Performance evaluation of technical support
News - 2 June 2019
VALEMO implements two new indicators to evaluate performance of technical support.
The performance of an asset is directly related to the efficiency of its technical support. This can vary according to many parameters (distance from bases/installations, availability of spare parts, resources, etc.). It is the operator’s role to monitor the performance of the technical support.
In order to ensure consistent and recurring monitoring of this performance, VALEMO deployed 2 indicators in 2018 on a portion of its operating assets:
- TI (Intervention Time): Time between the occurrence of the failure and the arrival on site of the maintenance team
- TR (Resolution Time): Time between the beginning of the intervention and the restart of the turbine
The objective is to measure the efficiency of technical support both on their reactivity to intervene on site and their ability to repair the machine quickly.
These indicators allow for multiple analyses:
- Monitoring of the evolution over time: Good service technique one day, good service technique always? Not necessarily… But the reverse is also true. It is therefore essential to measure the evolution of these indicators over time, whether to measure maintenance, degradation or performance improvement.The graph below shows the evolution of the intervention time month by month, the number of interventions as well as the average intervention time for a given farm:
- Comparison of support technique with each other: comparing market players is essential to provide a global vision, a reference framework on which to base. This type of information can become predominant in the final choice of a turbine manufacturer during the development phase as well as during recurring points with the latter.
VALEMO currently operates 530 MW of wind power, a figure that will rise to 630 MW in 2019.
We work with the following turbine manufacturers :
- GE / Alstom
We have deployed these indicators across most of our farms. This involves automating the calculation of these indicators from the beginning of asset operations using powerful data processing tools such as PowerBI.