Predictive Maintenance


Transform from monitor-and-react to predict-and-act

Problem


Unforeseen asset downtime is a high operational risk to manufacturers, requiring deeper insights into asset health that IoT sensors and real-time condition monitoring alone are not able to deliver.

Solution



4Pointx PdM solution uses AI to automate the analysis. By correlating signals from multiple sensors, the solution detects anomalies (aka leading indicators) that usually show up as early as 60 to 90 days prior to the actual failure.

Our building blocks for an effective maintenance paradigm

Build AI

Build AI

Define normal operation for any asset

Our Build AI analyses the full spectrum of sensor data captured for an asset in order to define and build what are considered its normal operating signatures.

  • Automatically selects the important parameters that impact asset behavior
  • Works even for new assets that have limited OEM knowledge on failures
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Predict AI

Predict AI

Detect any unusual behavior with never-before-seen signatures

Our Predict AI scans every incoming asset data to compare and predict any unusual behavior that deviates from normal operating signatures.

  • Adapts to the unique behavior of asset
  • Scales easily to 1000’s of assets
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Explain AI

Explain AI

Augment decision making

Use our Explain AI to know what parameters are causing the unusual behavior, and how much does it deviate from the normal.

  • Assisted root cause analysis
  • Automated error code lookup from digitised user manual
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Learn AI

Learn AI

Continuous improvement

As the SME validates the abnormalities, our Learn AI incrementally learns in the background resulting in lesser and high-fidelity alarms.

  • No more false alarms
  • Man-teach-bot, bot-gets- better phenomenon
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Want to learn more?