As demand, load and energy costs fluctuate, dynamic control settings are vital for sustaining peak machine performance and monitoring asset health crucial for avoiding unplanned downtime. Join Flanders Make experts to explore how AI-driven performance optimization turns variable-demand assets into lean, dependable performers.
You’ll learn to:
- Continuously adapt setpoints and operating modes to changing demand, ensuring every kilowatt and cycle delivers maximum value.
- Monitor real-time health of machinery whose wear patterns don’t follow textbook curves, so you can head off failures before they strike.
- Integrate predictive analytics and control logic to cut Total Cost of Ownership (TCO), blending proven classical techniques with cutting-edge AI.
Through concise case studies – from district heating and battery storage to wind turbines – we’ll give you the decision-making toolkit you need: when to lean on legacy methods, when to unleash machine learning, and how to fuse both for unrivalled productivity, quality and reliability. Walk away with practical guidelines to upgrade your operations and future-proof your assets.
Speakers:
- Jan Helsen, professor at VUB
- Lavinius Ioan Gliga, Research Engineer at Flanders Make
- Bruno Depraetere, Research Fellow at Flanders Make
Flanders Make
