PETRONAS
PETRONAS reduces unplanned shutdowns with AVEVA PI System and Predictive Analytics
Petroliam Nasional Berhad (PETRONAS), an integrated Malaysian multinational oil and gas company, produces 2.4 million barrels of oil equivalent per day. This scale created data silos and high-value losses due to undetected failures on rotating equipment, with incomplete visibility and slow reaction times caused by dispersed operations. Deploying AVEVA PI System and AVEVA Predictive Analytics made it possible to automate knowledge of machine behavior and immediately alert experts to anomalies through a cloud-based early warning system. The benefits are considerable: $33 million saved since 2019 through reduced unplanned downtime, with 51 warnings issued, 12 of them high-risk, representing a 20x return on investment. Asset utilization is up 0.1% per plant, and multidisciplinary collaboration is speeding up event response times.
Testimonials
FAQ
How did AVEVA PI System and Predictive Analytics save PETRONAS $33 million?
PETRONAS, which produces 2.4 million barrels of oil equivalent per day, deployed AVEVA PI System and AVEVA Predictive Analytics to automate knowledge of how its rotating equipment operates. The system generated 51 early warnings, 12 of them high-risk, helping to avoid major unplanned shutdowns. The result: $33 million saved since 2019, a 20-fold return on investment. Predictive maintenance turns real-time data into tangible financial gains.
Why is breaking down data silos critical in the oil sector?
The sheer scale of PETRONAS created data silos and incomplete visibility, with experts spread across several sites and slow reaction times. AVEVA PI System centralizes operational data in a single repository accessible to all subject-matter experts, wherever they are. This unification speeds up multidisciplinary collaboration, improves response times to events and unlocks the hidden value of data. It is a pillar of digital transformation in oil and gas.
How does AVEVA Predictive Analytics detect failures in rotating equipment?
AVEVA Predictive Analytics applies machine learning models to the operating signatures of rotating equipment (compressors, turbines, pumps). The solution detects subtle deviations from normal behavior and issues early warnings, several weeks before failure. At PETRONAS, this detection generated 51 warnings, 12 of them high-risk, preventing high-value losses on critical onshore and offshore assets. Predictive analytics thus becomes a major lever for industrial reliability.
What operational benefits does AVEVA bring to an oil and gas producer?
In addition to the $33 million saved, PETRONAS increased asset utilization by 0.1% per plant, including reliability and overall equipment effectiveness. Response times to events are faster thanks to stronger multidisciplinary collaboration. The program's 20x ROI demonstrates the power of an approach combining real-time data management (PI System) and advanced predictive analytics (Predictive Analytics). It is a textbook case for oil and gas majors undergoing transformation.
How is a cloud-based early warning system transforming maintenance in the oil and gas sector?
AVEVA's cloud-based early warning allows PETRONAS to instantly notify subject-matter experts, wherever they are, as soon as an anomaly is detected on rotating equipment. This cloud architecture breaks the geographic isolation of offshore and onshore sites, speeds up decision-making and democratizes access to critical data. Maintenance moves from a reactive, scheduled approach to a condition-based approach driven by the actual condition of assets, generating major operational and financial gains.