ADNOC Completes First Phase of AI Maintenance Project
Phase 1 covers the modeling and monitoring of assets for six ADNOC Group companies. The four phases of the project are expected to be completed by 2022.
The Abu Dhabi National Oil Company (ADNOC) completed the first phase of its large-scale multiyear predictive maintenance project to improve asset efficiency and integrity across its upstream and downstream operations.
Announced in November 2019, the project is being implemented over four phases as part of the company’s digital acceleration program to embed advanced digital technologies across its operations.
Phase 1 covers the modeling and monitoring of 160 turbines, motors, centrifugal pumps, and compressors across six ADNOC Group companies. All phases of the project are expected to be completed by 2022 and will enable monitoring of up to 2,500 critical machines.
Using artificial intelligence (AI) technologies including machine learning and digital twins, the company’s predictive maintenance platform helps with equipment stoppages, reduces unplanned equipment maintenance and downtime, increases reliability and safety, and is expected to deliver maintenance savings up to 20%.
The platform is part of ADNOC’s Panorama Digital Command Center, implemented in partnership with Honeywell and its Forge Asset Performance Management and predictive analytics solutions.
ADNOC’s additional digital transformation initiatives include the smart subsurface data analytics Thamama Subsurface Collaboration Center, use of computer vision technologies, big-data modeling tools for value-chain optimization, and blockchain hydrocarbon accounting.