Corrosion is one the most critical and challenging phenomena impacting all industries’ infrastructure integrity, leading to equipment outages, catastrophic failures, and more spending on maintenance costs if not addressed. Scholars are working to enhance and optimize corrosion monitoring and prevention to minimize the corrosion effect through adopting the IR 4.0 digital transformation. The transformation must integrate the current technologies and methodologies using artificial intelligence and machine learning to understand corrosion better and control it. This paper will present a comprehensive review of AI and ML corrosion applications, focusing on empowering computers to accomplish tasks without relying on explicit programming. Machine Learning allows computers to acquire knowledge and improve their performance without relying on explicit instructions from programmers. The deep learning (DL) aspect and the accuracy effect in the developed algorithmic models were also explored. The challenges and future direction in deploying AI-driven solutions for corrosion were discussed to create a clear picture in decision-making having reliable output products.

Voulme 1- Issue 1- PP: 10-22

DOI: https://doi.org/10.5281/zenodo.14804973