The Abu Dhabi National Oil Company (ADNOC) announced that it has completed the first phase of its large-scale multiyear predictive maintenance project, which aims to maximize asset efficiency and integrity across its upstream and downstream operations.
ADNOC says its predictive maintenance platform uses artificial intelligence (AI) technologies such as machine learning and digital twins to help predict equipment stoppages, reduce unplanned equipment maintenance and downtime, and increase reliability and safety. The company said it expects use of the platform to result in maintenance savings of up to 20%.
The predictive maintenance project, which was announced in November 2019, is being implemented over four phases.
“We are already seeing significant operational benefits and cost savings,” said Abdulmunim Saif Al Kindy, ADNOC’s executive director for people, technology and corporate support directorate, “and we intend to continue to embrace the power of digitalization and AI as we further enhance performance and drive value across our business.”
ADNOC’s predictive maintenance project is part of the company’s digital acceleration program, which focuses on embedding advanced digital technologies across the company’s operations.
The first phase of the project covers the modeling and monitoring of 160 major turbines, motors, centrifugal pumps, and compressors across six ADNOC Group companies. The company said it expects all four phases of the project to be completed by 2022, claiming the project will enable the central monitoring of up to 2,500 critical machines across all ADNOC Group companies.
The predictive maintenance platform is being implemented in partnership with Honeywell.