Modern manufacturing involves highly controlled and automated processes meticulously designed to deliver products to specific needs within strict specifications and in a cost-efficient and sustainable way. Sensors capture continuous data streams about the state of the process, e.g., equipment and the product, to ensure performance in variable and often harsh conditions — however, the ability to analyse this data in real-time offers unique advantages currently out of reach. Learning to calibrate its operation from sensor data, monitor its health status and make accurate forecasts on product outcomes and maintenance requirements are process attributes of future autonomous factories.
The ultimate ambition of the LITECS research programme is to reduce the environmental impact of aviation and industrial gas turbine engines by developing and deploying new measurement technologies to enhance the understanding and modelling of combustion and emissions generation processes and the role of alternative fuels.
A team of researchers based in the School of Engineering have developed electronic skin that could pave the way for soft, flexible robotic devices to assist with surgical procedures or aid people’s mobility.
Delin Hu, a first-year PhD student in the School’s Agile Tomography Group at the Institute for Digital Communications (IDCOM) was recently awarded the 2019/20 Postgraduate and Early Career Researcher Exchanges (PECRE) Award by the Scottish Research Partnership in Engineering (SRPe).