<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=239686353408221&amp;ev=PageView&amp;noscript=1">
Real-time monitoring of asset health reduced the frequency of routine maintenance by 75%.
The system immediately alerted the user to provide a likelihood of compressor failure.

A major oil company sought to improve effectiveness of its equipment maintenance spend. Compressor failure accounted for a significant share of the company’s lost production, resulting in a strict routine maintenance policy on all gas compressors. Non-productive time dropped significantly, but planned maintenance events rose significantly. Management sought to implement a data-driven, condition-based maintenance approach where preventative maintenance is prioritized based on real-time data streaming from the equipment. 

A cluster-based approach was used to aggregate multiple individual signals and eliminate white noise, allowing the company to prioritize critical repairs.

Arundo’s team of data scientists worked with the customer to implement a condition-based monitoring solution for gas compressors. Arundo developed a machine-learning model to map real-time hydrocarbon readings against a standardized set of operating ranges and deployed the model within the Arundo platform. Given the variance of individual signals, a cluster-based approach was used to aggregate multiple individual signals and eliminate white noise. When sensors detected a deviation from the predicted operating range, the system immediately alerted the user to potentially abnormal equipment behavior. Prior to implementation in the production environment, the system was validated against anonymized historical data. The system successfully identified anomalies related to pending failure at the sensor level several months before the existing control system raised any alarms.

95% Accuracy Rate
Model predicted equipment failure with a 95% accuracy rate, far superior to status quo forecasts.
After a short pilot phase, the client unveiled the condition-based monitoring platform across offshore sites in order to implement real-time monitoring of asset health.
Leading Major Oil Company
Oil & Gas
Efficiently scheduling preventive maintenance
Condition-based monitoring solution for gas compressors
Successfully prioritized critical repairs
Want to see how Arundo’s software could help improve maintenance costs for your oil and gas company?