Name: PreCoM podcast - Episode 03 - Predictive maintenance with sparse failure data by PreCoM project
Duration: 7 min 1 s
Description: In this episode, Prof. Jacobo de Uña Álvarez from ITMATI and University of Vigo explains how we can make predictive maintenance work, even when only sparse failure data is available!

In this episode, Prof. Jacobo de Uña Álvarez from ITMATI and University of Vigo explains how we can make predictive maintenance work, even when only sparse failure data is available!

PreCoM podcast - Episode 03 - Predictive maintenance with sparse failure data

The project will deploy and test a predictive cognitive maintenance decision-support system able to identify and localize damage, assess damage severity, predict damage evolution, assess remaining asset life, reduce the probability of false alarms, provide more accurate failure detection, issue notices to conduct preventive maintenance actions and ultimately increase in-service efficiency of machines.

The consortium includes 3 end-user factories, 3 machine-tool suppliers, 1 leading component supplier, 4 innovative SMEs, 3 research organizations and 3 academic institutions.

Checkout our current work at:
https://www.precom-project.eu/

Follow us on twitter
https://twitter.com/PreCoM_Project

and LinkedIn
https://www.linkedin.com/in/precomeu2020/

This project has received funding from the European
Union’s Horizon 2020 research and innovation programme
under grant agreement No. 768575.