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Case study

The challenge

Based in Norway and the UK, Aize revolutionizes project execution and operation in heavy-asset industries using software to increase efficiency, improve collaboration and reduce costs. The process of detecting rust on the surfaces of various assets used in energy industries is a widespread challenge that drives up costs and extends the operational efforts manual asset monitoring requires. Getting ahead of maintenance issues, before something breaks down, can potentially save people’s lives and prevent natural disasters. Performing rust detection without the benefit of any technology support can take up to three months. Aize collaborated with Cognizant to develop an innovative solution for the automatic detection of rust anomalies for sub-surface and topside assets installed in the oil and gas and other heavy-asset industries.

Our approach

Working closely with Aize, Cognizant helped develop a novel solution to auto-annotate suspected rust areas using still images extracted from video streams collected during drone flights over land-based storage tanks. Leveraging computer vision tools, the solution trains a machine learning classification using a weak supervision methodology that obtains pixel-level fuzzy labels. This approach alleviates the burden of obtaining hand-labeled data sets, which can be costly or impractical.

Automated detection solution for energy operators

Aize sees the automated detection solution as the first step toward autonomous unmanned inspections using sophisticated machine learning-powered sensors backed by weak supervision. The new platform’s goal is to hold a digital twin, or digital representation, of an oil rig, vessel, gas container or other heavy asset typical of those in use by Aize’s clients. Engineers use the platform to work with an asset’s digital representation and plan detailed inspections in advance of location visits to save potentially 50% of the effort it typically takes to conduct an inspection. Once on location, staff follow the plan and record everything in the system, capturing a history of the development of issues on a particular asset. The solution helps energy operators dramatically reduce the cost of rust detection and the cycle time of performing a quality inspection while improving the quality and integrity of operational work processes.

More than 50% reduction

in effort required for integrity inspections

Automated inspections

of oil and gas assets for surface corrosion

Reduced

number of resources needed for inspections