The project will deploy and test a predictive cognitive maintenance decision-support system able to identify and localize damage, to assess damage severity, to predict damage evolution, to assess remaining asset life, to reduce the probability of false alarms, to provide more accurate failure detection, to issue notices to conduct preventive maintenance actions, and ultimately to increase in-service efficiency of machines.
Increase availability and
maintainability by 15%
Reaching 30% of time spent on predictive maintenance
accidents by 30%
Reduce energy consumption by 6-10%
Reduce raw material consumption by 7-15%