Predictive Maintenance AI
Xylo-Zero
Overview
Xylo-Zero is a predictive-maintenance AI solution that detects small equipment changes at the site.
It analyzes acoustic, vibration, temperature, and PLC/Drive data together and notifies operators of anomaly events and inspection priorities.
Field challenges
Equipment issues first appear as changes in sound, vibration, temperature, and operating state. When that data is stored in separate systems, actual anomalies are harder to identify.
How it works
A field device collects condition signals and reads PLC/Drive operating data. The system uses operating state to select valid windows, detects anomalies at the edge, and sends events to dashboards and alerts.
- Signals
- Acoustic, vibration, temperature, current and operating signals, PLC/Drive data
- Deployment
- Field edge device with dashboards, alerts, and maintenance-system integration
Key capabilities
- Acoustic, vibration, and temperature collection
- PLC/Drive operating-data integration
- Analysis window selection by operating state
- Edge anomaly-event detection
- Inspection-priority and action support
- Control and maintenance-system integration
Deployment goals
- Early anomaly detection
- Inspection priorities
- Reduced risk of unplanned stoppages and safety incidents
Frequently asked questions
- What equipment can we start with?
- We assess equipment with measurable condition signals, including motors, bearings, gearboxes, conveyors, cranes, pumps, fans, and compressors.
- Do we need to replace the existing PLC or control system?
- No. We review field interfaces and connect the solution to existing PLC/Drive data, dashboards, alerts, and maintenance workflows.