Improvement of the remote expert system based on software Otea.
ITMATI, Universidades de Vigo
Energy and Environment
Development of a system that, through the platform of remote management of facilities OTEA, is able to predict maintenance incidents through the interpretation of the data monitored, and can apply rules that improve the efficiency of the system and extend the life of the equipment.
Challenges and goals
- To multiply the value of the OTEA system by maximizing the efficiency of the facilities and minimizing the basic management resources.
- To deploy a predictive tool which enables to detect maintenance incidents before they happen.
Mathematical and computational methods
- Neural Networks.
- Random Forest.
- Quantile regression.
- Generalized additive models (GAM).
Results and Benefits
The implemented tool created applies mathematical and statistical algorithms in order to get a reliable predictive maintenance, improving the efficiency of the current system, extending the equipment life cycle and allowing a smarter management of resources.
In addition, an increment of the OTEA platform value has been obtained, and offers a more complete service to the clients whereas the maintenance cost are reduced.