AIPM

Project description

The main objective was to foster the adoption of Artificial Intelligence (AI) in the railway sector. This project aimed to enable members to learn collaboratively, share successes and challenges, and accelerate the adoption of model-driven approaches. Predictive Maintenance (PM) was identified as the project’s focal area, given its significant potential to transform maintenance practices across infrastructure and rolling stock domains.

We addressed the following areas:

1. Current Status of AI adoption for Predictive Maintenance per member (overview of the progress made by participating members, showcasing how AI solutions are being developed and operationalized to address specific requirements and enhance performance)

1. What does AI bring to the table to improve maintenance: Economic Benefits: Transforming Railway Maintenance with AI, Risk Management, Economic Optimization, Safety Enhancements

1. How: Achieving AI Success in Railways: Critical Factors: Organizational Variances and Resource Gaps, Building a Strong Business Case, Laying a Technological Foundation, Setting Realistic Expectations,

1. Conclusion & Takeaway manifesto : Data Readiness and Quality, AI’s Role in Rail Operations, Collaboration and Organizational Impact Managing Expectations, The Need for Collaboration, A Collective Vision for AI in Railways

Deliverables

• Executive report outlining the current status of AI adoption, its economic and operational benefits, and the critical factors for success. Drawing from insights gained over the past three years, it offers practical recommendations to address challenges and unlock the transformative potential of AI in railways.

• Catalogue of use cases (from Proof-of- Concept & pilot phases to operation phase)

• Yearly reports on AIPM project activity

Project Members