The scope

A monitoring system was required to identify issues before upgrading fleet software, allowing maintenance teams to identify and fix any issues that arise. This needed to integrate with other products in order to verify any results and provide operators and manufacturers with any logs to inform future decisions.

The system was required for daily use and updated in real time while being able to continually analyse and system log files.

The solution

QuEST developed a system that identified any issues, helping users to find the root cause and fix this before the software was released and any upgrades to the fleet were completed.

The development of this system collecting all operational logs from the locomotive installed with the software to allow engineers to understand issues and rectify them to reduce any potential impact that this issue may cause.

The monitoring process was developed by writing scripts in Python with a selenium webdriver, allowing for this information to be used across multiple platforms. The test cases are run on Field Test On Unit (FTON) systems for transport intelligence products in order to verify any results visually.


  • Automated: The monitoring system pulled logs from units with less human interaction, reducing additional work required
  • Effective: The system was designed to analyse data in a short period of time to inform decisions


  • Time-saving: By not only identifying issues but also finding the root cause allowed for solutions to be considered an implemented much more efficiently than before
  • Optimisation: Performance of engineers are optimised by building this into their way of working as an essential tool, rather than an additional step in their process