We remotely monitor rolling stock to determine the condition and predict maintenance.
On-board data capture and monitoring contributes to the optimal availability of rolling stock. We equip rolling stock (locomotives, trains, trams, metros) with sensors. The sensors record the behaviour of assets that are susceptible to maintenance, such as traction systems, motors, air conditioning, lighting and doors. By analysing the data, we help our customers have their vehicles operate as reliably as possible.
Data helps explain and predict defects and wear. Instead of waiting for a defect to result in a failure, maintenance companies can preventively maintain components like batteries and diesel generators. This results in improved availability and a maximum return on assets. With double the benefits: economic benefit for the operator and less delay for the passenger.
An increasing number of sources is used to capture the data. Sensors recording the current condition of the assets are the key source. Combining non-conformance alerts with GPS data, improves the insight. By regularly reading and analysing this data, we can predict and schedule fixed maintenance cycles.
"The collection, analysis and use of data is consistent with the trend of developing smart maintenance"
The collection, analysis and use of data is consistent with the trend of developing smart maintenance. Predictive maintenance makes workshops better equipped for incoming rolling stock. The maintenance process can be designed more efficiently, which saves on costs. Rolling stock can be used more effectively, which increases its availability.