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Platform

Predictive Maintenance

AI anomaly detection watches vibration, temperature and current on motors, pumps, fans and conveyors, estimates remaining useful life, and opens a Work Order with the parts before a failure.

A gloved hand fitting a wireless vibration sensor to a motor bearing housing, with a tablet showing a rising anomaly score

Why It Matters

Most breakdowns announce themselves weeks ahead as a small change in vibration or heat. IoTServa learns what normal looks like for each machine, flags the drift early, and turns it into planned work instead of an emergency stop.

  • AI anomaly detection per machine
  • Vibration, temperature and current analytics
  • Remaining useful life estimates
  • Automatic Work Orders with spare parts
  • MTBF, MTTR and availability KPIs

What It Does

AI Anomaly Detection

A model learns the normal pattern of each machine across load and time of day, and scores how far today has drifted from it.

Vibration and Bearing Analytics

Trend overall vibration, bearing temperature and motor current, and spot imbalance, misalignment and bearing wear early.

Remaining Useful Life

Estimate how many days a component has left at the current rate of wear, with the confidence shown.

Work Orders with Parts

Open a Work Order automatically with the likely cause, the steps and the spare parts, and book it into a maintenance window.

Maintenance Calendar

Plan condition-based and time-based maintenance on one calendar, with greasing and inspection reminders by running hours.

Reliability KPIs

Track MTBF, MTTR, availability and maintenance cost per asset, Site and Organization.

See It in the Software

The Node page for Steam Pressure with the latest value, a 24 hour trend chart and its device and register details
Node Detail Each Node shows its latest value, a 24 hour chart, where it lives in the hierarchy and the register it is read from.
The Sensors list showing each device as Healthy with Manage and Replace actions
Device Health Every sensor, meter and drive with its gateway, port, driver and health, and a Replace action that keeps the history.

Screens from the live IoTServa software with a demo company and demo data.

Predictive Maintenance Questions

Which sensors do we need?

Vibration and temperature sensors on bearings, and current from the motor starter or an energy meter. Existing PLC values can be used too.

How long before the AI is useful?

It starts scoring after a few weeks of normal running and improves as it sees more load conditions.

See VYROX Hardware or Read the Protocol Guides

Start with One Site. Prove It on Real Devices.

Tell us which protocols are on site. We will scope a pilot that reads your real devices.

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