Arundo Analytics Launches Industrial Equipment Condition and Performance Monitoring Application

With Fuglesangs AS, a pump equipment manufacturer and supplier, Arundo recently demonstrated a smart pumping system built on Arundo CPM at an event in Oslo for the launch of Subsea Valley Norwegian Centre of Expertise (NCE) Energy Technology.
By IOT Journal
Feb 12, 2018

PRESS RELEASE:

Arundo Analytics, a software company enabling advanced analytics in heavy industry, has announced the Arundo Condition & Performance Monitoring application (CPM) for industrial equipment. With Fuglesangs AS, a pump equipment manufacturer and supplier, Arundo recently demonstrated a smart pumping system built on Arundo CPM at an event in Oslo for the launch of Subsea Valley Norwegian Centre of Expertise (NCE) Energy Technology. Arundo and Fuglesangs showed the first end-to-end system for real-time pumping analytics in the cloud, based on the latest advances in sensor technology, edge computing, cloud software and machine learning.

Arundo's CPM application was at the core of the demonstration, which took place in front of an audience of over 300 attendees from leading energy and technology companies, as well as members of the Norwegian government. Terje Søviknes, Minister of Petroleum and Energy, spoke at the event.

Arundo's CPM application incorporates several best-in-class technologies:
• 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; and 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.

Finally, Arundo CPM enables anomaly detection for predictive equipment analytics. Arundo's 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. 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").

Impaired operations or failure of pumps may have significant consequences for operators. However, prior to this system, the industry had no cloud-based solution that integrates machine learning and advanced data science for the early identification of operating anomalies.

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