On‐line inference of polymer properties in an industrial polyethylene reactor

TLDR

Industrial polymerization reactors struggle to control product quality due to the lack of suitable on‑line polymer property measurements, making it essential to detect deviations from desired targets to reduce off‑grade material and ensure consistency. The article develops a scheme to predict melt index and density in a fluidized‑bed ethylene copolymerization reactor. The authors derive theoretically based models that predict quality variables from on‑line temperature and gas composition measurements, update adjustable parameters online using infrequent laboratory measurements and a recursive parameter estimation technique, and illustrate the methodology with operating data from an industrial reactor. The approach successfully predicts both melt index and density.

Abstract

Abstract A major difficulty affecting the control of product quality in industrial polymerization reactors is the lack of suitable on‐line polymer property measurements. In this article a scheme is developed to predict melt index and density in a fluidized‐bed ethylene copolymerization reactor. Theoretically‐based models are derived to predict quality variables from the available on‐line temperature and gas composition measurements. Adjustable parameters in these models are updated on‐line using infrequent laboratory measurements and a recursive parameter estimation technique. The application of this methodology is illustrated using operating data from an industrial reactor. It is shown that both melt index and density can be successfully predicted. Knowledge of product property deviations from desired targets is required so that manufacturers can take corrective actions to reduce the quantity of off‐grade material made and produce a consistent product.