UL's MACSI win KTI's Consultancy Research Impact Award

UL's MACSI (Mathematics Applications Consortium for Science and Industry) and Rural Aughinish Alumina were the winners of the Knowledge Transfer Ireland Consultancy Impact Award, the award was presented at a ceremony in Dubin on Thursday 30th March.

The Consultancy Award recognises consultancy provided through an Irish publicly-funded research performing organisation (RPO), by its researchers, to a business or public sector organisation. The consultancyactivity will have resulted in a demonstrable economic and/or public benefit. 

Rusal Aughinish Alumina (AAL) is Europe’s largest alumina refinery. The company wanted to improve aspects of its production process and sought the expertise of researchers at MACSI (a network of mathematical modellers and scientific computational analysts based in Ireland) in the University of Limerick. The team developed bespoke systems for AAL that ensure the quality of the extracted products is not affected in the event of a loss of power at their plants. This project has resulted in a staggering 200pc increase in the accuracy of prediction of product quality, enhancing the overall efficiency and decision-making of the plant.

AAL has a long-standing relationship with the Mathematics Applications Consortium for Science and Industry (MACSI) at UL with whom they have successfully collaborated for over 10 years on a number of research projects. AAL sought to improve predictions of product quality five days in advance to address the fact that system events meant the plant could lose power directly impacting product quality. AAL engaged the MACSI team on a piece of consultancy tasking MACSI with improving the prediction process. To do this MACSI developed mathematical and statistical models for process understanding that combine first principles simulation and data driven stochastic dynamics. The project resulted in a 200% increase in the accuracy of prediction of product quality, enhancing the overall efficiency of the plant and supporting AAL decision making. The two algorithms developed under the consultancy engagement have been implemented by the company and are in daily use. This project has had a major impact on the MACSI team at UL whose skills have been enriched by applying mathematical techniques to real world industrial problems. It enabled two-way knowledge transfer between the parties through staff exchanges and joint workshops. AAL, MACSI and UL continue to work together with this project having contributed to the development of a new SFI-funded research agreement in 2016 and a new project between AAL, UL and Imperial
College London.