Abu Dhabi National Oil Co. (ADNOC) has completed the first phase of its large-scale multi-year predictive maintenance project to maximize asset efficiency and integrity across its upstream and downstream operations. Phase 1 covered modeling and monitoring of 160 major turbines, motors, centrifugal pumps, and compressors across six ADNOC Group companies.
The predictive maintenance project, which was announced in November 2019, is being implemented over four phases and is one of the largest in the oil and gas industry. All four phases of the project are expected to be complete by 2022 and the project will enable the central monitoring of up to 2,500 critical machines across all group companies, ADNOC said.
Utilizing artificial intelligence (AI) technologies such as machine learning and digital twins, ADNOC’s predictive maintenance platform helps predict equipment stoppages, reduce unplanned equipment maintenance and downtime, increase reliability and safety, and the company expects it to deliver maintenance cost savings of up to 20%.
ADNOC’s predictive maintenance project is part of the company’s digital acceleration program, which focuses on embedding advanced digital technologies across its operations. Other digital initiatives include its AI and big data-driven Panorama Digital Command Center; its smart subsurface data analytics Thamama Subsurface Collaboration Center; and its use of computer vision technologies, big data modeling tools for value chain optimization, and blockchain for hydrocarbon accounting.
The predictive maintenance platform is an integral part of ADNOC’s Panorama Digital Command Center at its headquarters and is implemented in partnership with Honeywell, using Honeywell Asset Performance Management and predictive analytics enterprise solutions.
