PARTNERS

NOMAD DIGITAL nomad

CO-SPONSORS

NEM nexala Danburykline Rail Services OSIsoft Alstom Siemens Railnova

NETWORKING BREAK SPONSORS

Inspecta Cyent Mechan

Agenda

DATA & ASSET OPTIMISED ROLLING STOCK MAINTENANCE SUMMIT: DAY 1, 7TH DECEMBER 2016

Predictive Maintenance & Advanced Data Analytics: Evaluate Practical Applications To Drive Maintenance Efficiency & Reduce Costs

7:30 Registration & Networking

8:30 LBCG Welcome & Chairman's Opening Remarks

Day 1 Chair - Justin Southcombe, Commercial Director, Perpetuum (United Kingdom)

KEYNOTE PANEL: BEST-IN-CLASS TOC PERSPECTIVES ON THE FUTURE OF DATA-DRIVEN MAINTENANCE & ITS IMPACT TO THE BOTTOM LINE

8:40 Scrutinise The Potential Of Predictive Maintenance In Practical Application - Will The Latest Technology Offer You The Best Opportunity To Drive Efficiencies? 

Railway operators are undeniably shifting towards a predictive maintenance model, but building a business case for condition based monitoring systems has proved difficult for the industry. Hear from multiple leading operators on how they have communicated the benefits internally and identified the measures of success.

  • Apply-cutting edge diagnostic software to improve your company's maintenance planning process
  • Understand the best methods for replacing planned maintenance with condition-based tasks to improve revenues
  • Build a business case to support the transition to condition based maintenance

Moderated by Justin Southcombe, Commercial Director, Perpetuum (Unidted Kingdom)

Panelist: Héloïse Nonne, Head of Data Science, SNCF (France)

Panelist: Neil O'Connor, Head of Fleet Performance, Southwest Trains (United Kingdom)

ROLLING STOCK PREDICTIVE MAINTENANCE

9:20 What Can We Expect When Using Artificial Intelligence To Predict Failure?

Having heard the perspective of multiple operators, this case study will take an in depth look at how predictive models can be designed for rolling stock maintenance, and will answer some key questions:

  • What exactly is a predictive model and how does it work?
  • How do we take iterative steps to build predictive models?
  • How do we address the 'black box problem'?
  • What questions should we answer before putting an artificial intelligence into production?

Héloïse Nonne, Head of Data Science, SNCF (France)

9:50 Question & Answer Session

NEXT GENERATION CBM

9:55 Next Generation "Condition Based Maintenance" - From Big To Smart Data

Condition based maintenance is more than just gathering and analyzing data. What is the most realistic  and fastest way to realize sustainable savings?

  • Explore reference cases from projects across Europe
  • Understand major blocking points and key success factors form CBM implementation
  • What's next - beyond "Condition Based Maintenance"

Dirk Seckler, Head of Sales Rail Services, Knorr Bremse (Germany)

10:15 Question & Answer Session

10:20 Networking Break Sponsored By Mechan (United Kingdom)

Join Your Peers In The Networking Exhibition Area To Discuss Vital Insights

UNLOCK MAINTENANCE EFFICIENCIES FROM THE CORRECT DATA

WHAT IS THE RIGHT DATA TO REVIEW?

11:00 Identify Which Data Sets Are Suitable For Extensive Analysis To Maximise The Payback Of Condition Based Maintenance

Big Data is an omnipresent term in train maintenance circles and is always at the centre of debate. But when dealing with large, complex data sets, which areas represent the most value and thus warrant the most extensive analysis? Hear from an industry leader to:

  • Assess condition, wayside and on-train monitoring to find out which method achieves the maximum payback for the operator
  • Identify false positives to ensure more reliable predictions
  • Review the ownership of data to create archive and conduct effective historical analysis

Jan Luijben, Information Manager, GVB (Netherlands)

11:30 Question & Answer Session

DUTCH RAILWAYS CASE STUDY

11:35 Right Time, Right Task, Right Train: Turning CBM Data Into Business Value - Predictive Maintenance Use Cases From Dutch Railways

Condition monitoring is more than detecting train failure or malfunctions. Continuous gathering of data allows for trend analysis over the entire fleet and allows for data-driven performance improvements for instance actual state-dependent maintenance. Find out how CBM data analytics push the limit of early warning detection in overheated wheel axle bearings and air leakage in braking pipes.

  • Detect different phases of degradation to identify corresponding maintenance actions
  • Build data-driven predictive models of remaining useful life to identify the right timing for maintenance
  • Automatize the detection and alarm generation to facilitate the process

Wan-Jui Lee, Data Scientist, Dutch Railways (Netherlands)

12:05 Question & Answer Session

CBM APPLICATION

12:10 Analyze CBM Results Obtained After Eight Years Of Experience To Effectively Apply CBM To Rolling Stock

CBM is currently front of mind in the rail industry, but a small number of operators are implementing it in a complete and efficient way.

But by reacting on time to prevent failures during operation and scheduling the proper maintenance interventions to extend the asset's life, savings can be obtained while ensuring a secure railway operation.

Real business cases will be explained during the presentation to demonstrate the main qualitative and quantitative benefits that have been obtained after the implementation of CBM technologies in:

  • One of the biggest and busiest Metros in the world
  • One of the main high speed fleets in Europe
  • Several regional trains and trams projects

Álvaro José Zevallos Román, Area Sales Manager Railway Division, NEM Solutions (Spain)

12:35 Question & Answer Session

PRINCIPAL DATA SOURCES

12:40 Choose Your Principal Data Source To Inspire Confidence In Your Remote Condition Monitoring Information

There is a lot of discussion, and quite rightly, about Big Data but the railways are only just embarking on the IoT journey. The choice in your principle data source is still one of the most important decisions you must make if confidence in the RCM system and the results are to be maximised, and deployment not delayed. This presentation will:

  • Investigate recent case studies from this year that show how the Perpetuum vibration monitoring system has been seamlessly applied across new rolling stock components
  • Compare common legacy maintenance optimisation practices with RCM methodologies
  • Discuss the innovations that might be required to speed up the introduction of RCM systems in railways

Justin Southcombe, Commercial Director, Perpetuum (United Kingdom)

13:10 Question & Answer Session

13:15 Networking Lunch

LONDON UNDERGROUND CASE STUDY

14:15 Hear About London Underground's Implementation Of Data-Driven Maintenance To Introduce A Coordinated Approach To Modern Practices

Hear how Chris Welford and Stephen Foot (London Underground) are leading a range of projects and initiatives which are implementing a more analytical overview of London Underground's coordinated approach to modernising its maintenance. Also view the context of this within TfL's organisational challenges and objectives

  • Discuss examples of projects delivering technical improvements to existing Train Monitoring Data systems to implement new Condition Monitoring systems (including demonstration video)
  • Understand the development of predictive algorithms; modelling, optimising, convincing stakeholders, determining the optimal usage model, and evaluating benefits of the new approach
  • Derive full benefit from improved technical solutions by developing and implementing new operating processes and building front line staff competence in usage of asset data
  • Use Train Monitoring Data system data to enable maintenance optimisation

Stephen Foot, Head of Asset Condition, Maintenance Engineering, London Underground-TfL (United Kingdom)

Chris Welford, Condition Monitoring Manager, Maintenance Engineering, London Underground-TfL (United Kingdom)

14:45 Question & Answer Session

ORGANISATIONAL DIGITAL MATURITY MODELS FOR CRITICAL INFRASTRUCTURE

14:50 Use Global COTS Real Time Information To Build The Case For Enterprise Digitalisation Solutions In Rail

Modern Railways are looking for uniform ways to dramatically improve operations using data to drive more timely and effective decision making. Industry and asset specific applications like automatic train control, condition maintenance and energy monitoring help deliver safety, availability and cost reductions, but limit data accessibility to all the organizational stakeholders who can accelerate process innovation. 

These application data silos also have a practical limit in their ability to integrate with business systems and processes.  This presentation will highlight several cases of railways taking a COTS real-time infrastructure approach to integrating all the assets and applications to deliver organizational transformation.

  • Use real-time Rolling Stock data to drive CBM on both the trains and railway
  • Review the value of real-time in condition monitoring
  • Build a system-wide view of operations to bring together all the data sources into "one version of the truth"
  • Nurture an organizational data driven culture
  • Leverage a collaborative data driven ecosystem

Matthew R Miller - Transportation Industry Principle, OSIsoft LLC (USA)

15:10 Question & Answer Session

UNLOCK TRUE VALUE FROM MULTIPLE DATA SETS

NEW FLEET CAPABILITIES & RETROFITTING OF DATA CAPTURE TOOLS

15:15 Identify Which Older Fleet Sensors Can Be Used To Develop Predictive Maintenance And Which Areas Warrant Investment

While presenting a business case has thus far been difficult, employing a CBM system on new fleets may seem a no-brainer for most forward-thinking train operators. What is more of a challenge is finding an inexpensive way to incorporate predictive maintenance for legacy fleets.

  • Assess which smaller tools can be employed on older fleets to develop predictive maintenance in a cost-effective manner
  • Find out which data is the most crucial to maintenance operations to ensure shrewd investment in necessary sensors
  • Discover how to maximize the value of data from existing sensors

Philippe de Laharpe, Head of Remote Diagnostics Project, Rolling Stock Division, SNCF (France)

15:45 Question & Answer Session

15:50 Networking Break Sponsored By Cyient (United Kingdom)

LESSONS LEARNED: THE RIGHT AND WRONG WAY TO APPLY CONDITION-BASED MAINTENANCE

16:35 Consider Errors Made In Predictive Maintenance Programs, As Well As Industry Best Practice, To Establish Good Business Rules For Operating Systems

Although it is clearly informative to hear examples of maintenance success, often it can be just as informative to hear what has gone wrong in order not to stray into unnecessary pitfalls. Hear from this operator to:

  • Identify which CBM strategies and practices have been found to be faulty to avoid replicating erroneous co-relations and false predictions
  • Pinpoint the precise data gathering devices and data sets that have not represented value to avoid unnecessary analysis and expenditure
  • View examples of successful CBM implementation in order to replicate success at your organisation

Paolo Masini, Director of Rolling Stock Engineering & Maintenance, Trenitalia (Italy)

17:05 Question & Answer Session

DOES ASSET DATA CREATE MORE PROBLEMS THAN IT SOLVES?

17:10 Harness Asset Data To Achieve A Successful Asset Condition Monitoring Program

Fleet Managers and Maintenance Teams can be overwhelmed by asset condition monitoring projects.

New IoT data sources are cause for anxiety to organisations: do I have the expertise to analyse the data? Do I have the internal organisation to act on the data? Do I need to invest in several new technologies and their integration? Do I know what problem I want to solve?

The journey from accessing proprietary data on the train, transforming it into actionable diagnostics and triggering work orders and mobile interventions is full of barriers and many projects fail to deliver value.

  • Discuss Railnova's journey to unlock asset value
  • Consider the hurdles the industry is facing to move to effective asset monitoring
  • Consider the best practices of Railnova clients to achieve success in their asset condition monitoring projects

Christian Sprauer, CEO, Railnova (Belgium)

17:30 Question & Answer Session

FERTAGUS CASE STUDY

17:35 Examine RCM Data Daily To Ensure Train Availability And Reliability

Using RCM data day-by-day can be a challenging procedure, but one which is crucial to update OEM maintenance plans and enhance reliability. Hear from this operator on how to:

  • Leverage RCM reliability figures to reactively alter maintenance strategies
  • Work closely with stock management and asset management teams to ensure the correct material and equipment selection for the train
  • Examine RCM data daily to maximise train reliability

João Grossinho, Director of Maintenance, Fertagus (Portugal)

18:05 Question & Answer Session

SIGN DETECTION METHODS AND COMPETENCY & SKILLS DEVELOPMENT

18:10 Review A Study For Failure Sign Detection Methods Using Monitoring Data On Commuter Trains

Plus

Discuss The Introduction Of Competency Training For Maintenance Staff in JR East

It is an ideal for railway companies to use rolling stock without failures, and these can be reduced through maintenance works. And if warning signs can be identified before failures, maintenance efficiencies can be reaped.

But for this innovative working style to be implemented, maintenance staff must be trained to have the necessary skills and competencies.

  • Discuss methods for failure sign detection using IT and monitoring systems
  • Reap benefits in maintenance work through prevention, foresight and estimation
  • Train maintenance staff in an innovative working style by using IT

Yoshimitsu Sugiura, Deputy General Manager, Principal Chief Researcher, Technical Centre, East Japan Railway Company (Japan)

Takumi Ishii, Deputy Director, East Japan Railway Company, Paris Office (Japan)

18:40 Question & Answer Session

18:45 Drinks Reception

DATA & ASSET OPTIMISED ROLLING STOCK MAINTENANCE SUMMIT: DAY 2, 8TH DECEMBER 2016

Technical Considerations To Drive Assets To Full Capacity & Optimise The Maintenance Supply Chain

7:30 Day 2 Registration

8:20 Day 2 Opening Address & Recap of Day 1

Day 2 Chair - Neil O'Connor, Head of Fleet Performance, Southwest Trains (United Kingdom)

KEYNOTE PANEL: SOURCING & SUPPLY CHAIN OPTIMISATION

8:25 Unlock Optimal Approaches To Mitigate Franchise Commitments On Maintenance Backlogs

Often a roadblock to consistent operations, an effectively managed supply chain can be the difference between a smooth train service and the fleet grinding to a halt. This keynote panel will multiple perspectives on how to manage these relationships, franchise commitments and spare parts effectively.

  • Demystify the relationships between production, maintenance, suppliers and ROSCOs to minimise the likelihood of a breakdown in the supply chain
  • Debottleneck the supply chain to minimize downtime waiting for replacement materials
  • Analyse intellectual property rights and software design rights to ensure a wider supply chain

Moderated by Neil O'Connor, Head of Fleet Performance, Southwest Trains (United Kingdom)

Panelist: Abhinay Ramani, New Trains Project Manager, First TransPennine Express (United Kingdom)

Panelist: Gustav Sjöberg, Business Development Manager, MTR Tech AB (Sweden)

COMPONENT OVERHAUL & LIFE CYCLE EXTENSION

8:55 Decide The Optimal Periodicity For Replacing Train Components To Safely Minimize Maintenance Costs

Every operator knows that there are huge potential savings to be made by increasing the periodicity of component replacements and maintenance work. However there are multifarious challenges that must be overcome in order to benefit.

  • Renegotiate your warranty with your train manufacturer to allow an increase in maintenance periodicity
  • Hear about manufacturers employing bottom up assessments and giving operator support to allow a longer time between overhauls
  • Discuss train care and maintenance techniques to increase reliability levels
  • Analyse the risk and uncertainties associated with maintenance of rolling stock critical components
  • Propose and demonstrate a risk model to determine the probability of component failure in order to support decisions on maintenance 

Abhinay Ramani, New Trains Project Manager, First TransPennine Express (United Kingdom)

Babakalli Alkali, Assistant Head of Department Mechanical Engineering, Glasgow Caledonian University (United Kingdom)

9:25 Question & Answer Session

FROM CENTRALIZED DATA PROCESSING TO DISTRIBUTED DATA PROCESSING; EMBEDDED ON-BOARD AGENT PROCESSING; BUILDING SMART DATA; REDESIGN OF THE TRAIN DIAGNOSIS SYSTEM; DATA ANALYTICS.

9:30 Intelligence of Trains: How to leverage the Remote Online Monitoring Technology by integrating it on the operations and maintenance strategy of the Railways Operator.

The Railway Industry has seen a big trend with the Train Digitalization strategy, but the major challenge is how to extract insight and valuable information from the large amounts of data available, in a way the Remote Online Condition Monitoring Tools (ROCM) are (will be) able to capture the railways experts' knowledge and therefore become a strategic tool to enhance the maintenance and operation company strategies.

In this session, Nomad Tech will:

  • Propose a top-down approach, from Railways Engineering to the ROCM, that will be presented and discussed with the audience;
  • Present real success cases of how to integrate the Remote Condition Monitoring Tools (ROCM) with your Railways Organization Maintenance strategy (e.g. Reliability Centred Maintenance) and Operations management.

Augusto Costa Franco, General Manager Software Engineering & Power Systems, Nomad Tech (Portugal)

9:50 Question & Answer Session

9:55 Networking Break Sponsored by Inspecta (Sweden)

MAINTENANCE, ENGINEERING & OPERATIONS: INTEGRATED APPROACHES TO ROLLING STOCK MAINTENANCE

10:40 Align Project Management And Leadership Skills To Ensure Effective Collaboration Between Fleet Engineering And Fleet Production

A struggle for some operators lies in the relationship between fleet engineering and fleet production, specifically regarding the understanding of each other's function. While one focuses on enhancing the fleet and the other on maintaining the train service, a joined up approach can yield great benefits.

  • Overcome conflicting objectives between fleet engineering and fleet production to ensure commonly held goals
  • Understand when to run services short to allow timely delivery of modifications
  • Ensure that data analysts and maintenance engineers work effectively together to maximise the value of data interpretation

Paul Edwards, Fleet Manager, London Overground (United Kingdom)

11:10 Question & Answer Session

APPLYING MSG TO MAINTENANCE PROGRAMS

11:15 Hear About The Application Of MSG To Enhance Maintenance Programme Development For RCM

Condition based maintenance using remote train monitoring, presents an undeniable opportunity for train operators to improve the predictability of system degradation and plan maintenance intervention strategies. It is not, however, a utopian solution to improving train performance, maintenance cost and downtime.

Remote train monitoring is a real-time inspection methodology, the benefits of which can only be realised, if it used to support a well constructed, preventative maintenance strategy. The application of Maintenance Steering Group logic (MSG), derived from the aviation sector, is designed and proven to reduce maintenance costs and improve reliability, whilst ensuring safety is maintained. This session will discuss;

  • The first principles of MSG and its processes
  • Maintenance organisation design to manage RCM based data
  • The benefits of an MSG based maintenance  programme in rolling stock performance
  • The business case for using an MSG based approach to maintenance programme design

Rob Spence, Managing Partner, Danburykline (United Kingdom)

11:35 Question & Answer Session

USE DATA TO ACHIEVE AVAILABILITY AND RELIABILITY

11:40 Gain Insight Into Cutting-Edge Predictive Maintenance To Drive Optimal Availability & Reliability

Working within a franchise throws up many challenges, not least of all the commitment to consistently deliver modifications. Find out how an operator is striking the right balance between which vehicles to stop for maintenance and when to stop them.

  • Develop operational mitigation strategies to ensure stable fleet availability
  • Bridge the gap between operational and maintenance teams to establish common reliability and availability goals
  • Ensure that your fleet operates at the expected capacity to avoid financial penalties

Neil O'Connor, Head of Fleet Performance, Southwest Trains (United Kingdom)

12:10 Question & Answer Session

CONTINUOUS IMPROVEMENT

12:15 Strategies For Continuous Improvements Of Fleet Reliability And Availability In The Stockholm Metro

MTR Tech has been responsible for the rolling stock maintenance in the Stockholm Metro since 2009. There has been a continuous improvement of delivery over time in both fleet reliability and availability. Gustav shares the main contributing factors, both on a strategic level and key maintenance improvement initiatives.

  • Discern the contractual responsibilities of a PTA-maintainer to clarify roles and give right incentives
  • Discuss the process for reliability improvements to support and structure the improvement work
  • Consider models for improvement (RCM, CBM) to analyze reliability and solutions
  • Review vehicle availability improvements to maximize traffic delivery
  • Implement cultural change to ensure theory meets practice

Gustav Sjöberg, Business Development Manager, MTR Tech AB (Sweden)

12:45 Question & Answer Session

12:50 Networking Lunch

TRAIN SYSTEM AVAILABILITY

13:35 Move From "Digitalization" To Train System Availability

"Digitalization" was one of the most often used words at Innotrans 2016.
The number of "digital" product announcements or articles published continues to grow since. Using data to improve is however nothing new. Train systems collect data to allow operators and maintainers to understand and to improve these systems for many years.

The novelty lies in the quantity of data that can be made available and managed
today in real time, and in the correlation of datasets that can create new information.
This presentation will reflect on the technical and cultural challenges that need to be addressed to fully benefit from these new developments. Examples from field deployments in operation today will be used to demonstrate how digital tools can help improving  train system availability:

  • Move from information to accurate prediction
  • Hear about HealthHub™, Alstom's solution for Predictive Health Management
  • See a demonstration of HealthHub™, at Virgin

Mike Muldoon, Commercial Director, Alstom (United Kingdom)

13:55 Question & Answer Session

SMART DATA ANALYTICS

14:00 Digitalization Transforms Transportation: Using Smart Data Analytics To Achieve Highest Availability In Mobility Services

Rail and road networks are essential for mobility and are facing major challenges. Cities are growing, more and more people and products must be moved - on the premise of guaranteeing safety, protecting the environment and managing costs.
Digitalization drives our mobility by using smart data analytics for infrastructure and vehicle service with the objective of guaranteeing highest availability, by taking IT-security seriously

  • Secure data transmission from sensor to central data storage
  • Turn data into value to enable Digital Services solutions (Smart Monitoring, Smart Data Analysis, Smart Prediction)
  • Overview of successful examples

Johannes Emmelheinz, CEO Mobility Services, Siemens (Germany)

14:20 Question & Answer Session

MAINTENANCE AND OPERATIONS

14:25 Case Study: Models To Achieve Mutual Goals And Interests Between Rolling Stock Maintenance And Operations

One key factor to achieve a top class traffic flow is to achieve a strong integration of rolling stock maintenance into the operations. In some areas conflicting interests will always exist, however many of them can be overcome and mitigated. MTR has in the Stockholm Metro managed to achieve a higher level of integration, through a number of measures from business set up to day-to-day operations procedures.

  • Discuss organization to set the structure for cooperation
  • Set goals and follow up procedures to align incentives
  • Outline key improvement areas to optimize day to day operations
  • Promote culture to increase staff motivation and understanding

Gustav Sjöberg, Business Development Manager, MTR Tech AB (Sweden)

14:55 Question & Answer Session

15:00 Networking Break

PROACTIVE CONDITION MONITORING

15:30 Proactive Condition Monitoring For Optimized Service And Extended Component Operating Life

  • Hear an overview of preferred condition monitoring strategies
  • Deliver the benefits of monitoring safety-critical components such as wheelsets and bearings
  • Discuss how condition-based maintenance helps minimize costly periods out of service
  • Extend the lifespan of expensive components through condition monitoring
  • Optimise operating mileage without compromising reliability or safety

Robin Foreshew, Business Development Director, Trimble Railway Asset Solutions / Nexala (United Kingdom)

15:50 Question & Answer Session

VR GROUP CASE STUDY

15:55 VR Group Case Study - CBM Pilot Program

VR Group plans to apply CBM to its diverse fleet of rolling stock. There are a lot of potential places where CBM can be applied, but it is essential to recognize where to start and how to allocate resources. It is important to be agile and introduce pilot programs to see what works and what doesn´t.

  • Identify where to use CBM to enhance maintenance operations
  • Learn how to make sure that you actually use the data in practice when planning maintenance activities and avoid that the reports are just "nice-to-have" data
  • Overview CBM case studies on brake pads and other train components

Jouko Järvinen, Operations Manager Maintenance Division, VR Group (Finland)

16:25 Question & Answer Session

16:30 Chair's Closing Summary

16:35 Close of Summit

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