Leveraging Generative AI to Tackle Corrosion Challenges in the Downstream Industry

Abstract

Abstract The downstream industry stands at the edge of a revolutionary transformation, driven by the unprecedented capabilities of Generative Artificial Intelligence (AI) in addressing critical corrosion management challenges. This paper examines how Generative AI technologies, particularly Large Language Models (LLMs) and advanced machine learning systems, fundamentally disrupt traditional corrosion management paradigms while creating substantial operational value and fostering innovation across downstream operations. The global economic burden of corrosion, estimated at approximately $2.5 trillion annually, presents a compelling case for technological intervention and innovation (1, 3). Through systematic examination of two groundbreaking use cases—AI-enhanced analysis of Piping and Instrumentation Diagrams (P&IDs) for corrosion-critical equipment identification and automated robotic corrosion inspection systems—this paper demonstrates the transformative potential of Generative AI in revolutionising asset integrity management, reducing operational costs, and enhancing safety protocols in corrosion-prone environments. Looking forward, the continued evolution of Generative AI will enable predictive corrosion modelling, material selection optimisation, and advanced operator training, positioning companies to create new value streams and gain a competitive advantage in challenging environments.

Ähnliche Arbeiten