ProUPS - Data Analysis-based Predictive Maintenance for Enhanced Availability of UPS
Uninterruptible Power Supplies (UPS’es) protect safety critical infrastructures. Thus, maximizing their reliability is of upmost importance. Despite considerable advances, UPS still experience failures with likely severe consequences.
ProUPS project propose an innovative, comprehensive data-analysis-based predictive maintenance approach aimed at ensuring prompt action prior to a failure of a component, and provision of a more cost-effective maintenance by servicing the device only when required instead of periodically. This way the reliability of a UPS would be significantly improved.
The project is challenging with respect to development of cost-effective prediction strategies for UPS maintenance based on data analysis. This concerns variable selection and extraction of the most indicative features and development of an efficient failure prediction and preventive maintenance methods. Furthermore, the project foresees creation of a novel predictive maintenance service provided to end customers in a form of an add-on solution. In fact, the service boosts reliability of critical power protection while at the same time, reducing the total cost of ownership (TCO) by a reduction of operational and maintenance cost. Indirectly, this will also decrease the cost of downtime of power sensitive equipment and services.
|Head of project at USI||Cesare Alippi|
|ALaRI Personnell|| Slobodan Lukovic
|Starting date||Monday, January 1, 2018|
|Partners involved|| Centiel SA
|Research area|| Ubiquitous and Pervasive Computing
|Project ID||26736.1 PFNM-NM|