The Abyss Fabric technology has revolutionised the identification of condition visualisation, fabric maintenance planning and prioritisation, allowing you to work from a predictive maintenance mode, significantly saving in both time and costs. It has proved to reduce millions of dollars of maintenance costs, and save significantly (up to 25%) from optimising maintenance operations, shifting from a reactive and calendar-based inspection to proactive and risk-based inspections.
Anadarko engaged Abyss in a pilot to address their growing concerns of onset of corrosion on offshore platforms and large OPEX to manage them. Abyss engaged due to its core capabilities in data analytics, computer vision and machine learning and designed an analytics tool, AbyssFabric around these capabilities, which comprehensively and actively processes 1000s of images to automatically identify corrosion and classify its severity.
The automated analytics approach consistently and objectively achieved >95% detection performance, as vetted through some blind tests orchestrated during the pilot. The algorithm was then deployed on terabytes of data on the platform, to automatically build a rich corrosion database. This enabled the operators to focus their remediation efforts on high-risk areas immediately. Post pilot, Anadarko has engaged with Abyss to scale AbyssFabric to two large offshore platforms. In the scaled version, AbyssFabric not only detects corrosion but also tags it to individual equipment IDs, thereby building a comprehensive equipment based corrosion database.
The technology is set to transform how Fabric Maintenance is done.