Digital Twin for the SBR Cold Emulsion Copolymerization Process

• Published in: Macromolecular reaction engineering Vol. 18; no. 3
• Main Authors: Carpio, Roymel R., Feital, Thiago, Câmara, Maurício M., Gerhardt, Flávio, Oliveira, Leo Lincoln, Pinto, José Carlos
• Format: Journal Article
• Language: English
• Published: Weinheim Wiley Subscription Services, Inc 01.06.2024
• Subjects: 3‐butadiene rubber; cold emulsions; Continuously stirred tank reactors; Copolymerization; digital twin; Digital twins; Dynamic models; Emulsions; Modelling; Monitoring; Parameter sensitivity; polymerization reactors; process monitoring; Process variables; styrene/1
• ISSN: 1862-832X; 1862-8338
• DOI: 10.1002/mren.202300055

Development of accurate and robust dynamic models for the description of emulsion copolymerization processes is fundamental for the implementation of monitoring, advanced control, and optimization strategies. There are several studies on the dynamic modeling of styrene/1,3‐butadiene rubber (SBR) emulsion copolymerization, but most of them focus on hot conditions or only one semi‐batch reactor, as in the case of cold conditions. For this reason, the present study focuses on the dynamic modeling of SBR cold emulsion copolymerization processes considering a train of 15 continuous stirred tank reactors, as in many real industrial sites. The developed dynamic model is implemented by using the digital twin (DT) concept, which involves the online reading of process variables and an adaptive strategy for online tuning of some of the model parameters, being also sensitive to the effect of real‐time changes on the number of reactors in the train, a subject that has been overlooked previously, but which is important at the plant site. The practical application of the DT for monitoring a real industrial process illustrates the robustness and accuracy of the developed tool, making it useful for opportune detection of process anomalies and opening the way for future advanced control strategies. This study presents the practical implementation of a digital twin (DT) based on a dynamic model for monitoring the styrene/1,3‐butadiene rubber (SBR) cold emulsion copolymerization process considering a train of 15 continuous stirred tank reactors, as in many real industrial sites, involving the online reading of process variables and an adaptive strategy for online tuning of some model parameters.