Reducing risk
As industrial operators intensify efforts to improve asset integrity and reduce unplanned downtime, corrosion under insulation (CUI) remains one of the most persistent challenges facing the energy and process sectors
Against this backdrop, an expanding collaboration between Aramco and CorrosionRadar highlights a growing shift toward predictive, data-driven integrity management strategies.
CONTINUOUS REMOTE MONITORING
Aramco has announced the deployment of CorrosionRADAR’s predictive CUI monitoring solution across a major greenfield development in Saudi Arabia. Unlike traditional inspection programmes that rely heavily on periodic manual inspection and insulation removal, the system is designed to provide continuous, remote monitoring of insulated assets from the earliest stages of plant operation.
The deployment reflects a wider industry transition from reactive maintenance models to condition-based monitoring supported by AI-enabled analytics. According to the project team, embedding the monitoring infrastructure during the design and construction phase is expected to deliver both short- and long-term benefits, including reduced inspection scope, improved maintenance planning and extended asset life.
A representative from the Aramco Greenfield project management team says: “With Corrosion Under Insulation accounting for significant pipeline maintenance costs in some of our facilities, it poses a serious threat to the future success of this development. To address this, we are working closely with CorrosionRADAR to deploy its predictive CUI monitoring solution throughout the Greenfield project from day one. This approach will ensure we achieve continuous CUI visibility, improved asset integrity, and, most importantly, greater operational efficiency.”
ADDRESSING CORROSION UNDER INSULATION
CUI remains a major operational risk because corrosion can progress undetected beneath insulation systems for extended periods. In hydrocarbon processing environments, fluctuating temperatures, moisture ingress and chloride contamination create conditions that accelerate external corrosion on insulated carbon steel assets. The consequence is often costly shutdowns, leaks or structural degradation identified only during scheduled turnarounds.
CorrosionRadar’s system addresses this challenge using permanently installed sensors capable of detecting moisture ingress and monitoring corrosivity beneath insulation without requiring insulation removal. The company’s long-range monitoring architecture combines corrosion and moisture sensors with wireless data transmission and cloud-based analytics platforms.
The monitoring solution supports operating temperatures ranging from approximately -90°C to 260°C in standard deployments, with some sensor configurations rated up to 300°C. The sensors can localise corrosive conditions to within approximately one metre and estimate corrosivity rates in millimetres per year.
Central to the deployment is CorrosionRadar’s Clarity software platform, which aggregates live sensor data and applies predictive analytics, machine learning and AI-driven risk modelling. The platform reportedly monitors more than 45 million data points globally and is designed to integrate with existing risk-based inspection (RBI) and integrity management frameworks. Features include automated reporting, historical trend analysis and 3D visualisation of CUI risk across plant assets.
The system architecture uses long-range wireless communication technologies, including LoRa-based transmission, enabling monitoring over distances exceeding one kilometre while minimising field infrastructure requirements. Battery-powered sensor nodes are intended to simplify installation on both greenfield and brownfield facilities.
THE BROADER IMPACT OF CUI MANAGEMENT
During the 19th Middle East Corrosion Conference and Exhibition (MECOC), Ahmad O. Al-Khowaiter, executive vice president of technology & innovation at Aramco, emphasised the broader significance of AI-enabled corrosion management technologies for the energy sector: “The technological revolution we are now living through is changing how every industry operates. The advent of AI and big data is taking us into a new world where opportunities are limitless, and we are moving at a pace none of us have experienced before. AI will give us the power to predict failures before they occur, optimise maintenance schedules and extend the productive life of critical assets.”
Al-Khowaiter also noted the operational impact already being achieved through the deployment of predictive monitoring technologies: “CorrosionRadar’s technology is already delivering huge value through inspection cost reduction, improved uptime, and optimised turnaround planning.”
The greenfield deployment represents a significant evolution in how operators approach CUI risk. Traditionally, integrity programmes have relied on periodic inspection campaigns involving insulation stripping and spot ultrasonic testing. By contrast, continuous monitoring systems provide persistent visibility between inspection intervals and enable maintenance teams to prioritise interventions based on measured risk conditions rather than inspection schedules alone.
“Our latest project with Aramco is an important example of how embedding a CUI monitoring solution across a facility from the outset, will have a transformative impact on long-term asset strategies and maintaining asset health,” Dr. Chiraz Ennaceur, CEO and co-founder of CorrosionRadar, adds: “By prioritising data, machine-learning and predictive strategies over reactive ones, Aramco will be able to detect early indicators of corrosion and take informed action against any damage – improving safety, reducing costs, and enhancing operational efficiency.”
As operators across oil and gas, petrochemicals and power generation continue to digitise asset integrity programmes, large-scale predictive CUI monitoring deployments may increasingly become part of standard plant design philosophy rather than a retrofit integrity measure.
