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WHO SHOULD ATTEND

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

AGENDA

IMPLEMENTING SMARTER COST REDUCTION STRATEGIES, WORKING MORE EFFICIENTLY & ADOPTING NEW TECHNOLOGY TO OPTIMISE MAINTENANCE COST   

 

08:00 – Coffee and Registration

08:50 - Chair’s Opening Remarks

IMPROVING COST BASE EFFICIENCY & OPTIMISING WHOLE LIFE CYCLE MANAGEMENT 

Saving Money, Optimising Asset Utilization & Managing Realistic Expectations On What New Technology Innovation Can Actually Deliver

KEYNOTE PANEL – ENGINEERING DIRECTOR PERSPECTIVES ON WORKING SMARTER TO DELIVER MORE VALUE   

09.00 – Adopting Technology, Organising Resources More Efficiently & Calibrating The Mix Of Condition Based, Predictive & Classical Maintenance Strategies 

Four high-level engineering director case studies identifying the optimal overall approach to working smarter to allocate resources more efficiently to improve fleet reliability at a reduced cost.

STRATEGIC CASE STUDY 1 Identifying The Key Maintenance Cost Drivers & Efficiently Allocating Resources To Match The Age, Specification & Utilisation Of Individual Fleets (20 minutes) 

Thierry Fort, Rolling Stock Engineering Director, SNCF

STRATEGIC CASE STUDY 2 Structuring The Organization & Adapting The Workforce To Implement Maintenance Strategies More Cost Effectively & Efficiently (20 minutes)

Pat McNamara, Head of Production, Eurostar International Ltd

STRATEGIC CASE STUDY 3 Combining Condition and Prediction Based Maintenance Regime To Deliver Success – Delivering Results On Cost Reduction, Fleet Reliability & Efficiency (20 minutes)

Kyle Lau, Chief of Engineering, Beijing MTR

STRATEGIC CASE STUDY 4 Implementing Lean and Technology-Enabled Maintenance Strategies For New Passenger Rolling Stock Changeover – Learnings From Konkan Railway (20 minutes)
Dr Deepak Tripathi, Chief Mechanical Engineer, Konkan Railway 

 

10:20 - Extended Conference Discussion & Feedback 

An opportunity for delegates to question speakers and feedback to conference on how they have addressed the challenges raised in the opening panel. 

 

HITACHI RAIL PRESENTATION

10:40 – Generating Actionable Information Through Data

  • Update on new developments and application for rail monitoring
  • Aggregating internal and external datasets around a common problem statement
  • Condition monitoring case studies

Darren Willshire, Fleet Director, Hitachi Rail

Justin Southcombe, Commercial Director, Hitachi Rail

 

11:10 Morning Refreshment Break & Networking In The Exhibition Area 

>> “Application Of New Technology To Deliver Net Benefit” Showcase & Interview <<

 

NEW INNOVATIVE CONCEPTS – COMBINING THE APPLICATION OF LEAN TECHNIQUES & PREDICTIVE MEASURES 

11:40 – Successfully Implementing Lean & Cost-Effective Predictive Maintenance Strategies Simultaneously 

  •  Explore the key set-up costs and calculate the ROI of decreased maintenance activity
  • Understand the initial implementation challenges faced and how to overcome these 
  • Reduce the frequency of maintenance tasks leading to reduced downtime
  • Practical examples on using predictive analysis to deliver actual results 

Gerald Schinagl, Manager of Digital Innovation, OBB 

12:00 - Questions & Discussion

 

REAL-LIFE MORE ACCURATE DATA PREDICTION OF MAINTENANCE NEEDS 

12:10 – Application Of Existing Data To Increase The Efficiency Of Your Maintenance Strategy And Reduce The Maintenance Effort

  • Explore the data you have collected and what can be used to spot patterns or trends in asset health status and behaviour
  • How to mix human expertise and artificial intelligence for pattern detection
  • Understand how pattern detection can enable you to prevent in-service failures and adjust maintenance effort

Philippe Laharpe, Manager for Telediagnostics, SNCF

12:30  Questions & Discussion

 

12:40 – Implementation of Predictive Maintenance through Railigent and the Digital Depot

  • High system availability through smart monitoring and predictive maintenance

Johannes Emmelheinz, CEO Customer Services, Siemens Mobility

13:00  Questions & Discussion


13:10 Lunch Break

 

OPTIMISING BOTH NEW & LEGACY FLEETS ROLLING STOCK MAINTENANCE‚Äč

 Adopting New Technology And Improve Cost Base Efficiencies 

 

APPLICATION OF DATA-DRIVEN DECISION MAKING FOR LEGACY FLEETS  

14:10 – Legacy Fleets - Best Practice Application Of Condition Based Maintenance & Making Better Use Of Existing Technology 

  • Implementing cost-effective solutions for older legacy fleets 
  • Managing realistic expectations on what technology can deliver 
  • Moving from regular interval maintenance to condition-based maintenance 
  • Prioritising key components and subsystems for condition-based maintenance 
  • Practical examples of data-driven decision making that reduces maintenance frequency

Paolo Masini, Head of Rolling Stock Technology and System Engineering, Trenitalia

14:30 Questions & Discussion  

Chaired by Simon Jarrett

 

COST-EFFECTIVE SOLUTIONS FOR MAINTAINING NEW ROLLING STOCK

14:40 – Condition-based monitoring and predictive maintenance with the CALIPRI technology

  • Ensuring accurate and reliable measurements with CALIPRI
  • Understanding the benefits of automated data transfers with smart data handling
  • Wheel wear analysis and prediction, looking at profile analysis and profile comparison, wear prediction, trend analysis
  • Optimized wheelset maintenance, tolerance monitoring, automated email notifications

Wolfgang Eder, Sales Manager Railway Applications, Nextsense

15:00 - Question & Answer Session

Chaired by Simon Jarrett

 

Demonstrating How Adopting The Latest Technologies Can Result In A Net Reduction In The Amount Of Money It Costs To Run & Maintain Your Trains

 

APPLICATION OF FUTURE TECHNOLOGIES FOR OPTIMISING CONDITION BASED MAINTENANCE  

15:10 – The Next Wave Of Digitalisation & A.I. Opportunities To Improve The Effectiveness Of Condition Based Maintenance 

  • Easing Operations: Energy efficiency, passenger experience and safety supporting drivers with real-time information.
  • Easing Availability:  Deploying predictive analytics to reduce LCC.
  • Easing Depot Performance and Inspection: From wayside systems to tablets to execute maintenance activity.

Javier De La Cruz, Managing Director, CAF Digital Services

15:30 Questions & Discussion  

Chaired by Simon Jarrett

 

15:40 Afternoon Refreshment Break & Networking In The Exhibition Area 

>> “Application Of New Technology To Deliver Net Benefit” Showcase & Interview <<

 

MANAGING THE INTEGRATION OF CHANGES IN MAINTENANCE STRATEGY

16:10 – Organizing & Upskilling Your Workforce To Undertake Digitally Enabled Maintenance Activities Accurately & Effectively

Philippe Laharpe, Manager for TelediagnosticsSNCF

16:30  Questions & Discussion

 

PANEL – APPLYING THE LATEST TECHNOLOGIES TO IMPROVE RELIABILITY & REDUCE COST

16:40 Adopting The Latest Technology Innovations To Deliver Maintenance Benefits  –Demonstrating Image Recognition, Acoustic Analysis, A.I. & Digitalisation In Action    

Highlighting practical examples on how the latest technology innovations are being applied – or alternatively tested, trialled and evaluated - to deliver net benefits for rolling stock operators. What are the notable shifts in rail maintenance innovation through digitalization?  What are the optimal processes to get the most out of IoT and big data analysis investments?   And crucially, what are the real-world limitations on what technology can deliver considering the challenges of workforce upskilling and rapidly leveraging technology in a real world capacity? 

Evaluate The Potential Of Each Solution To Reduce Cost & Improve Reliability  

Tech Focus 1 Assess The Next Wave Of Digitalisation & A.I. Opportunities To Improve The Effectiveness Of Condition Based Maintenance (15 minutes) 

Staffan Ingvander, Project Manager, MTR Nordic Group

Tech Focus 2 Acoustic Analysis To Improve Condition Monitoring Of Difficult To Visually Inspect Mechanical Components (15 minutes) 

Simon Jarrett, Engineering Assurance Manager, Chiltern Railways

Tech Focus 3 Installing Image Recognition Technologies For Reliable Fault Detection & To Connect Repair Strategy For Quicker Spare Parts Sourcing (15 minutes) 

Sergio Barcena, Director of Operations, Planning and Maintenance, OUIGO Espana

17:25 Extended Questions & Discussion 

Chaired by Simon Jarrett

17:45 Chair’s Closing Remarks & End Of Day One, followed by an Evening Drinks Reception            

            

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