Advancing Operational Risk Management in Oil and Gas Refineries: A Review of IoT and AI-Driven Paradigms for Enhancing Safety, Reliability, and Environmental Stewardship

Refinery industries face numerous challenges, including corrosion, fire hazards, gas leakage management, and the overall complexity of operations. These challenges necessitate the adoption of advanced technologies for effective management and mitigation of risks. This review paper explores the critical role of the Internet of Things (IoT) and Artificial Intelligence (AI) in enhancing risk management and operational safety in refineries. IoT enables real-time monitoring and precise environmental data collection through the deployment of advanced sensors, smart devices, and interconnected networks. Simultaneously, AI enhances decision-making processes by analyzing complex datasets, predicting hazards, and optimizing risk mitigation strategies. The findings of this study are systematically categorized into five primary areas: real-time monitoring, risk prediction, corrosion detection and management, human factors and their role in safety protocols, and the existing opportunities and challenges in adopting these technologies. Results highlight that the integrated use of IoT and AI not only improves safety and operational efficiency but also significantly reduces costs. Nonetheless, barriers such as cybersecurity vulnerabilities, data integrity issues, and high implementation costs remain critical concerns. By proposing a comprehensive and scalable framework, this paper identifies innovative pathways for future research and practical advancements in refinery risk management and sustainable operations.

کلیدواژه ها:

Risk Management ، Refinery Safety ، Corrosion Prediction ، Predictive Maintenance ، Internet of Things ، Artificial Intelligence