PreCoM 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 by at least 10%.
The platform includes 4 modules: a data acquisition module leveraging external sensors and sensors directly embedded in the machine tool components; an artificial intelligence module able to track individual health condition and supporting a large range of assets and dynamic operating conditions; a secure integration module connecting the platform to production planning and maintenance systems, self-healing and self-learning capabilities; and a human interface module including production dashboards and augmented reality interfaces.
PRODUCT DEVELOPED IN THE FRAMEWORK OF A FUNDED PROJECT
Project Acronym and Title: PreCoM – Predictive Cognitive Maintenance Decision Support System
Funding source: H2020-IND-CE-2016-17 : Industry 2020 in the Circular Economy696174
Grant Agreement Number or Funding reference: G.A. 768575