The 3 steps below show how data is collected, collated, analysed and presented
The sensors capture ultrasonic and vibration data from the turbines in the machine.
Each sensor is weather-sealed with a 2 year battery life for minimal maintenance.
The Gateway continuously gathers and catalogues the data collected from the array of sensors.
The data is collected using wifi and can be up to 200m away from the Gateway
The Portal displays each machine and its computed operational status.
The XTRA Cloud accurately identifies problems such as lubrication and debri issues so that machines are repaired quickly and downtime is reduced
Machine learning aid's predictive maintenance by analyzing historical data from machines, identifying patterns and anomalies, and predicting when maintenance is likely to be needed in the future. Combined with the XTRA Portal, maintenance schedules are optimized, reducing downtime and extending the life of equipment.
Our machine learning model is trained on 7,000,000+ hours of machine monitoring. Allowing it to not only identify issues but also accuractely diagnose the specific problems. This allows engineering teams to quickly effectuate repairs and minimise downtime.
Machine with and without XTRA Sensors installed
Get in touch with one of our experts and learn how much you could save by implementing our predictive maintenance system.
