Enhancing operational visibility of potential or emerging risks onboard rolling stock
Relevant RTS critical priority(ies):
Reliable and easy to maintain; Data driven
Situational awareness is key to the smooth delivery of systems and services. Therefore enhanced notification of the condition of these systems can make the difference between successful customer experience and user interaction, or brand deterioration.
Asset Monitoring systems remove the hard, complicated task of processing data and provide a comprehensive picture of what’s going on with operational assets. The patterns identified by the data analysis enable added value to customers by informing them of potential or emerging issues. On rolling stock, sensor driven data systems provide an indication of potential leaks or inefficient fuel usage and increasing temperatures which may have an impact on asset performance and maintenance. Moreover, solutions installed on-board rolling stock can provide operators with insight of the condition of the infrastructure on which they operate and mitigate potential delays by pre-empting repairs.
SensorInsight360 from CGI is a multi-industry and multi-capability system developed to enhance operational visibility. Therefore, providing businesses with the advantage to prompt contingency and reduce operational risk.
Using machine learning and intelligent algorithms, specifically developed to each business case, provides the users of SensorInsight360 with a capability to determine necessary actions required to ensure operational integrity. In addition, it assists with improving maintenance visibility and process flows which in turn reduce operational cost by delivering targeted responses.
SensorInsight360 applications span multiple industry sectors; in the transport arena the technology provides users with visibility of rolling stock and infrastructure performance to complement asset utilisation and highlight where engineering focus can be applied, developing intelligence around asset mobility.
Angel Trains has utilised the integrated Internet of Things (IoT) platform to provide a comprehensive set of data that gives a full picture of the condition of the trains; to analyse data to support coolant monitoring and fuel economy; and to analyse journey times and monitor train performance.
