Brian is the Head of Product Management, joining Nomad in December 2017, responsible for the global product portfolio including software and applications. Prior to joining Nomad, Brian has over 25 years’ experience in telecommunications, primarily focused on mobile core network infrastructure for voice and data. Starting in a software development role, his career has taken him into product management and technical pre-sales. He has broad international experience having worked for major vendors and within multiple start-up organisations, including several long-term assignments in the UK, USA, France and Germany.
One aim of the intelligent train concept is to provide a single maintainer-friendly view of the train. True digital enablement involves the ability to predict failures, highlight hidden problems and issue real-time alerts when failures happen. By using information in a more structured, controlled and repeatable way to plan corrective maintenance, engineers can move towards a condition-based maintenance regime, helping to maximise equipment life, increase availability, reliability and reduce costs. The key is to identify potential failure warning signs before a failure occurs, as the repair cost is usually typically far lower to handle pro-actively as opposed to after the failure has occurred.
Train systems generate a huge amount of data – a standard EMU generates in excess of 5,000 signals, equivalent to 2GB of data per train per day, and gathering this data is costly – data transmission could cost thousands of Pounds per train per year. We think that about 0.25% of this data is critical from a maintenance perspective, so the secret is smart use of the full data set. This requires the ability to access this data, process it and then have an on-shore back office solution which can visualise and analyse it, develop predictive algorithms and integrate procedures into maintenance management. Data can then be compared to understand how fleets are performing relative to each other and, if presented in a standardised form, allow for direct comparisons across manufacturers. A key part of the savings comes from changes in maintenance practices based on the information being generated from the condition-based maintenance solution.