Publications

As global energy demand continues to rise, alongside challenges such as declining gas production and environmental concerns, optimizing efficiency, and reducing emissions from air-cooled exchanger fans in industrial processes has become a pressing issue. Currently, the air coolers at the North Belut facilities are operating at full capacity, with all 4 to 6 fans running at maximum capacity. Despite their inherent capability to achieve outlet temperatures as low as 100°F, they consistently fall short of their intended design capacity due to the current gas flow rate being lower than the original design specifications. This raises significant concerns regarding the overall health and efficiency of these critical cooling systems.

This paper aims to present an innovative solution for evaluating the performance of process equipment, specifically air coolers, by utilizing machine learning to develop the Equipment Performance Monitoring System (EPMS) application. This application includes a dashboard for monitoring, serving as a process equipment surveillance tool. This cutting-edge tool acts as a vigilant monitor for process equipment, enabling detailed analysis of air cooler performance. Its primary features are to promptly detect and address operational inefficiencies and maintenance requirements, representing a proactive approach to performance optimization. By taking this proactive approach, not only power consumption can be improved, but also the integrity and reliability of the facility's cooling processes can be maintained by placing one or two of the fans on standby mode.

Through case studies and simulations, this paper demonstrates the potential for substantial improvements in the operational performance of air-cooled exchanger fans. The primary goals of this innovative solution are not only to develop an Equipment Performance Monitoring System (EPMS) using a machine learning approach but also to implement the result of this surveillance tool to achieve improvements in air-cooled efficiency, and emission reduction.