Introduction to Integrated Process Modeling, Advanced Control, and Data Analytics in Optimizing Polyolefin Manufacturing

This chapter introduces key concepts and methodologies in polymer process modeling, emphasizing its role in driving innovation and sustainability in polyolefin manufacturing. Beginning with an overview of essential polymer attributes, such as molecular weight distributions (MWN, MWW) and the polydispersity index (PDI), the chapter highlights the use of moment-based modeling techniques to quantify polymer properties. A practical workshop using Aspen Plus, including Aspen Polymers, is presented to demonstrate how the attributes of mixed copolymer streams can be analyzed. This hands-on approach provides an accessible entry point to understanding the impact of mixing on polymer quality. The development of a simplified simulation model for a slurry high-density polyethylene (HDPE) process is explored in depth, showcasing the workflow and motivating questions that highlight the transformative potential of process simulation. These models serve as quantitative tools for sustainable design, capacity expansion, process optimization, and product innovation. Additionally, the chapter reviews industrial applications of polymer process modeling, advanced process control, and data analytics, underscoring their synergistic role in enhancing the efficiency, quality, and profitability of polyolefin manufacturing. This integrated perspective advances the understanding of polymer process modeling as a foundational pillar for achieving next-generation manufacturing goals. This is a preprint version of a chapter from our book-Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing. Please cite the original work if referenced [65,66].