Case Study: Global Leader in Delivering a Secure, Transformative Enterprise Cloud Platform achieves predictive valve failure detection with SoftServe

Machine learning increases oil rig Uptime by predicting valve failures

SoftServe worked with Global Leader in Delivering a Secure. Transformative Enterprise Cloud Platform, a global enterprise cloud platform provider, to address an oil and gas challenge: predicting valve failures before they caused costly production stoppages. The customer needed a way to analyze noisy time-series sensor data from industrial equipment and identify whether a poppet valve was likely to fail in the next 10–14 days.

SoftServe built a machine learning model using Python, XGBoost, group-based cross-validation, and GCP data storage to process data from more than 100 sensors and generate daily failure predictions. In a four-week PoC, SoftServe produced nearly 5,000 time-series features per day and achieved a test AUC of 0.62–0.69, helping improve uptime by enabling more proactive maintenance scheduling and reducing unplanned downtime.