Rail Infrastructure 
Asset Management Summit

• Examining the level of predictive maintenance capabilities offered by current asset management system suppliers, including reinforcement learning, supervised learning, and non-supervised learning?
• Delve into the evolving landscape of enterprise asset management systems, exploring the latest trends and capabilities being integrated into the next generation of platforms.
• Essential questions operators should be asking asset management system suppliers to ensure alignment with their specific needs, including predictive maintenance capabilities and the integration of aii.

• What are the benefits of an integrated digital twin solution bringing together asset management, geospatial data, linear views, and real-time data feeds, enhancing collaboration between railway departments and stakeholders?
• How are suppliers developing tools withing their asset management systems to provide owners with a linear scale view track conditions to enable digital twin capabilities in rail?
• Learn how mobile solutions enable field engineers to interact with asset management systems, facilitating data collection and maintenance activities while providing a platform for ai and machine learning integration.

• Explore the transformation from traditional mechanical approaches to a digital era in rail asset management, incorporating digital components and software solutions and understand how this shift impact’s reliability maintenance strategies.
• What new technologies and software solutions are being developed to analyse vast sets of rail asset data efficiently, examine how these innovations have the potential to redefine data-driven decision-making.
• How are rail control rooms integrating software and digital data into their operations, leading to improved visualization of the actual condition of rail assets?

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

• Implementing a holistic maintenance strategy, what are the benefits integrating reactive, scheduled, and remaining useful life maintenance for a comprehensive approach to improving asset reliability in rail.
• Breaking data silos to address challenges related to data isolation within rail departments, understanding the importance of sharing information for informed decision-making.
• The value of leadership in transformation, the role of organisational leaders in aligning departments toward a common predictive maintenance vision

• How is the rail industry working to enhance collaboration and share efforts to leverage data, ai, and machine learning to enhance the accuracy of predictive models aimed at forecasting asset failures.
• Comparative analysis, sharing case studies from different railways, revealing how various operators approach predictive maintenance using these technologies and the varying levels of accuracy achieved.
• Exploring the role of emerging talents in driving breakthroughs within railway organisations, where skilled individuals combine data science and domain knowledge to develop innovative solutions.

• How are infrastructure owners leveraging new technologies and data analytics to enhance their understanding of failure modes, enabling more effective decision-making and optimising maintenance strategies.
• Examine the evolution of risk-based maintenance methodologies within the rail industry, how do owners find the right balance between proactive and reactive maintenance?
• Improving hot weather resilience, addressing issues related to track expansion, thermal stress, and potential service disruptions.

• The challenges of managing diverse assets within a complex rail system and their interconnected effects on safety, reliability, and efficiency.
• Strategies for optimizing the allocation of resources to different asset types to achieve a cohesive and high-performing railway network.
• Holistic evaluation and management of risks across the rail network, balancing individual asset risks with broader system safety considerations, and the impacts of various decisions on overall railway operations.

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

• Analysing the benefits of a unified global framework in rail asset management to drive growth and consistency across operating companies.
• Balancing sustainability and asset management, examine the intricate relationship between asset management and sustainability, understanding how a lack of standardization can hinder sustainable efforts.
• Optimising approach to metrics and reporting, emphasising the significance of comprehensive metrics and reporting and addressing the challenges posed by focusing solely on individual metrics and measurements.

• Asset management maturity assessment, going beyond existing frameworks and metrics, measuring asset management maturity to ensure profitable and sustainable rail operations.
• The correlation between asset management maturity and sustainability, understanding the critical role of mature asset management practices in achieving sustainability goals and aligning with global standards.
• Exploring the challenges of fragmented asset management practices within the rail industry, creating a holistic evaluation framework that aligns organizational processes and practices with industry benchmarks.

• Finding the optimal balance between asset renewals, refurbishments, and maintenance activities in rail infrastructure management, what are the key factors influencing the decision-making process?
• Understand how predictive condition monitoring and other technological tools can provide valuable insights for identifying optimal timing for asset interventions.
• Examining the interplay between engineering standards and the need for flexibility in asset management strategies and addressing scenarios where customization might be more beneficial.

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

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