Annual Smart Fleet maintenance Summit (SfM360)
In-Person, On-line & On-Demand Event
SFM360, is the world’s leading end-client driven collaborative platform designed to inform maintenance, operations and supply chain organisations on the real world experiences, financial implications and tangible benefits of investments in digitalization of fleet maintenance to create a digital supply chain, improve life cycle asset management, data management and decision making in maintenance to meet asset management cost targets across multiple rolling stock asset including legacy and new fleets.
Co-located with our Rolling Stock Procurement Summit, 14th March 2023, This year’s Smart Fleet Maintenance Summit brings together the European Rolling Stock Industry to collaborate and share real world findings on their incremental investments in new digital wayside and on-board monitoring technologies to improve reliability, automate rolling stock processes and reduce cost in maintenance activities. Case study presentations will cover the financial implications and tangible benefits of implementing sensors, IoT, intelligent asset management systems, AI, Machine Learning and Digital Twins to collect and analyse data in real time, optimising scheduling, advancing sustainability and improving availability of rolling stock fleets.
Presenting an INTERNATIONAL line-up of Senior European Railway Industry Leaders from leading operators, such as NS, SBB CFF FFS, Transport for London, SNCF, NMBS/SNCB, SJ AB, DSB, DB Regio, South Western Railway, Northern, RENFE, Great Western Railway, MTR, Transpennine Express Ltd, Central Japan Railway Company and many more sharing in-depth case studies and presentations on:
- Investing in methodology and continuous data management, building a roadmap for engineering to ensure you meet asset management cost
- Adopting a circular business model, building digital twins to deliver a digital supply chain, improving resilience and sustainability and make maintenance more data driven
- The application of artificial intelligence within the maintenance world, implementing machine learning tool sets to improve decision making in maintenance