Ventilation system

The most worthwhile data to monitor is energy consumption, volume flows, air quality, filter differential pressure and the temperature and vibration of the motors. Many technical faults announce themselves through higher temperatures, increased power consumption or unusual vibration. In the Siemens example, the values feed into a digital twin that also reveals oscillating behaviour across the system, for example when units keep switching on and off because of incorrect set values.

Maintenance becomes predictive when the condition of filters and drives is measured continuously rather than at fixed intervals. The differential pressure upstream and downstream of the filter shows when a replacement is due. Long-term data in the cloud makes the quality of different air filters comparable and allows maintenance to be scheduled during production downtime. Magna used to measure the bearings of its ventilation units manually every six months; today sensors do it continuously.

Demand controlled ventilation regulates the air volume according to measured values rather than fixed times. In WAGO's logistics centre in Sondershausen, air quality sensors, presence detectors and volume flow controllers capture conditions on site, and the building automation uses this data to control the ventilation systems with heat recovery. The GELSENWASSER-Monitor shows why this matters: initial analyses found excess consumption in schools because a ventilation system had not been adjusted to actual usage.

Failures can be avoided when the motors and bearings of ventilation units are monitored continuously and faults are reported automatically. In its paint shops, Magna records motor vibration, imbalance and bearing condition, and alarms go to smartphones when limit values are exceeded. In the Siemens example, faulty ventilation motors used to be reported mostly by phone. Today, a monitoring system connects all building services to the cloud and automatically creates a ticket for every event.