Rail Infrastructure 
Asset Management Summit

• What are the common challenges in improving digitalization and data management, exploring gaps in digitization, and addressing challenges in storing and retrieving asset information efficiently.
• Transforming Data into Value, examining the process of turning raw data into actionable insights, informed decisions and the potential of AI and machine learning in analysing big data streams
• Addressing the challenge of establishing shared information flows and improving standards for common data use within rail operations and maintenance
• Exploring the economic and operational benefits of investing in data management for reliability improvement, addressing the operational advantages of resilient rail systems under varying conditions.

• Comprehending the importance of data transparency in rail operations, developing strategies to improve transparency, data quality and identifying alternative available data sources.
• How are owners confronting the challenges of integrating legacy IT systems and improving the accuracy of manually entered data to build reliable algorithms for rail operations.
• Building trust through transparent data practices, defining the limitations of your data and models to build confidence in models used to improved decision making in rail.

30 minutes networking break and refreshments in the main networking and exhibition space of the summit.

• The role of leadership in championing data-driven decision-making, Cultivating a Data-Driven Mindset in Rail Culture
• Importance of Data Quality, Addressing the mindset of data administrators and the significance of data quality for effective decision-making, what step are owners taking to improve data quality in rail operations.
• Connecting data quality to the effectiveness of AI systems, emphasizing that accurate data entry is essential for AI model reliability and highlighting the impact of inaccurate data on decision-making.

• Brief overview on how the rail domain is capable of onboarding new technologies.
• Examples of how Space technologies (satellite services) could support Railways (Satellite Communications, Earth Observation, GNSS-GPS/Galileo…)
• Focus on the latest “use case” (Safe Train Positioning), and how the European Railway stakeholders jointly with Space stakeholders work together to bring out a proposal for a satellite safety of life services applicable to railways (ERTMS).

• Examining the multifaceted impact of digitalization on rail safety, showcasing how technology contributes to workforce safety, accident reduction, and error reduction.
• Productivity and performance gains, discover how digitalization strategies can drive productivity increases, streamlining operations while maintaining a focus on safety protocols.
• Explore the integration of digital tools, such as geofencing and data analytics, to effectively manage fatigue among rail workers, optimizing performance and well-being.

Asset information is often stored in disparate databases with operational performance not linked to causal assets and low data quality on fundamental asset properties linked to life-cycle and planning requirements, including size, intervention, unit costs, and lifetime. For evaluation of Asset condition to determine renewal and maintenance requirements for financing, it is crucial to ensure a high Data Quality foundation. The Network condition evaluation framework builds a structured database of Asset condition through prioritisation of data quality on asset parameters linked to life-cycle evaluation, algorithmic rules and processes for comprehensive data quality control and enhancement, and assignment of disparate data sources to causal assets for renewal and maintenance indication. A portfolio Network condition is then evaluated based on asset KPIs aggregated to a Condition grade, generating a foundation for financing scenario modelling, including potential condition deterioration, renewal and maintenance requirements, and public reporting of current Network asset management.

1 hour networking break including lunch and refreshments in the main networking and exhibition space of the summit.

BENEFITS OF INVESTING IN DIGITAL STRATEGIES FOR DATA COLLECTION AND OPTIMIZING DECISION-MAKING PROCESSES, BUILDING JUSTIFICATION FOR INVESTMENT IN DIGITAL SYSTEMS TO IMPROVE OVERALL EFFICIENCY IN RAIL OPERATIONS

GeoNext will present practical examples of how to increase the quality of a point cloud, the higher the quality of a point cloud, the more detailed information can be extracted. We show how to improve a misalignment of a mobile collected point clouds.

• What is the current industry level of maturity, incorporating digital twin and GIS technologies into rail projects, particularly focusing on advanced stations, route planning, and safety measures.
• Predictive analytics for passenger safety, real-world applications, benefits, and challenges of using digital twins for ensuring passenger safety.
• Rail renewals, potential for digital twins in planning rail asset renewals, examine how digital twins can improve decision-making, predictive maintenance, and optimising the lifecycle of rail assets.
• Integrating artificial intelligence (AI) and machine learning (ML) in conjunction with digital twins in rail asset management, enhancing data analysis, modelling, and prediction to improve decision-making in rail.

30 minutes networking break and refreshments in the main networking and exhibition space of the summit.

• Collecting information in the design stage, preparing asset information for the operations phase
• BIM processes, models, drawing, reports, and data drop
• What information do you have and what information is needed to attribute information in BIM models?
• Key attributes to uniquely identify the elements and group data by type numbers.
• Digital information and requirement for construction and handover stages

• What is Infrabel responsible for?
• How have we introduced GIS at Infrabel (with the example of the InfraGIS application and its different representations: geographic, schematic & photographic via “RailView”)?
• How can GIS & geolocation be used to ensure worker safety on railway construction sites (presenting examples of some projects under the “Safer-Work” programme)?

• Building Complete Models, exploring the ease and challenges of constructing comprehensive models using data-driven approaches, AI, and mathematical optimization to enhance railway operations.
• What is the initial cost associated with AI and Machine learning and what are the expectations on ROI, potentials savings in performance, maintenance, and renewals cost?
• Measuring cost-benefit investing in machine learning or AI, practical approaches to quantify the impact of technology and innovation adoption in rail projects, including AI and machine learning.

• Discover how collaborative partnerships can revolutionize digital asset management, optimizing data strategies and boosting information capabilities within the constantly evolving data landscape.
• Gain insights into how rail companies are shifting from in-house teams to leveraging specialized external resources, streamlining asset information management while allowing them to focus on core competencies.
• Explore the benefits of internal teams vs dedicated companies for processing sensor data and asset information, enabling efficient decision-making and maintaining data relevance.
• Working with owners to build a robust case for investing in condition monitoring systems, calculating the tangible costs of failures and unreliability, enabling accurate Roi forecasting for the investments in condition monitoring.

90 minutes drinks reception and canapes in the main networking and exhibition space of the summit.