IIoT‐Based Intelligent Process Control for Crude Oil Separation: Investigating the Impact of Model‐Based Control and Genetic Algorithms

Abstract

Integrating the Internet of Things (IIoT) with intelligent process control can improve the performance and efficiency of various industrial processes. However, there is a need for continued research on integrating IIoT‐based control with advanced techniques such as model‐based control and genetic algorithms to fully realize these benefits. This study investigates the impact of such integration on the performance of crude oil separation processes. To this end, we implemented IIoT‐based intelligent process control with model‐based control and genetic algorithms using specific IIoT devices and platforms, such as SCADAPACK 535E and FactoryTalk. The results of our implementation show that this technique can significantly improve the quality of crude oil separation, with an increase from 95% to 99% over two months of production. Overall, our findings suggest that integrating IIoT‐based intelligent process control with advanced techniques such as model‐based control and genetic algorithms can significantly improve the performance of crude oil separation processes and may have similar benefits in other industrial processes. Further research is needed to fully understand these techniques’ potential in different contexts and identify best practices for their implementation.