Most of the production losses incurred during the planned maintenance activities can be brough down substantially. AlgoAPM® has embedded energy forecasting functionality by carefully planning a maintenance activity around the forecast.
Together with the expected energy inputs, the inputs from turbine and EBoP Scada, the APM measures all sources of lost production and objective is to reduce the losses and increase production.
Together with the expected energy inputs, the inputs from turbine and EBoP Scada, the APM measures all sources of lost production and objective is to reduce the losses and increase production.
The APM has investigation tools that are capable of detecting repetitive faults. The tools also make it clear whether the fault is on a specific turbine or whether all turbines are impacted with a serial defect
There are several predictive maintenance algorithms that provide action recommendations; e.g blade wear, soiling and icing e.t.c usually a couple of weeks in advance. If timely actions are taken, the incidents of turbine breakdowns are reduced substantially.
There are several predictive maintenance algorithms that provide action recommendations; e.g blade wear, soiling and icing e.t.c usually a couple of weeks in advance. If timely actions are taken, the incidents of turbine breakdowns are reduced substantially.
