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AI-Powered Anomaly Detection explained
AI-Powered Anomaly Detection explained
Nick avatar
Written by Nick
Updated over a week ago

With Anomaly Detection, MaintainX immediately alerts technicians if they enter a value that appears to be an anomaly into a Procedure field. An AI model detects anomalies in repeating Work Order chains based on historical data from previous inspections. This helps organizations to minimize downtime by catching and flagging early signs of fault with a machine. It also helps to prevent data entry mistakes and improve the quality and precision of the data going into MaintainX.

Minimize downtime with AI-Powered Anomaly Detection.

Anomaly Detection detects faults using historical data – before they take down your equipment.

  • Predict faults: Spot machine faults early to address them before equipment goes offline.

  • Eliminate errors: Improve your data quality by flagging values that might have been entered by mistake.

Catch anomalies in Procedure fields instantly.

Technicians see right away when a Procedure input is:

  • Out of the expected range

  • Contradicts a trend (e.g., was decreasing, now increasing)

  • Usually has a decimal and now doesn’t

Catch anomalies in Procedure fields instantly.

The technician now has three options:

  • Correct the value if it was a mistake

  • Confirm the anomaly as a flag

  • Tell the system that it’s not an anomaly

Make sure follow-up action is taken

When anomalies are confirmed:

  • A ‘flag’ is recorded on the WO

  • The technician is prompted to create a corrective action

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