systems that deal with flow of gas, liquid, and, potentially, solids flowing simultaneously in pipes, channels, and reactors. The PREMIERE project seeks to better understand the behaviour of these flow patterns, and use machine learning and computer simulations to predict how these patterns can be influenced for the better - whether the flow is in the body or in a chemical plant.
Commenting on the programme, Professor Mark Simmons, Head of the School of Chemical Engineering, said “We are delighted to be a part of this multi-disciplinary collaboration. The funding will support our healthcare and manufacturing research, allowing for advances in these sectors.”
In addition to healthcare and manufacturing, researchers across the collaboration will also look at the energy sector. Participants expect the programme, which will be based on machine learning-powered computer simulations, to improve supply chain design, decision-making, safety management, and help reduce carbon emissions.
Manufacturing plays a major role in the UK and global economy, but unpredictability in demand, availability of raw materials, and variations in consumer preferences can cause uncertainty in the industry. To manage these risks, manufacturers need their processes to be as efficient, sustainable, and robust as possible. Through PREMIERE, machine learning algorithms could be used to predict, and help people plan for, supply chain interruptions.
For example, a raw materials-producing country may be unable to meet demand due to economic or geopolitical upheaval. An artificially intelligent algorithm would constantly keep track of how this might affect supply chains, warn about risk of disruptions, and suggest viable alternatives from which industrialists can choose. The Birmingham team will exploit machine learning algorithms for novel, resilient product design using bespoke manufacturing technologies, including microfluidic systems which can cope with a wide range of feedstocks.
The Birmingham team will work with Imperial and clinicians from University of Birmingham's Surgical Reconstruction and Microbiology Research Centre to collect data on acute compartment syndrome. This is a life-threatening condition often seen in patients from road traffic accidents, and is difficult to diagnose accurately. A wrong diagnosis can lead to amputation or death. Through PREMIERE, smart algorithms that interpret patient data could be used to diagnose patients based on individual symptoms and those of previously diagnosed patients, potentially leading to more accurate diagnoses.
The researchers behind PREMIERE expect their algorithms to be flexible enough to offer a whole range of solutions, as part of the same framework, depending on the needs of their industrial and medical partners: from approximate solutions delivered in real-time, to highly-accurate ones that require use of powerful, high-performance computing.
PREMIERE will be funded by the EPSRC, which is part of UK Research and Innovation. This will support a team of PhD and postdoctoral research associates, as well as research software engineers across the four partner universities working closely with industrial and medical partners