SIAM Prize Win for Mathematics PhD Students
Several of our students have won a prize in SIAM’s ‘Math Matters’ contest.
Candidates were invited to submit new ideas for the Math Matters, Apply It! series, which demonstrates the role of Mathematics in our everyday lives. The competition was sponsored by the Society for Industrial and Applied Mathematics (SIAM).
The problem of detecting and reducing redundancy in alarm networks arose during a Knowledge Transfer Partnership with Sabisu, a Manchester-based software company who market a decision support platform for the oil and gas industry. Alarm systems are vital for the safe operation of almost all large-scale industrial and technical installations, such as oil refineries or power stations.
The approach taken to optimize these alarm systems is based on graph theory and modern linear algebra techniques, and the results have been presented at an international IEEE conference and published in peer-reviewed proceedings.
As a showcase application, industrial alarm data from a SABIC UK petrochemicals plant was analyzed. By the removal of redundant alarms the average load per plant operator was reduced by 12%, freeing valuable time for the operators to monitor safety-critical alarms.
Reference: T. D. Butters, S. Güttel, and J. L. Shapiro. "Detecting and Reducing Redundancy in Alarm Networks", Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), pp. 1224--1229, 2015. Eprint: http://eprints.ma.man.ac.uk/2302/