virtual conference on maintenance planning

Smart Fleet Maintenance Summit

Improving the Circular Economy of
Rolling Stock Maintenance

 

16th & 17th November 2021, 

Virtual Event: Watch Live + Content Available On-Demand for 12 weeks

Agenda

Virtual Conference on Maintenance Planning: Implementing Industrial IoT Predictive Maintenance, & Reliability Centred Maintenance Analysis

The Rolling Stock Maintenance Summit is designed to help Heads of Fleet Engineering, Rolling Stock Maintenance, Planning & Supply Chain Managers implement Digital Transformation to Optimise their Maintenance Regimes by Introducing Innovation, Improving the Use of Data and Information to Support Decision Making and Deliver Improvements in Maintenance Standards to Deliver better Value from Maintenance Activities across multiple Rolling Stock assets. Apart from these, the virtual conference on maintenance planning has various other perks as well.

Implementing Efficiency Programs To Optimise Maintenance Regimes, Improving Reliability & Reducing Cost In Rail Operations

THE TIMINGS BELOW ARE DISPLAYED IN LOCAL TIME ZONES

DAY 1

16 Nov 2021

09:00

OPENING PANEL: Modernising Fleet Operations Utilizing Smart Maintenance Strategies: Adopting New Technologies to Make Fleet Maintenance and Operations More Efficient and Reliable

• Improving the introduction of new innovations to support maintenance activities, what can we learn from other operators at the rolling stock maintenance summit.
• How can operators optimize their current maintenance regimes to reduce the effort needed to implement them and release resources for other critical activities
• What are the common obstacles in new introducing new technologies, and how are operators overcoming these shortcomings to deliver cost benefits in their operations
• Getting more value from the data and information from on-board systems to make better-informed decisions and increase efficiency in your maintenance organization
• Understanding the distinction between operational technology and information technology in rail operations to drive improvements in your maintenance regimes through reliability centered maintenance analysis

DAY 1 CHAIRMAN: Pieter Hopmans, Manager Strategic Procurement, Planning & Purchase, NS

Sergio Barcena, Director of Operations Planning and Maintenance, Ouigo Spain

João Grossinho, Head of Rolling Stock, Fertagus - Grupo Barraqueiro

DAY 1

16 Nov 2021

10:00

Using Technology & Data to Reduce Overall Cost in Your Maintenance Budget, Managing the End to End Process to Ultimately Realizing the Savings in Your Maintenance Regimes

• How can rail operators effectively increase performance and drive improvements in maintenance standards through better use of data in their organisation's
• Having a clear view of your business processes to integrate and embed new methods and IT to deliver improvements in new technology implementations
• Building the people competencies within your organization to be able to utilize, analyse and respond to data to reduce maintenance interventions and cost

Marco Caposciutti, Technical Director, Trenitalia

DAY 1

16 Nov 2021

11:00

PREDICTIVE MAINTENANCE CONCEPTS IN AVIATION: Basic Principles in Aeronautical Application

• Maintenance main principle and finding critical patterns in data
• Predictive Maintenance Concept In Aviation
• Predictive maintenance in Alitalia
• Predictive maintenance – engine – performance deterioration, decision making process

Fabrizio Sandrelli, Manager Maintenance Planning and Control Center, Alitalia Società Aerea Italiana S.p.A.

Goffredo Danna, Manager, Engines Engineering Dept, Alitalia Società Aerea Italiana S.p.A.

DAY 1

16 Nov 2021

12:10

Case Study: How an Intercity Train Operator is Applying Telemetry Data and Pattern Recognition to Reduce In-Service Failures and Cost Substantially Through Preventative Maintenance on their EMU’s or Intercity Fleet

• Identifying the significant cost drivers of your existing maintenance on a yearly basis, which subsystems should you focus your investment in monitoring?
• Improving collection and analysis of data from On-board sub-systems to improve the economics of reducing maintenance costs
• Implementing cost-effective, robust, and easy-to-maintain sensors through industrial IoT predictive maintenance events, what sensors are operators using to monitor critical on-board subsystems?
• What are the cost benefits in using the preventive maintenance and algorithm recognition approach compared to the classical reactive maintenance approach?

Dr Tony Lee Kar-yun, Operations Director, MTR Hong Kong

DAY 1

16 Nov 2021

12:45

SNCF Case Study on Implementing Predictive Maintenance: Prognostic Expert System for Railway Fleet Maintenance

• Implementing a mixed maintenance solution based on real-time data analysis and condition-based maintenance
• Defining signalling thresholds using technical knowledge and physical models to assess the health state of a system
• Overcoming maintenance load and infrastructure availabilities to enhance the current maintenance regime
• Examine how dynamic thresholds are computed and how they are combined with failure thresholds to manage maintenance load and aging effects

Fabien Turgis, Research Engineer, Predictive Maintenance System for Railway Rolling Stock, SNCF

Pierre Audier, Research Engineer, Predictive Maintenance System for Railway Rolling Stock, SNCF

DAY 1

16 Nov 2021

14:15

Operator User Case Study: Implementing Data Monitoring of wheelsets on a Suburban Passenger Train to Reduce Maintenance Scheduling, Spare Parts and Materials Cost

• Setting the organizational goal of implementing predictive maintenance for wheelset maintenance and replacement
• How can operators improve the management wheel condition to reduce wheel flats or rolling contact fatigue and increase availability of their fleet?
• Examining the common failures with wheelsets to understand which critical parameters to measure
• Measuring wheel consumption to define a successful strategy for wheel profiling to reduce maintenance intervention

Curtis Wood, Data Scientist, VR FleetCare

DAY 1

16 Nov 2021

14:30

Using Machine Learning to Identify Dominant Failure Modes, Analyse and Process Data to Make Maintenance Scheduling Decisions

• How are operators using machine learning in their rail operations to improve maintenance processes?
• Using machine learning determine if a correlation exist between some variables in the data and a failure in a component
• How can data science teams within rail organisation work with the maintainers to build trust in their models to increase efficiencies in maintenance activities

Sami Kalevirta, Head of Digital Services, VR FleetCare

DAY 1

16 Nov 2021

15:00

Future Rail Vehicle Maintenance: Condition-Based And Automated Asset Management

• Finding suitable system integrators and automation partners with experience of operating in the railway
• The evolution of automation and robotics in rail maintenance and operations, what new modules are operators using to increase safety in train operations
• How can operators effectively deploy automation to increase financial and non-financial benefits in their maintenance operations
• Upgrading your depot space to accommodate the dimensions required operate new machinery in an increasingly busy environment
• Improving occupational and operational safety in a maintenance workshop environment, what technologies and solutions are operators implementing to increase workplace safety

Adam Bevan, Professor, Institute of Railway Research/Huddersfield University

Farouk Balouchi, Research Fellow, Institute of Railway Research/ Huddersfield University

DAY 2

17 Nov 2021

09:00

DAY 2 OPENING: Training and Processes Management and the Importance of Technology and IT in Rail Operations as a Driver for Performance Improvement

• Investing in the future workforce to deliver a seamless digital transformation in rail maintenance and operations
• Implementing high level training for management teams on the principles and benefits of lean to get buy-in to principles of improvement
• Applying a multi discipline approach including change management, lean business improvement techniques and data analysis to help change people behaviours
• Putting the brakes on: Stop doing what you are doing and expecting a different result
• Focusing on continuous improvement as key driver for performance and reliability
• Investing in training and development of senior management and maintenance engineers to improve software awareness within rail organisations
• Multiskilling production mechanics to improve critical knowledge around software systems

Neil Robertson, Chief Executive, National Skills Academy for Rail

Keisuke Setogawa, Business Manager, Central Japan Railway Company

Kristijan Apostolski, Project Manager Continuous Improvement, Great Western Railway

DAY 2

17 Nov 2021

10:00

Reshaping Fleet Maintenance with SAP - Run Simple and Intelligent

Driving high performing fleet assets contributes significantly to customer satisfaction and safety. Embracing digital transformation enables companies to react with speed and flexibility to complex business challenges associated with modern fleet maintenance. This session will focus on:

• SAP's vision for Intelligent Fleet Maintenance.
• Digital transformation anchors: (1) Revitalizing core solutions and (2) Enabling innovation.
• SBB's journey towards reshaping fleet maintenance with SAP

Johann Schachtner, Solution Manager, Industry Business Unit Travel and Transportation, SAP SE

Urs Gehrig, Senior Consultant, Corporate Development, SBB CFF FFS

DAY 2

17 Nov 2021

11:00

Introduction of an IoT train: software management challenges

The focus of this session will be on software management and cyber security, both during the introduction of a new train and while preparing the standing organisation for maintenance.

Meinte Wildschut, Project Manager, NS

Daniel Jaeggi, Head of Business Development, RazorSecure

DAY 2

17 Nov 2021

12:00

How Can Rail Operators Make Sure Their Maintenance Regimes Fit the Use of The Trains to Increase Efficiencies in Their Operations: Implementing Effective Strategies for Planning and Scheduling of Production for Rolling Stock Maintenance:

• What strategies and technologies are operators implementing to improve planning and allocation of resources for rolling stock maintenance?
• Improving specification in maintenance planning for overhauls and managing the impact of engineering changes in maintenance plans
• Using AI to track the mileage of your trains, plot new routes and increase efficiencies in maintenance planning to reduce cost in parts and consumables
• Optimizing overhaul planning to extend component and material life, reducing cost and increasing availability for operators
• How do you identify high risk items In Your Maintenance Planning and are the same for All Operators?
• How can rail operators make sure their maintenance regimes fits the use of the trains to increase efficiencies in their operations

Dave Hatfield, Fleet Director, Grand Central Railway Co

Richard Poulton, Managing Director, T&RS Engineering Ltd

Tadashi Ono, Senior Manager, East Japan Railway Company

DAY 2

17 Nov 2021

12:30

Using Methods such as Reliability Centred Maintenance to Manage the Reliability of Modern Assets and Initiate a Paradigm Shift from Reactive to Proactive Management of Maintenance

• Understand how Reliability Centred Maintenance can be used to create a cost-effective maintenance strategy to address the dominant causes of equipment failure
• Implementing RCM Assessment to define the maintenance requirement for each failure mode to improve maintenance planning and increase efficiencies in parts and materials ordering
• How are operators implementing RCM process to identify the operating context of the component or system and determining a Failure Mode Effects and Criticality Analysis
• Applying RCM logic to determine the appropriate maintenance tasks for the identified failure modes in the FMECA
• Reverse engineering failure modes and effects analysis to determine the key variables and define effective counter measure

Speakers to be announced

DAY 2

17 Nov 2021

13:45

The Reality of a Holistic Railway System: Collaborating with Operators, Infrastructure and Suppliers to Improve Business Processes by Sharing Data on Common Failure Data Environment Within Rail Operations

• What does collaboration mean in the context of the rail industry and how are operators working together to share information?
• Insights from suppliers and operators on their business processes, how they are set up, how they are run, what data plays an important role in decision making?
• Improving maintenance standards by sharing or buying data from suppliers on common failure data environment to improve business processes and reduce maintenance interventions?
• Setting best standards in sharing of information and data between rail operators to drive improvements in the networks and prevent speed restrictions
• Working with infrastructure owners to standardize equipment on-board trains to increase coverage of the network and deliver benefits for maintainers across the whole rail network
• Understand how data from infrastructure inspections are helping train operators build a better understanding of track forces on the train undercarriage

Juliette van Driel, System Manager WTMS and Real-time monitoring, ProRail

Danilo Sorrentino, Head of Vehicle-Track Interaction Section, SNCF RÉSEAU

Mercedes Gutierrez, UIC Infrastructure & TTI Senior Advisor, UIC

DAY 2

17 Nov 2021

14:30

Optimising Materials Management, Forecasting, Storage Management of Spare Parts to Guarantee Parts Availability for Routine Maintenance and Heavy Overhauls

• Strategies to reduce failure rates on high value equipment to save significant cost during routine maintenance and fleet overhauls
• Moving from time-based maintenance to condition-based maintenance to extend the life cycle of rolling stock equipment and components
• Implementing technologies to optimize overhaul planning to extend component and material life, reducing cost, and increasing availability for operators
• What are the benefits and consequences of introducing digital manufacturing processes to increase availability of parts, how does it affect your downstream processes like stores management?
• Finding cost effective ways to managing storage of materials and items onsite and offsite, are there any other solutions outside of procuring more space or entering a managed service agreement?

Joris van de Sande, 3D printing program manager/Strategic Buyer, NS

DAY 2

17 Nov 2021

14:30

Optimising Materials Management, Forecasting, Storage Management of Spare Parts to Guarantee Parts Availability for Routine Maintenance and Heavy Overhauls

• Strategies to reduce failure rates on high value equipment to save significant cost during routine maintenance and fleet overhauls
• Moving from time-based maintenance to condition based maintenance to extend the life cycle of rolling stock equipment and components
• Implementing new technologies to optimize overhaul planning to extend component and material life, reducing cost, and increasing availability for operators
• What are the benefits and consequences of introducing of digital manufacturing processes to increase availability of parts, how does it affect your downstream processes like stores management?
• Finding cost effective ways to managing storage of materials and items onsite and offsite, are there any other solutions outside of procuring more space or entering a managed service agreement?

Joris van de Sande, 3D printing program manager/Strategic Buyer, NS

Who will attend

industrial iot predictive maintenance events

Roles

Heads of Fleet Engineering

Directors of Fleet Production

Rolling Stock Maintenance Directors

Rolling Stock Technical Managers

Fleet Planning Managers

Directors of Maintenance Procurement

Sourcing Managers Parts & Materials

Heavy Works Manager (Overhaul)

Depot Managers

Chief Data Scientist

Heads of Maintenance Modernisation

Directors Training & Continuous Improvement

Rolling Stock & Technologies Engineers

SAP EAM Rolling Stock Asset Managers

Companies

Train Operating Companies

Infrastructure Owners

Original Equipment Manufacturers (OEMs)

Train Operating Companies (TOCs)

3rd Party Sub-Systems Equipment Manufacturers

Maintenance organisations

Data Management Software Providers

Business Process Improvement Consulting Companies

HR Training Companies

Cyber Security Services

Manufacturers of materials and consumables

Engineering Companies

cyber security virtual conferences

Industry Perspectives

"We have implemented technology over the years which hasn't realised its full potential. The technology is not built around the way in which we organise ourselves as a business or the way in which we generally operate. So, do you change the organisation to match the technology that's being provided? Or do you want the technology that aligns with the way in which you operate as a business? How do you get something that's fully embedded fundamentally working well for you? I think that's quite a difficult piece.”

 Head of Asset Condition,
London Regional Metro Operator

 

“The biggest challenge for the future is to deliver a preventive maintenance strategy in rolling stock operations. That's only possible with pattern recognition, big data and analytics that come from the train. If we're able acquire data over a longer period of time we will be able to optimise our maintenance plan significantly to save costs.  It's very difficult to do this without data and you need to be very brave to take decisions, for example to skip some scheduled replacement of an element without enough data.”

Program Manager New Rolling Stock, National Passenger Operator, Belgium

“People have been talking about predictive maintenance for years. It seems that there are very few successful cases that have been showcased in the industry. I think it would be great to discuss what we have done so far in this area and what are the pain points today, where and how the industry has been able to overcome those pain points to be successful in the predictive maintenance approach.”

Chief RS Asset Development Manager, National Passenger Operator,
Hong Kong