Ken Pipe, Ken Pipe has a wealth of prognostics experience from aerospace which he has successfully applied to the rail sector. He has been heavily involved in the development of data driven predictive maintenance technology since 1983 in several sectors. In rail, Ken has been technical lead for applying the Humaware p-RCM toolset to ta range of applications from bogie components through to signalling points and escalator station assets.
AGENDA AT A GLANCE
- 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
- 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