Webinar Series: Energy Intelligence Academy

In many ventilation and air handling systems (AHUs), surprisingly little is known in day-to-day operation about how much air is actually flowing through the system and whether the configured values still match the actual demand. Before a system can be optimized effectively, it is essential to understand what is really happening – where air is being moved, how much is actually needed, and where energy is being wasted. Typical situations include:

• A production hall has been modified, machines have been relocated, or areas are now used differently – but the airflow rates are still set to the same values as they were years ago.  
• Fans continuously move more air than necessary because setpoints have never been reviewed.  
• Supply and exhaust air are not properly balanced. This creates pressure differences, causes uncontrolled outdoor air infiltration, and wastes costly heating or cooling energy.
• Airflow values may be available in the building management system, but no one knows exactly how reliable those values actually are.
• Operators see high electricity consumption at the end of the month but cannot clearly identify which part of the air handling system is responsible.

Many ventilation systems today are still operated with fixed setpoints and static operating strategies, even though production, utilization, and outdoor temperatures are constantly changing. This results in unnecessary energy consumption and untapped optimization potential. In our talk, we explain how AI-based operational optimization continuously adapts ventilation systems to actual demand. etaONE® uses existing operational data to proactively optimize air volumes, operating times, and ventilation and cooling, without additional hardware or changes to existing infrastructure. Real-world examples from industry illustrate the potential:

• At the Stellantis paint shop at the Opel Rüsselsheim plant, energy consumption for ventilation was reduced by more than 60% through intelligent operational optimization.
• Under critical temperature conditions, predictive control enables improved thermal preparation of production areas and reduces the risk of heat-related disruptions.

Participants will learn how they can operate their existing ventilation systems more efficiently and reliably using AI, and what concrete potential intelligent operational management can unlock in their own facilities.