Shaping Industry 4.0: Pioneering Local AI for Enhanced Proactive Maintenance
Fundamental to Industry 4.0 is the idea of prognostic services, a pivotal factor molding the future landscape of manufacturing. These services wield the power to optimize asset operations by facilitating coordination among higher-level systems and enabling edge systems to adjust controls in real-time based on asset conditions. Deliverable D2.4 ‘Local AI for Proactive Maintenance Support’ delves deep into the profound impact of these services within the AI-PROFICIENT project.
In this deliverable, Kerman Lopez de Calle (TEK), Regis Benzmuller (CONTI), Vasillis Spais (INOS), Marc Anderson (UL), Alaaeddine Chaoub (UL), and Alexandre Voisin (UL), take us on a journey through Work Package 2 (WP2) – Smart Components and Local AI at System Edge. The focal point is the development of edge systems poised to revolutionize asset health prognostics by offering predictive maintenance support. Integrated within assets or controlling them, these systems hold the potential to reshape asset management.
At the heart of Industry 4.0 lies the concept of prognostic services, the cornerstone shaping the future of manufacturing. These services wield the power to optimize asset operations by facilitating coordination among higher-level systems and enabling edge systems to adjust controls in real-time based on asset conditions.
Within this deliverable, the AI-PROFICIENT team aims to share the prognostic models and algorithms that are developed through Task 2.4 – Self-prognostics and Component Operating Condition Estimation. Not only do these models offer insights, but they also present results from public datasets, providing a glimpse into the effectiveness of these cutting-edge methodologies.