Can the railway industry utilize data to its full potential?

Technology is increasing at an exponential rate. By 2020, 50 billion devices are expected to be connected through the Internet of Things, generating 44 trillion GB of data1. This data needs to be utilized to create a more efficient and reliable railway that provides faster, lower risk, cost-effective and reliable service for its users.

As a rail systems specialist, I have worked for numerous railway companies over diverse geographical locations in extremely different conditions. From a freight rail company in Queensland, Australia to a metro extension project in Edmonton, Alberta, I’ve worked with diverse weather conditions, schedule frequencies and railway systems designs.

I have also had the unique experience of working in numerous different railway departments including rolling stock, signalling, systems, governance, construction, operations, and maintenance. These experiences have provided me with great insight into the sometimes-conflicting requirements of different departments under one company. For example:

  • Operations’ objective is to maximize the trains’ time on tracks (utilization).
  • Maintenance’s purpose is to provide routine inspections and repairs, which requires removing equipment from operation.
  • Engineering’s ambition is to provide more equipment to measure, analyze and automate. To deliver this requires equipment to be removed from operation and/or more equipment to be installed and therefore maintained.

Since these different departmental requirements sometimes conflict and compete, cross-department communication and data sharing is essential.

Mind the Gap

Data utilization and sharing is a critical gap when it comes to maximizing efficiency in the rail industry. Our most recent whitepaper, “Can the railway industry utilize data to its full potential?” describes how the railway can improve its utilization of data at a company, industrial and global level. The whitepaper describes how to improve data management by treating data like all other railway assets and managing it throughout its lifecycle.

The paper also provides some examples of how to improve data acquisition and data management. It discusses the application of data analytics in the maintenance field, including condition monitoring and predictive maintenance. It has been estimated that this can reduce railway maintenance costs by 25 per cent while improving service and increasing asset availability. This can result in the railway challenging its maintenance philosophies and the status quo.

A Future Ready railway will be prepared to use all types of data to improve reliability and service, and to reduce risk and increase innovation.

Can the Railway Industry Utilize Data to its Full Potential?

Read the full whitepaper

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