Digital expertise for better outcome
By model based diagnostics we gather data from around 6.000.000 sensors from turbines worldwide and create 1.500.000 individual digital models out of it. The system flags around 250.000 deviations per year. But which of these positives correspond to real-life faults?
Our algorithms filter out the costly false-positives and insignificant deviations. This drops the count of significant deviations that need to be adressed to aproximately 8.000 site visits a year. In fact: we don’t need to follw false-positives and your average turbine needs to be visited less often.
And the implementation won’t stop there: From service technicians reports to analyzing damage parts, it all feeds back into an ever-learning knowledge base supporting all kinds of digital tools.
By picking up vibrations on turbine components, sensors can lower the risk of slow- and fast-developing damages by early detection, and optimize maintenance strategies – such as automatic turbine shutdown or preventive repair. This helps to save service costs and reduce downtime.
A market leading condition monitoring solution enabling improved detection capabilities on drivetrain components.
With smart use of data and cutting edge machine learning capabilities or condition monitoring solution make early detection up to 3 years in advance on fast and slow developing damages.
Our service can be offered in a passive and active mode to suit your service requirements.