PARTNERS 2018

Siemens

CO-SPONSORS

Fugro PlowmanCraven ESIM Plasser Sperry MERMEC

NETWORK BREAK SPONSOR

SKF

Close Networking Opportunities

Meet Senior Decision Makers From:


European And Global Rail Track Operators


With The Following Job Titles...


Directors, Heads and Managers of:

  • Track
  • Track Maintenance
  • Track Division
  • Infrastructures
  • Engineering
  • Track System
  • Project
  • Asset Management
  • Automation Engineer
  • Data/IT
  • Diagnostics and Maintenance Machines
  • Heavy Maintenance
  • Light Maintenance
  • Tamping
  • Safety Managers
  • Head of Quality       
  • Maintenance Performance & Reliability
  • Programme Improvement, Integration & Delivery
  • Reliability Improvement

       


Agenda Day One

Day One: Wednesday 26 June 2019

Case Studies & Discussions Focusing On Data Utilisation & Predictive Maintenance To: Evaluate Practical Applications To Drive Efficiency & Reduce Costs

8.00  Coffee And Registration

9.00  Chair's Welcome And Introduction

Luca Carotti, Hd of Engineering Department, MERMEC Group

EUROPEAN TRACK OPERATORS PERSPECTIVE: OPTIMISING INFRASTRUCTURE MAINTENANCE 

9.10 Intelligent Rail Infrastructure Maintenance: Today And Tomorrow

Bardo will deliver an "helicopter view" of the wider EU digitalisation context in which rail infrastructure managers perform rail maintenance. Highlight  of the main challenges that are associated with the deployment of the digital technologies in maintenance, such as data management, GDPR, safety liabilities, IP and cybersecurity before concluding with some final remarks about the future perspective in this domain.

Bardo Schettini Gherardini, Senior Analyst and Manager of the Technical Team,   European Rail Infrastructure Managers (EIM)

9.40  Questions And Discussion

DATA UTILISATION SESSION 1: GLOBAL OPERATOR CASE STUDY - GENERATING OBJECTIVE DATA FOR TRACK ANALYSIS 

9.50 The Usage Of Vision System Technology To Make Automatic Patrolling And Periodical Inspection A Reality

The difficulty to keep workforce is expected to emerge in the 2050s in Japan, as the population between the age of 15 and 65 will decrease by 30%. As one of the tactics of the future vision, JR-West intends to make "automatic inspection" a reality. 

  • Improving the European standard algorithm of Vision System technology
  • The right balance between "new-technology" and "past-technics"

Hirotaka Yokouchi, Manager of Track Division, Track and Structures Department of Shinkansen (High-Speed Rail), West Japan Railway Company

10.20  Questions And Discussion

10.30  Morning Refreshments & Networking In The Exhibition Area

DATA UTILISATION SESSION 2 -  OPERATOR CASE STUDY - DIAGNOSING TRACK DEFECTS  

11.00 Optimising Diagnostic Data To Monitor Track Conditions.

Exploring the increased potential of track monitoring technology that enables to save money and have a reliable track structure.

  • Which data is import to use?
  • How to better detect track defects?
  • Technology to report and alert faults to the user
  • Visual Inspection and track geometry

Marco Gallini, Head of Diagnostics and Maintenance Machines Department, Italian Railway Infrastructure Manager (RFI S.p.A.)

11.30  Questions And Discussion

STRATEGIC DATA UTILISATION SESSION 1 - DATA STREAM MANAGEMENT

11.40 Utilise Data Effectively And Stream The Whole System: RILA -Generating The Geodetical Backbone With Continuous Dynamic Data Positioning

Predicting track condition and trends using geodetically-accurate positioned data streams - including engineering data to correct track alignments - to achieve optimum assets reliability and minimise maintenance costs.

  • Using Track Recording Vehicle, (TRV) 
  • Automated Track Measuring System (ATMS)
  • Combining different systems for predictive analysis
  • Resulting engineering data for maximum life of assets

Nick van den Hurk, Principal Consultant Rail Transport, Fugro

12.00  Questions And Discussion

DATA OWNERSHIP - CLOUD STORAGE

12.10 Examine Who Owns The Data In The Cloud & How To Take Functional Data From Different Sources 

The myriad of data collected is an important asset; this session will shed light in the regulatory and commercial issue surrounding data ownership and responsibilities. 

  • How is data stored?
  • Who owns the data?
  • Who is responsible of safe keep of your data?
  • What happen if you want to change providers, will you lose your data?

Joël Casutt, Teamleader Technology and Development,  SBB

12.30 Questions & Discussion

12.40  Lunch In The Networking Exhibition Area

PARTNER CASE STUDY

13.40  Manage Your Assets Smarter - Intelligent Remote Track Condition Monitoring To Ensure 100% Availability

Russell Clarke, General Manager ,Siemens Mobile Communications

Dr.-Ing.Thomas Hempel, Project Manager Technology and Infrastructure, Siemens Mobility GmbH

14.00  Questions And Discussion

NEW TECHNOLOGIES FOR DATA MANAGEMENT - DEEP LEARNING & DATA ANALYTICS TECHNOLOGY

14.10 New Technology Applications For Deep Maintenance Data Utilisation: What's On The Horizon For Rail?

In the last two years an Innosuisse Project in collaboration with CSEM fast-tracked the development of deep learning algorithms for processing images acquired of the rails and their surroundings. Images are collected by  diagnostic vehicles up to 160 km/h and analysed using ultra-modern algorithms to identify and classify defects. As more and more data is stored, the self-learning system uses this knowledge to progressively improve its performance and improves safety and availability of the railway infrastructure.

  • The business case for AI integration
  • What systems are available, and what is the difference between them?
  • Cost benefit analysis
  • What is the time of development?

Joël Casutt, Teamleader Technology and Development,  SBB

Matthias Höchemer, Expert Machine Learning & Vision, Swiss Center for Electronics and Microtechnology (CSEM)

14.40 Questions & Discussion

PREDICTIVE MAINTENANCE SESSION 1 - SHIFTING FROM TRADITIONAL MAINTENANCE TO A PREDICTIVE MODEL

14.50 Explore How To Transform From Regular Maintenance To Predictive Maintenance: Improving Work Practices In the Field

Understanding the right methods and processes for implementing new equipment for main track predictive maintenance and how to correctly implement process changes in an organisation to successfully transition from Generic Time Based to Predictive Based Maintenance.

  • How easy is it to implement?
  • Work orders priorities or watch list?
  • How to prioritise work
  • Reporting back the defect root cause
  • How much will it cost?
  • How long does it take to implement?

Hugues Gigleux, Data Science Team Manager, SNCF Réseau

15.20 Questions & Discussion

15.30 Afternoon Refreshments & Networking In The Exhibition Area

Sponsored by SKF Group

Short introduction By Daniel de Andrade, Technical Lead Manager, SKF Group

PREDICTIVE MAINTENANCE SESSION 2: OPERATOR CASE STUDY - REDUCE COSTS THROUGH PREDICTIVE MAINTENANCE

16.00 How To Manage Predictive Maintenance To Reduce Number Of Failures, Amount Of Unplanned Maintenance & Required Level of Reserve Asset Capacity

Detailed real life case study on how a track operator has reduced maintenance cost and failures by successfully applying predictive maintenance best practice.

  • How easy was it to implement?
  • Encountered challenges and related solutions
  • What data are they using and why?
  • Cost benefit analysis

Ian Dean, Principal Engineer Track, Network Rail

Andrew Nwichi-Holdsworth, Network Data Manager, Network Rai

16.30 Questions & Discussion

PREDICTIVE MAINTENANCE SESSION 3 - MAINTAINING A FULLY OPERATIONAL NETWORK

16.40 Combine Optimal Preventative Maintenance With Train Scheduling: Continuous Network Monitoring With Unmanned Systems Ensures Safety And Optimises Maintenance Schedules

The Unmanned Diagnostic System for track inspection is the only maintenance system capable to guarantee the continuous monitoring of the network and therefore its fully operativity and total safety. The increase in network capacity that results in the shortening of the time windows available to perform ordinary monitoring and maintenance activities make it essential to have a constantly updated digital representation of the infrastructure together with the state-of-the-art tools for predictive technology. Such kind of advanced solution empower railway companies to optimise their budget for maintenance and prevent technological obsolescence.

  • Unmanned Diagnostic System to acquire track parameters
  • Smart Framework to support infrastructure maintenance decision chain
  • Automatic definition of working plans
  • Preventive and final analysis of the quality of maintenance intervention
  • Reduce and optimise maintenance costs

Riccardo Ruggiero, Head of Software Development Department, ESIM Group

17.10 Questions & Discussion

17.20 Chair's Closing Remarks

Luca Carotti, Hd of Engineering Department, MERMEC Group

17.30 - 18.30 Networking Drinks Reception In The Exhibition Area

Group

Key Themes

Agenda At A Glance

European Track Operators Perspective: Optimising Infrastructure Maintenance
The Usage Of Vision System Technology To Make Automatic Patrolling And Periodical Inspection A Reality
Optimizing Diagnostic Data To Monitor Track Conditions.
Utilize Data Effectively And Stream The Whole System: RILA -Generating The Geodetical Backbone With Continuous Dynamic Data Positioning
Examine Who Owns The Data In The Cloud & How To Take Functional Data From Different Sources
Case Study - Manage Your Assets Smarter - Intelligent Remote Track Condition Monitoring To Ensure 100% Availability
New Technology Applications For Deep Maintenance Data Utilisation: What's On The Horizon For Rail
Explore How To Transform From Regular Maintenance To Predictive Maintenance: Improving Work Practices In the Field
How To Manage Predictive Maintenance To Reduce Number Of Failures, Amount Of Unplanned Maintenance & Required Level of Reserve Asset Capacity
Combine Optimal Preventative Maintenance With Train Scheduling: Diagnose When To Do The Maintenance
Introducing Technology Into Track Maintenance To Improve Your Asset Management
Leverage Asset Management To Maximise Maintenance Delivery & Reliability Assess, Which Type Of Asset Management Is Used To Deal With The Data.
How To Get Full Coverage Of The Rail Condition & Remove Defects
An artificial intelligence system to find rail flaws - Introducing Elmer®
How To Optimise Your Grinding Activities To Improve Long Term Maintenance Strategies Whilst Saving In Cost
Maximise The Benefit Of The Tamping Machine Intervention
Checking Permanent Way Using "One" Integrated Solution

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