Experts at the University of Huddersfield are playing a central role in a £680,000 project designed to transform the maintenance of rail vehicles – and they will test their new techniques on the hard-working trains operated by London Underground.
The University is home to the Institute of Railway Research (IRR), where Dr Adam Bevan and Dr Xiaocheng Ge are heading a contribution to an EU-funded Shift2Rail research programme titled ‘Smart Maintenance and the Rail Traveller Experience’ (SMaRTE).
The project focuses the use of information to enhance decision making and has two main themes – how to make rolling stock maintenance more effective, and the human factors that persuade passengers to choose rail travel. The University of Leeds takes charge of the latter element, while Huddersfield’s Institute of Railway Research handles the maintenance and systems engineering dimension.
SMaRTE is a two-year project that receives €769,958 under the EU’s Horizon 2020 programme. It has partners in countries that include Portugal, Belgium, Italy and Sweden.
The conventional approach to rolling stock maintenance is to carry out scheduled (interval-based) maintenance, which includes visual inspection to check the condition of components. But new technologies are increasingly becoming available and adopted which allow maintainers/operators to continuously monitor the condition of systems and components. This technology can provide data to predict the onset of problems, leading to early intervention and more effective rolling stock maintenance.
Gains from this “smart maintenance” include cost savings and vehicle availability, due to the fact that rail vehicles spend less time out of service. This effectively means that the capacity of the rail service can be increased. Also, continuous monitoring can lead to improvements in passenger satisfaction.
The Institute’s researchers have begun their contribution to SMaRTE by reviewing existing maintenance strategies and condition monitoring techniques. They will develop new condition-based maintenance (CBM) techniques and produce a prototype system that will be applied to a range of vehicle systems and components using real data from specific train fleets operated by London Underground, who are also a partner in SMaRTE and a close collaborator of the IRR. The outputs from this study will be to identify the benefits of applying the CBM techniques compared to the current interval-based maintenance strategy and support the implementation of the CBM-model by other train operators and maintainers.
Original article © University of Huddersfield.
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