Virtual Conference on Maintenance Planning
Implementing Efficiency Programs To Optimise Maintenance Regimes, Improving Reliability & Reducing Cost In Rail Operations
The Rolling Stock Maintenance Summit is designed to help Heads of Fleet Engineering, Rolling Stock Maintenance, Planning & Supply Chain Managers Implement Digital Transformation to Increase Efficiencies in their Maintenance Regimes, Optimize the Introduction of Innovations including Predictive Maintenance for Fleet Management, Smart Rail Fleet Maintenance Summit, Improve the Use of Data and Information to Support Decision Making and Increase Maintenance Standards to Deliver better Value from Maintenance Activities across multiple Rolling Stock assets, fleet maintenance management events.
Increase
Organisational Competency & Optimise Supplier Relationships
Learn
To Apply New Technologies & Improve Safety Standards
Improve
Qualifying Data &
Real Time Decision Making
Deliver
Value Throughout
The Whole Fleet Maintenance Process
Confirmed Speakers
Sponsors & Partners
Learning Highlights at this Virtual Fleet Maintenance Conference
1.
Improving the Circular Economy in Rolling Stock Maintenance, Implementing Sustainable Solutions to Reduce Rolling Stock Life Cycle Cost through virtual fleet management conferences.
3.
Benchmarking Successful Applications of Business and Engineering Process Change in Maintenance Regimes and Depots to Extend Maintenance Intervals and Increase Availability of Fleet
5.
Data Management: Accessing Raw Data, Improving Quality of Data, Linking Various Data Sources to Have a Better Understanding of The Real State of an Asset
2.
Smart Maintenance Strategies: Implementing Technology that Fundamentally Works Well in a Rail Operating Environment and Embedding that into Your Organisation
4.
Implementing Strategies to Extend the Life of Components and Materials to Keep Maintenance Cost Low and Increase Availability of Rolling Stock through predictive maintenance for fleet management.
6.
Practical Real-World Execution of Prescriptive Maintenance on High Value Assets: Overcoming the Obstacles and Pain Points to Fully Realize the Predictive Maintenance Approach
Who will attend
Roles
Heads of Fleet Engineering
Directors of Fleet Production
Rolling Stock Maintenance Directors
Rolling Stock Technical Managers
Fleet Planning Managers
Directors of Maintenance Procurement
Sourcing Managers Parts & Materials
Heavy Works Manager (Overhaul)
Depot Managers
Chief Data Scientist
Heads of Maintenance Modernisation
Directors Training & Continuous Improvement
Rolling Stock & Technologies Engineers
SAP EAM Rolling Stock Asset Managers
Companies
Train Operating Companies
Infrastructure Owners
Original Equipment Manufacturers (OEMs)
Train Operating Companies (TOCs)
3rd Party Sub-Systems Equipment Manufacturers
Maintenance organisations
Data Management Software Providers
Business Process Improvement Consulting Companies
HR Training Companies
Cyber Security Services
Manufacturers of materials and consumables
Engineering Companies
Industry Perspectives
"We have implemented technology over the years which hasn't realised its full potential. The technology is not built around the way in which we organise ourselves as a business or the way in which we generally operate. So, do you change the organisation to match the technology that's being provided? Or do you want the technology that aligns with the way in which you operate as a business? How do you get something that's fully embedded fundamentally working well for you? I think that's quite a difficult piece.”
Head of Asset Condition,
London Regional Metro Operator
“The biggest challenge for the future is to deliver a preventive maintenance strategy in rolling stock operations. That's only possible with pattern recognition, big data and analytics that come from the train. If we're able acquire data over a longer period of time we will be able to optimise our maintenance plan significantly to save costs. It's very difficult to do this without data and you need to be very brave to take decisions, for example to skip some scheduled replacement of an element without enough data.”
Program Manager New Rolling Stock, National Passenger Operator, Belgium
“People have been talking about predictive maintenance for years. It seems that there are very few successful cases that have been showcased in the industry. I think it would be great to discuss what we have done so far in this area and what are the pain points today, where and how the industry has been able to overcome those pain points to be successful in the predictive maintenance approach.”
Chief RS Asset Development Manager, National Passenger Operator,
Hong Kong
“What would be ideal is to have any real-world scenario involving mid-term data (one year or something along those lines). For example, monitoring of wheel profile across a subway line. I would also like to hear a real-use case: not only around getting data, but also the process and history of that activity.”
Rolling Stock Engineer on-board electronics & Communication systems, Rapid Passenger Transit Operator, Madrid
“We need to ask the question: why do we do maintenance? Are we over maintaining? I believe a lot of the time we do a lot of maintenance that makes little difference. I think root cause analysis is key. Failure mode analysis is not well practiced by many operators and would allow to see which are your high-risk components, to reduce back-end cost including parts and materials.”
Head Of Innovative Track Measurement Systems, German Rail Infrastructure Owner
“Time-based and cycle-based are well known ways to do maintenance. But today we have technologies that help us learn more about the real-time condition of a system and its components, so we should take advantage of this and try to initiate a paradigm shift into a proactive management of maintenance. How do achieve that paradigm shift? We started with introducing RCM in the Rolling Stock domain, and then moved over to other infrastructure assets, real estate assets, to switches for electricity or elevators. ”
Head of Competence Centre Predictive Maintenance, Swiss Passenger Operator
Metis Previous Sponsors & Partners
Co-Sponsor, RSP360 2021