Case studies
Manufacturing HVAC · Industry 5.0 & IoT
Multivariate anomaly detection across an HVAC fleet
The client
An international HVAC-systems manufacturer, with dozens of machines installed at geographically distributed end-customers. With Statwolf’s Anomaly Detection solution it moved from reactive to proactive monitoring, identifying emerging issues in real time.
The challenge
- Unable to identify degradation and malfunctions in time, with unexpected downtime.
- Fixed-threshold monitoring: false alarms and unusual behaviour not captured.
- Root-cause diagnosis difficult, resolutions slow, costs high.
- Adding new machines to the monitored fleet too onerous.
The solution
- Unsupervised multivariate models per machine, continuously analysing telemetry.
- Visualisation tools to make alerts immediately understandable.
- Explainable AI that clarifies the causes of anomalies and speeds up diagnosis.
- An MLOps architecture: models that update and scale transparently with the fleet.
The results
proactive
interventions before critical downtime
−false alarms
more team trust in alerts
scalable
new machines with minimal effort
