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Managing the migration to predictive maintenance to maximise asset lifecycles and reduce costs in a more dynamic grid environment
14-16 January 2020 | Berlin, Germany

Programme

Conference Day 3 Thursday 16 January 2020 Download
08:00Registration and refreshments
08:45Welcome back from the Chair
09:00Machine Learning as a Predictive Tool – combining central data platforms, legacy data and machine learning algorithms to inform intelligent field operation strategies and minimise excavation damage to existing infrastructure
09:45Cybersecurity – evaluating the cybersecurity risks inherent in predictive maintenance and devising a strategy to ensure effective prevention and monitoring of assets as the number of sensors in the grid increases
10:30Morning refreshments, networking and exhibition
11:00Digital Twin – evaluating the potential of digital twins in enabling advanced predictive maintenance both for individual assets and the grid overall
11:45AI & ML – assessing the potential of AI & ML to process high volumes of grid data and provide advanced insights to support predictive maintenance procedures
12:30Lunch, networking and exhibition
14:00LIDAR & UAV – examining the full potential of LIDAR & UAV technologies to facilitate airborne analysis of hazards to power grid infrastructure and enable advanced maintenance strategies
14:45Blockchain – exploring the potential of next generation data collation methods to enable real-time, multi-party data insights to support predictive maintenance
15:30Afternoon refreshments, networking and exhibition
16:00Tutorial: Augmented Reality – exploring the potential of next generation technologies to provide field forces with real time maintenance guidance on a wide range of assets from a central facility
17:30End of Day Three