A Hybrid Fuzzy-Monte Carlo and DEA Framework for Risk-Based Inspection of Flexible Risers

Flexible risers are critical subsea assets subjected to numerous failure mechanisms. This work introduces IBR-Flex, a high-resolution Risk-Based Inspection (RBI) framework designed to shift integrity management from traditional calendar routines to a dynamic, risk-based process. The methodology employs heuristic rules to codify expertise into probabilistic models that adjust failure rates based on section attributes. At its core, a dual predictor-corrector algorithm integrates deterministic physical models to forecast evolving risks, updating them dynamically as new evidences, e.g., inspection data, are acquired. To prioritise interventions across four domains - safety, environment, economy, and reputation - Data Envelopment Analysis (DEA) establishes a Relative Risk (RR) efficiency frontier.

Keywords: Flexible pipes, risk-based inspection, RBI, integrity, data science, subsea engineering, fault-tree.