Concluding Remarks

The highly competitive environment of petrochemical production requires a high utilization and optimization of the processes to produce chemicals with the least amount of energy and cost.

The petrochemical industry has invested in control systems, advanced process control and real time optimization applications to optimize their process and operations. However, the current technologies do not optimally address changes in feed composition and other effects related to asset utilization. Artificial intelligence (AI) and machine learning (ML) powered by cloud-based computing offers a complementary add-on to increase efficiency and support higher yields and margins by operating closer to product specification at the lowest energy intensity. AI can optimize the existing automation platforms and applications by providing real time predictions and prescriptions for operators and plant engineers.

This presentation addresses the development and deployment of AI-based advanced process control and real time optimization applications designed to decrease emissions, reduce energy consumption, and improve overall efficiency of petrochemical plants.