Institute of Railway Research/University of Huddersfield
Farouk’s research interest are in vehicle and track dynamics, condition based maintenance (CBM) and predictive maintenance (PdM). He has worked on several large consortium projects on the European Shift2Rail (S2R) Joint Undertaking. Here he has looked at methods and techniques in data driven approaches using machine learning and data analytics; more recently he is the IP3 work package leader on S2R project representing Network Rail to develop On-Track Machine (OTM) planning tool; in this project he is supporting NR develop algorithms and optimise OMT planning through the development of decision support (DST) tools. He is also involved in the development of a commercial vehicle-based track condition monitor system supporting Siemens to reduce the effects of service effecting failure (SAFs) on the GB railway. Additionally, the focus of this event, he has been involved in a S2R project looking at developing Digital Twins of rolling stock bogies to establish a CBM Framework for freight locomotive fleet maintenance and tactical optimisation of scheduling.