8:00AM Registration And Breakfast Networking

8:30AM Conference Chair’s Welcome & Opening Remarks

David McGorman, Digital Director, Unipart Rail & Managing Director, Instrumentel

8:40AM How Can IoT And BIG DATA Transform Rail & Rolling Stock Maintenance

  • Identifying and positioning the unique territorial, terrain and operating challenges specific to the middle east region, Rail Operators, Transit Authorities, Municipalities and Key Stake Holders
  • Exploring the potentials of Digitalisation to enhance your operations and cost efficiencies
  • A Partner ecosystem enables a new thinking for rail

9:00AM Depot Planning And Refurbishment To Incorporate New Technology – Including Robotics, Condition Monitoring, Scanning Systems & Automation

  • Best practices for optimising and planning depot maintenance activities
  • Optimally configuring new technologies
  • Training the workforce to handle new technologies

9:20AM Strategic Planning For Retrofitting On Board Data Collection Systems (Case Study)

Kapil Jambuhlkar, Head of Rolling Stock Maintenance – Indian Railways

  • Extending the life and cost efficiency of ageing rolling stock – development of a technical retrofitting strategy
  • Business case and budgeting for retro-fitting
  • Examining the technologies, sensors and devises to be used on rolling stock itself, the technology systems, databases and IoT
  • Identifying what is possible when developing a strategy to retrofit ageing rolling stock, cost and feasibility

9:40AM Rail digital twins for maintenance analytics: An Industrial AI approach

Dr. Diego Galar , Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering, LTU, Luleå University

  • For  railway assets, much data needs to be captured and information extracted to assess the overall condition of the whole system including the one from design and manufacturing which obviously contains the physical knowledge. Therefore the integration of asset information during the entire lifecycle is required in IT/OT /ET dimensions to get an accurate health assessment of the whole system.
  • However, railway is conservative and attached to PM systems and early replacements so  the  lack  of  data  on  advanced  degraded  states   and  “black  swans”  makes  the  data-driven approach vulnerable to such situations. The risk related to these scenarios, despite their  low  latency,  is  not  acceptable,  especially  for  this type of assets  for  which  safety  is  a  must.
  • Therefore, there is a need to augment datasets before training data-driven algorithms. For this purpose Data covering a wider range of scenarios can be obtained by synthetic data generated by physics-based models. These models need to be realistic and provide meaningful and comparable information about the behaviour of the system under observation.
  • Industrial AI can help the use/owner/maintainer/designer to perform a virtual commissioning of the asset where it is digitized and virtualized combining the existing physical models with the data collected from the field and produce a digital twin containing both data driven and physical information.


10:00AM Upgrading Asset Management Systems, Reporting & Analytics To Improve Data Monitoring Efficiencies

Mohammed Alshamlan, Rolling Stock Digitalization Strategy Manager, Saudi Railway Company (tbc)

Yaser Halawani, Rolling Stocks Maintenance Manager-Freight, Saudi Railway Company (tbc)

  • How to identify opportunities to upgrade asset management systems and monitoring systems on legacy trains to improve on reliability and reduce maintenance incidents.
  • Examining the business case for making the investment in upgrading.
  • Understanding the life cycle cost and potential maintenance savings for the entire life of the train

10:20AM Customization And Integration of Wayside SMART YARD and On Board Condition Monitoring Technologies

Deepak Tripathi, Chief Maintenance Engineer & Head Of Railway Maintenance, Konkan Railway Corp


10:40AM From Real Time Asset Monitoring Towards Dynamic Maintenance And Operations

Frederic Sanchez, Maintenance Operations Director, Alstom Group

  • Mastering Condition-Based Maintenance and PHM (prognostics & health management
  • Turning data into actions to improve the efficiency of operations and maintenance execution
  • Innovative Dynamic Maintenance Planning programme


11:30AM Transforming Middle East Rail-Freight With Digitalized Systems And IoT

11:50AM The Cyber Threat: Strategies For Protecting And Securing The Digital Future

Muneeb Anjum Hameed, Business Manager Digital Transformation and Cybersecurity, TUV Rheinland

  • Advancement of integrated operational technologies and the Railway Internet of Things have enhanced operational efficiency but paradoxically has increased the attack surface exponentially across the international transport sector
  • The impact of supply chain vulnerabilities, insecure IT systems, the challenge of securely converging IT and OT and managing blind spots in the networks asset inventory, has increased security threats.
  • Invested in ensuring the design of a secure foundation
  • Innovation, Standardisation and Cybersecurity by Design for Digital Railways- Overview from the European Commission
  • Protecting customised transport systems and unified data streams: handling growing privacy concern
  • Safety and security in a digital age: Protecting Assets and Infrastructure Networks
  • Preventing Cyber Hacks: Enabling Secure Frameworks And Addressing The Heightened Security Challenges
  • Infrastructure And Assets To Increase Safety, Performance and Functionality

12:10PM Leveraging ‘Big Data & IoT’ To Innovate Rolling Stock Maintenance: Artificial Intelligence (AI) And Big Data Technology

Ammar Alanazi, Director Of The National Center For Artificial Intelligence And Big Data Technology

KACST – King Abdulaziz City For Science And Technology (tbc)

  • What is ‘Big Data’, IoT & Industry 4.0?
  • Why and how is ‘Big Data’ and IOT transferable
  • Outlining the ambitions of “Big Data, IoT and 4.0
  • Identifying the unknown data – data you did not know existed
  • Identifying the areas and opportunities for financial gain
  • Effective planning and control of maintenance tasks
  • Real time monitoring of asset health
  • Creating value by digitalising train operations
  • SaaS ‘Software as a Service Business Model

12:30PM The Challenges And Implications Of Digital Adoption

Samy Abdaltawab Abdullatif Mohamed, Vice Chairman And Head Of Line 2 & 3 Of Greater Cairo Metro (tbc)

12:50PM The Rail Maintenance Transformation Journey – How IoT And Predictive Maintenance Can Reduce The Cost And Increasing Quality Along The Entire Cycle Of A Railway Vehicle

Giuseppe Giannini, Global Head Of Services And Maintenance Technology And Systems, Hitachi Rail STS




1:50PM The Current And Future State Of Wayside Diagnostic Monitoring As A Tool For Condition Based Maintenance

Nick Ashberger, General Manager Business Development, Track IQ, A Wabtec Company

  • Designed to measure and monitor the condition performance of rail car components
  • Automated analysis of component condition data identifying faults before failures occur
  • European customer case study demonstrating the benefits and future of this technology

2:10PM Quantitative Data And Machine Learning Enable A Quantum Leap In Real-Time-Train Positioning

Frauscher Sensor Technology [tbc]

  • Quantitative DAS is the next evolution of distributed wayside sensing
  • In combination with machine learning, this technology provides more accurate information
  • Real-Time train localisation, detailed information on train length and train integrity will enable new and efficient approaches for future proof train operation

2:20PM Digitalisation Of Rolling Stock Maintenance: Not Only A Matter Of Predictive Diagnostic

Javier de la Cruz – LeadMind Managing Director, CAF S.A

  • Pros and cons and state of the art of predictive maintenance
  • Role to introduce LEADMIND: Predictive Analytics For Rolling Stock
  • What else can digitalisation bring to Rolling Stock Maintenance?
  • Digitalisation success cases beyond the predictive diagnosis

2:40PM Wheel set Lifecycle Monitoring

3:00PM On-Board IoT Solutions Applied For Reliable Maintenance Extension Of Safety Critical Railway Wheel-Set

Victor Martinez, Global Head of Condition Monitoring & Digitalisation Competence Center, SKF Group [tbc]

  • Bogies maintenance encounters high percentage of the train lifecycle cost and wheel life has been considerably extended during recent years
  • Wheel-set bearings are safety critical components with fixed maintenance intervals, are becoming the limiting factor for wheel-set bogie overhaul maintenance extension

3:20PM Overcoming The Challenges of Supporting A Network-Wide Program When Digitalising Your Operations

Matt Miller, Global Transportation Industry Principal, OSIsoft

  • Recognising The Technical Barriers That Effect Progression During The Lengthy Public Tendering Process
  • Proof of Practice – Highlighting Several National Developments In Rail
  • Compare Lessons Learnt


4:00PM From Real Time Asset Monitoring Towards Dynamic Maintenance And Operations

Frederic Sanchez, Maintenance Operations Director, Alstom

4:20PM Processing Big Data For Maintenance – What New Technologies Can Be Applied To Rolling Stock In A Costs Effective Manner?

  • How To Ensure You Are Getting Maximum Value For Your Data – Collection, Storage, Processing And Presentation
  • Capturing Data Systematically So It Can Be Compared Accurately With Previous And Future Data
  • Realising Value From Data From Outside Your System
  • Utilising Real Time Monitoring – Getting Data From The Source To Your Data Base, And Actually Using It
  • How Can You Crunch Data Into Useful Formats That Can Be Processed In A Meaningful And Easy To Understand Way
  • Analysing And Interpreting Data And Establishing Trends
  • Importance Of Data Quality And Data As An Asset

4:40PM How To Prepare For Predictive Maintenance

David McGorman, Digital Director, Unipart Rail & Managing Director, Instrumentel

  • Condition Based Maintenance and the importance of actionable information
  • Data acquisition and large number of Rail assets and the importance of understanding your data
  • Case Study: Showing how condition based maintenance can create value, operational efficiencies and savings
  • How Condition Based Maintenance informs our Condition Based Supply Chain, creating a digital dynamic supply chain of the future

5:00PM The Indian Railways Big Data Strategy For Rolling Stock

Vivek Mohan, Director, Mechanical Engineering (Freight), Indian Railways

5:20PM SERCO Middle East: Rolling Stock Optimisation

Adam Scanlon, Rolling Stock & Depots Manager, Dubai Metro, SERCO Middle East

  • How can we measure the benefits of digitalisation?
  • What will the future look like when IoT & BIG DATA has fully landed
  • Using Digital Twin concepts to drive digital transformation


5:40PM Interpreting Data To Deliver Actual Results On Reducing Maintenance Cost, Predicting Failure Condition & Optimizing The Reliability Of Onboard System Components


6:00PM SERCO Middle East: All Attendee Drinks Reception Hosted By