1. Connect
Read-only connections to your control and business systems. No new hardware required when the signals already exist.
Predictive maintenance
Predictive maintenance software for automated plants
Atherya learns how each machine actually behaves, spots the drift before the stop, and hands your team a maintenance window that fits the production plan. It plugs into SAP, WMS, CMMS, SCADA and PLCs without replacing any of them.
How it works
2. Learn
A behavioural model per asset, not a generic threshold. Two identical machines from the same vendor get two different baselines.
3. Warn
Early failure detection and anomaly detection with the evidence attached: which signal moved, when, and against which baseline.
4. Schedule
The recommended intervention is placed where it costs the least production, with your sign-off before anything changes.
Why it is different
It explains itself
Every alert carries the root cause analysis behind it, so maintenance can argue with the model instead of trusting it blindly.
It knows the plan
Maintenance recommendations are scheduled against real orders, shifts and bottlenecks, not against a calendar.
It scales across sites
Built for highly automated environments, from a single line to a multi-site pharmaceutical logistics operation.
Atherya vs. sensor-first platforms
Atherya
Sensor-first platforms
Integration approach
Read-only connectors to SAP, WMS, CMMS, SCADA and PLCs. No rip-and-replace.
Often needs new gateways, historians or middleware before it can start.
Predictive model
One behavioural model per asset, built from your existing signals.
Generic thresholds or fleet averages that miss the specific machine.
Action / scheduling
Maintenance windows ranked against real production orders and shifts.
Alerts go to a calendar or inbox; someone still decides when.
Explainability
Every alert shows the signal, baseline and evidence.
Black-box scores with little context for the plant floor.
Hardware / data-collection layerNo extra hardware
Uses the sensors and PLCs you already run. No extra hardware required.
Frequently requires new sensors, edge devices or data historians.
Questions we get asked
- How does predictive maintenance software reduce equipment failures?
- It reads the signals your machines already produce (PLC, SCADA, sensors, historical work orders), learns the normal behaviour of each asset and flags the drift that precedes a failure, so the intervention is planned instead of forced.
- How do you evaluate predictive maintenance software for a manufacturing plant?
- Check three things: whether it connects to the systems you already run without replacing them, whether it explains why it raised an alert, and whether it turns the alert into a schedulable action that fits your production plan.
- Does it replace our CMMS or ERP?
- No. Atherya sits on top of SAP, WMS, CMMS, SCADA and PLCs and sends its recommendations back into those systems. No rip-and-replace.
- What software works for predictive maintenance with sensors?
- Anything that can ingest high-frequency sensor streams alongside slow business data. Atherya combines vibration, temperature, current and cycle data with maintenance history so the model reasons on the same asset from both sides.
Start with your own data
Bring one line, one month of history and the failures that hurt most. We show what the model finds before you commit to anything.
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