Condition-based & predictive maintenance for train and track infrastructure
SmartVision is EKE-Electronics’ condition-based and predictive maintenance platform. It allows users to easily view the health status of their fleet or infrastructure via our browser-based user interface. Our Monitoring as a Service capability gives you the power to automatically monitor your fleet and/or track assets, independently of train manufacturers.
SmartVision condition monitoring brings added value in the form of reduced maintenance costs and/or improved operations. Based on the collected data, SmartVision helps operators or maintainers to understand the status of their fleets and infrastructure so that they can make the right decisions regarding operations and maintenance. Developing failures can be identified at an early stage and the maintenance process can be managed based on the condition of the assets.
SmartVision is an IoT-based fleet monitoring system bringing the power of cloud computing to access sophisticated analytics for the remote collection and analysis of on-board train systems and infrastructure.
Our easy-to-use web-based user interface turns data into actionable information to make informed business decision about when to perform maintenance based on the condition of your fleet and infrastructure. Our system allows you to view the status of your whole fleet and infrastructure in one place.
SmartVision is a modular system that provides flexibility and scalability to grow your condition based maintenance and digitization ambitions over time.
The SmartVision system is future-proofed enabling you to expand it to monitor the condition of critical or "troublesome" components with additional sensors at a later date, if there is a a business case to do so.
Our simple onboard measurement kit monitors the health of switches/points, insulation joints & rails.
Features include:
Developed in collaboration with VR FleetCare, the maintenance unit of the Finnish Railways.
EKE’s expertise in TCMS systems allows you to quickly and easily extract event and time-series data from management/diagnostic systems and sensors to monitor the health of the train and its sub-systems.
Features include:
