App Monitors Industrial Equipment Condition And Performance

Arundo Analytics’ Condition & Performance Monitoring (CPM) application for industrial equipment application incorporates several best-in-class technologies. These include:

  • Via Arundo’s Edge Agent software, field-installed industrial equipment intelligently streams its sensor data for real-time analysis.
  • Via the Arundo CPM dashboard, configurable panels allow customers to visualize streaming equipment data, key performance indicators and data-driven analytics. For the smart pumping system, this includes:
  • Streaming measurement data directly from the equipment, such as flow rate, differential pressure, temperature, speed and power  
  • Streaming edge calculations based on these sensors, such as pump efficiency and pump head
  • Machine learning analytics such as runtime efficiency and time in high vibration  

Arundo CPM also enables condition-based alerts to specific users via SMS or email and enables anomaly detection for predictive equipment analytics.

The anomaly detection approach is based on clustering techniques that learn from historical data and build a complex view of system behavior across groups of sensors. The trained model can then raise alarms when unseen or failure mode behaviors arise in the system.

Sponsored by Infosys

Infosys positioned as a Leader in Gartner Magic Quadrant for IT Services for Communications Service Providers, Worldwide 2020

The Gartner Magic Quadrant evaluated 12 vendors and Infosys was recognized for its completeness of vision and ability to execute.
Infosys leverages its global partner ecosystem, CSP-dedicated studio, design tools, and 5G Living Labs to boost service delivery. Innovative solutions such as the ‘Infosys Cortex2’ are driving business value for CSPs.

 

This anomaly detection approach accounts for multiple complex operational modes. It also enables the combination of multiple sensors into a single measure of the health of the system (a “virtual sensor”). For more information, pay a visit to Arundo Analytics.

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