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Bayesian Methods for Preventive Maintenance

| 2018:484 | Bahri Uzunoğlu
The context of this research is about the simple idea of assessing the optimal time for preventive maintenance based on available information to us from SCADA data of wind turbines. The approach is quantitative, measurable and repeatable. As a result, the contexts of these results belong in reliability and safety engineering and preventive maintenance of wind turbines.
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Maintenance of wind farms can be systematically categorized as preventive, corrective, and condition based maintenance. Most of the major the operation and maintenance costs are dominated by corrective maintenance. To reduce these costs it is necessary to lower the amount of corrective maintenance uncertainty.

To reduce the operation and maintenance costs it is necessary to lower the amount of corrective maintenance by shifting some parts of strategy to preventive maintenance which is achieved in this project by employing Bayesian adaptive approaches that employs newly arrived data to update predictions. The approach has simplicity in its implementation for any engineer with statistics background while its implementation is quick, simple and cheap in comparison to methods that are dependent on model of the specific technology.

Bayesian Methods for Preventive Maintenance | Energiforsk