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WHO WILL YOU MEET?

Meet Senior Decision Makers From


  • U.K. Rail Operators
  • European Rail Operators
  • Global Rail Operators

With The Following Job Titles


COOs, VPs, Directors, Managers, Team Leads & Chiefs Of...

  • Rolling Stock
  • Maintenance
  • Engineering
  • Innovation
  • Asset Management
  • State Of Good Repair
  • Equipment Maintenance
  • High Speed Rail
  • Fleet
  • Systems
  • Shops
  • Revenue Equipment

Plus:


  • Train Manufacturers
  • Maintenance Companies
  • CBM Technology Companies
  • OEMs
  • Asset Management
  • Consultancies

Humaware

Humaware are a UK technology development company who are at the forefront of developing and implementing data driven predictive analytics that enable organisations to extract actionable information from their remote condition monitoring data. Our condition indicator approach to defect detection enables our toolsets to be unbound by the structure of one specific industry and have been applied to different asset types across rail, aerospace, marine and energy sectors.  An end to end predictive maintenance capability was demonstrated on London Underground escalators where our tools detected events on average 382 days in advance of maintenance. These detections were timely enough to provide risk based Remaining Useful Lives which were validated. A risk based dynamic scheduling demonstrator was produced to demonstrate that actionable information for scheduling maintenance can be produced autonomously using data driven predicative analytics. (Innovate UK/RSSB). Our most recent projects include monitoring Track Circuit Indicators where we were able to remove the requirement to set and maintain the five fixed alert detection thresholds for each individual track circuit and provide actionable defect diagnosis using a novel user interface.

RSM17 Group Discount

AGENDA AT A GLANCE

Day One

  • Understanding The Real Opportunities And Challenges Of Introducing New Maintenance Technologies Into The Rail Sector
  • Getting The Right Balance Between Condition Based Monitoring And Corrective Maintenance
  • Case Study On Implementation Of Digitalisation Of Maintenance
  • Optimise Services And Reduce Cost With Remote Condition Monitoring
  • Performance And Reliability Optimisation Through Predictive Maintenance
  • Data interpretability
  • Machine Learning And Artificial Intelligence Applications To RSM.
  • Practical Examples Of Robotics Functions In RSM.
  • Evaluate The Pros And Cons Of Retrofitting Vs Procuring New Rolling Stock

Day Two

  • Developing A Workforce Strategy To Maximise Digitalisation Of Maintenance Benefits
  • Ensuring Your IT Infrastructure Is Ready For Your New System
  • Optimising Maintenance Processes To Anticipate Adverse Wweather Conditions
  • How To Optimise Your Maintenance Processes Without Compromising Safety And Performance
  • Understanding How To Co-Ordinate Rolling Stock Downtime To Meet Maintenance Needs
  • Management Strategies For Cost Effectively Replacing Obsolete Spare Parts, Components And Materials
  • Improving Your Maintenance Organisation's Environmental Sustainability Credentials Whilst Lowering Running Costs
  • What RAMP Compliance, European Rail Traffic Management System (ERTMS) And Other Regulations Really Mean To Maintenance Of Rolling Stock

Plus:

  • Train Manufacturers
  • Maintenance Companies
  • CBM Technology Companies
  • OEMs
  • Asset Management
  • Consultancies

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