Corrosion Under Insulation (CUI) is one of the process industries’ most persistent integrity threats and one of the hardest to manage through conventional sample-based inspection. Risk-Based Inspection (RBI), guided by API RP 580 and 581, is a sound framework for allocating inspection resources by probability and consequence of failure — but for CUI, its performance is limited by the quantity, consistency, and representativeness of the evidence available to validate degradation assumptions and update Probability of Failure (PoF).
ARIX® Technologies’ VENUS robotic platform removes that limitation: high-density Pulsed Eddy Current (PEC) and Real-Time Radiography (RTR) scanning, paired with georeferenced digital reporting, produces a far denser, more consistent inspection dataset — without scaffolding or insulation removal. This paper explains how that dataset strengthens existing RBI programs: sharper inspection targeting, more defensible risk decisions, and a consistent methodology across sites and portfolios. Robotics supplies the evidence RBI needs to become more accurate, repeatable, and economically scalable.
RBI is the accepted framework for prioritizing mechanical integrity because it focuses resources where risk is highest. For CUI, however, that decision is often based on indirect risk factors and a small number of inspection locations — not because the RBI philosophy is flawed, but because scaffolding, insulation removal, inspection, disposal, and reinstatement have historically been costly and disruptive.
