Leveraging Data and AI for Predictive Maintenance in Rail Webinar

Leveraging Data and AI for Predictive Maintenance in Rail Webinar

April 24, 2024 | Online :: Central Time

Maintenance is a major recurring cost for rail operators and asset owners. Predictive Maintenance, which can predict the likelihood of failure, has the potential to greatly improve efficiency, reliability and safety of rail operations. While the opportunities are abundant there are also challenges.

Railway companies are in various stages of data utilization and maintenance maturity to explore, comprehend and adopt Predictive Maintenance. This complimentary 60-minute webinar will introduce key concepts such as Big Data and Industrial Internet of Things (IIoT); discuss use cases of artificial intelligence/machine learning (AI/ML) in rail maintenance; highlight benefits and challenges in leveraging Big Data; and share best practices from pilot projects.

Learning Outcomes

  • Develop skills to interpret AI systems and build the AI-mindset within your organization
  • Learn about emerging tools and techniques used to reduce maintenance costs and improve operations
  • Gain insights to build business case for launching pilot projects that utilize data and analytics
  • Share best practices to reduce rail maintenance costs and improve operations


Wednesday, April 24, 2024 : Central Time

12:45 – 1:00 p.m.
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1:00 – 2:00 p.m.
Webcast Timing


    • Key terms and concepts
    • AI mindset and varying levels of adoption
    • Predictive Maintenance as a game changer

Use Cases of AI/ML in Rail Maintenance

    • Early detection of failures
    • Dynamic maintenance scheduling
    • Yard automation

Opportunities and Challenges in Leveraging Big Data

    • Asset utilization and resource allocation
    • Technical and culture issues with Data Silos
    • Cybersecurity and data privacy

Best Practices in Leveraging Data and AI for Rail Maintenance

    • Dashboards
    • Modeling and Simulation
    • Intelligent Networking of Subsystems


Shivani Saxena, Director, TAM America

Shivani Saxena, Director at TAM America, has experience of over 21 years in supporting clients seeking to improve the efficiency, capacity, safety and reliability of their assets. She delivers consulting assignments, research projects, knowledge transfer sessions and technical conferences. Prior to TAM America, Shivani has worked with CH2M Hill (now Jacobs), Kleinfelder, and Global Mass Transit.

Shivani received her undergraduate degree in civil engineering from the Indian Institute of Technology (IIT), Kanpur, India, master’s degree in civil and environmental engineering from the University of California, Berkeley, USA, and master’s in business administration from the Indian Institute of Management (IIM), Ahmedabad, India. She has done short-term courses at the University of Pennsylvania Wharton School of Business and the University of Amsterdam, the Netherlands.   

Online Delivery

We will be using Microsoft Teams to facilitate your participation in the upcoming event. You do not need to have an existing Teams account in order to participate in the broadcast – the course will play in your browser and you will have the option of using a microphone to speak with the room and ask questions, or type any questions in via the chat window and our on-site representative will relay your question to the instructor.

  • Microsoft recommends downloading and installing the Teams app if possible. You may also use the Edge browser or Chrome.
  • You will receive a separate email with a unique link to a personalized landing page which will include links to join all sessions of this event.
  • If you are using a microphone, please ensure that it is muted until such time as you need to ask a question.
  • The remote meeting connection will be open approximately 30 minutes before the start of the course. We encourage you to connect as early as possible in case you experience any unforeseen problems.



Leveraging Data and AI for Predictive Maintenance in Rail Webinar

April 24, 2024 | Online
Individual attendee(s) - $ 0.00 each