COURSE OVERVIEW

 This practical and highly-interactive course includes various practical sessions and exercises. Theory learnt will be applied using our state-of-the-art simulators. 

 

This course is designed to provide participants with a detailed and up-to-date overview of Artificial Intelligence in Polyethylene & Polypropylene Manufacturing. It covers the role of AI in polyethylene (PE) and polypropylene (PP) production; the AI for raw material selection and feedstock optimization, polymerization process optimization and process control and automation in polymer plants; the AI in polyethylene and polypropylene extrusion, molding and predictive maintenance of polymer processing equipment; the AI for heat exchanger and boiler efficiency optimization, reactor performance monitoring and optimization; and the AI for pump, compressor and conveying system health monitoring. 

 

Further, the course will also discuss the AI for pipeline and storage tank monitoring in polymer plants, polyethylene and polypropylene formulation optimization and copolymer production; the AI for polymer drying, pelletizing optimization and energy efficiency in polymer manufacturing; sorting and classifying recycled polymers; optimizing polymer blending with recyclates and predicting recycled polymer properties; and the process control for enhanced recycled polymer performance. 

 

 

During this interactive course, participants will learn the AI for polymer plant safety and risk management, environmental compliance and emission monitoring; the machine learning for process optimization in digital twins and AI-powered predictive analytics for plant performance monitoring; the AI in advanced control systems and process automation including smart polymer manufacturing and AI-driven decision making; the future AI trends in polyethylene and polypropylene manufacturing and AI for AI-driven predictive analytics in polymer processing; the AI-driven polymer plant profitability optimization, machine learning for cost reduction in polymer production and AI-powered energy efficiency improvement models; and the AI-assisted raw material and product cost minimization.