Safe, reliable rail transport is the backbone of our nation’s economy, contributing tens of billions of dollars to US gross domestic product (GDP) annually. Optimizing the performance and availability of existing legacy assets and newer, technologically advanced ones is an increasingly complex and costly challenge, though.

The components and data buses onboard these locomotives generate enormous volumes of data that can enable faster, more precise maintenance outcomes, but existing solutions can’t capture or analyze this valuable data.

With complete observability of all onboard data, owners/operators get the insights and context they need to make real-time decisions that help improve the safety and reliability of their most critical, expensive, and long-lasting assets.

Key takeaways:

→ Understand the importance of predictive maintenance and how it can enhance your most critical assets' operational efficiency and availability.

→ Gain insights into the challenges in implementing predictive maintenance, including capturing and processing large volumes of disparate data from multiple protocols and sources.

→ Discover the importance of full-take data capture in predictive maintenance and how it ensures that all frames are recorded so that appropriate action can be taken.

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