Predictive Maintenance for Optimized Manufacturing Solutions in Industry 4.0
In the context of the Zero-X Manufacturing flagship initiative , the DFA is supporting an event aimed at Predictive Maintenance for Industry 4.0 organized by some of the most important current European agents, which are also part of the ForeSee Cluster, to present the best solutions for Predictive Maintenance based on the most advanced technologies such as IoT, Digital Twin, Proactive Computing, Virtual/Augmented Reality and linked data.
ForeSee, a European Cluster of six innovative R&D projects (PROPHESY, PROGRAMS, Z-BRE4K, PRECOM, SERENA, UPTIME) on Predictive Maintenance solutions (PdM), has recently published a White Paper aimed at sharing the lessons learned regarding the solutions to guarantee the intended usage of production equipment and to avoid unplanned downtimes, as well as to provide recommendations for advancing PdM in industrial practice
These projects, which were active from 2017 to 2021, favoured that research and technology partners, together with industrial end-users, worked collaboratively to develop and deploy solutions that advance maintenance practice in industry towards more efficient, sustainable, human-centric and resilient factories
During this webinar, which is especially targeted to industry practitioners, people in academia and policy makers at the local, national and EU levels, representatives of each project will share the most highlighted insights of this Roadmap.
|Introduction to ForeSee: Predictive Maintenance for Industry 4.0 & Introduction to the Digital Factory Alliance
Sotiris Makris, Senior Research Scientist – LMS (Greece)
Oscar Lázaro, Managing Director – Innovalia Association (Spain) | DFA initiative
|Overview of ForeSee White paper
Kosmas Alexopoulos, Research Engineer – LMS (Greece) | SERENA project
|Predictive maintenance within Made in Europe digital transformation pathways
Chris Decubber – EFFRA, the European Factories of the Future Research Association
|Key values towards the development and implementation of PdM technologies for production systems