(28c) A Hybrid Approach for Fouling Monitoring and Forecasting with Application to an Industrial Heat Exchanger
AIChE Spring Meeting and Global Congress on Process Safety
Monday, March 13, 2023 - 4:30pm to 5:00pm
We propose a hybrid approach, where knowledge-based feature generation is integrated with data-driven methods, to forecast a key performance indicator (KPI) that acts as a fouling surrogate (Diaz-Bejarano et al., 2020). Knowledge-based feature generation allowed to monitor the evolution of fouling over time and enabled the use of off-the-shelf data-driven forecasting methods. Among the KPIs tested, two were selected to act as fouling surrogates. We advise monitoring them in tandem with the Reynolds number and the ratio ÎT/ÎTml as KPIs because the first one reflects the flow conditions in the heat exchanger while the ratio provides information on the heat transfer phenomena. The developed forecasting model, a time series multiple regression model, was capable to predict the KPI one-month ahead with a testing accuracy of R2=0.7. Furthermore, we showed that long-term forecasting is also possible with this model, always with the caveat that the furthest we look into the future, the more uncertainty the forecast carries. Nevertheless, the model can still be applied for process optimization and maintenance scheduling.
In the future, we believe it will be opportune to further develop the model as well as the optimization framework by including uncertainty quantification on the inputs and in the model. In this way, more robust decisions can be made that consider process safety, reliability, and profitability.
Cavitt SB. Ethylene oxide production. US Patent 4,374,260 (Feb. 15, 1983).
Crocco L, Glassman I, Smith I. Kinetics and mechanism of ethylene oxide decomposition at high temperatures. The Journal of Chemical Physics. 1959;31.
Diaz-Bejarano E, Coletti F, Macchietto S. A model-based method for visualization, monitoring, and diagnosis of fouling in heat exchangers. Industrial & Engineering Chemisty Research. 2020;59.
Hess L, Tilton V. Ethylene oxide-hazards and methods of handling. Industrial & Engineering Chemistry. 1950;42.
Montgomery DC, Peck EA, Vining GG. Introduction to Linear Regression Analysis. 5th Edition, John Wiley & Sons, Inc., Hoboken, New Jersey, 2012.
Sundar S, Rajagopal MC, Zhao H, Kuntumalla G, Meng Y, Chang HC, Shao C, Ferreira P,
Miljkovic N, Sinha S, Salapaka S. Fouling modeling and prediction approach for heat exchangers using deep learning. International Journal of Heat and Mass Transfer. 2020;159.
Trafczynski M, Markowski M, Urbaniec K, Trzcinski P, Alabrudzinski S, Suchecki W. Estimation of thermal effects of fouling growth for application in the scheduling of heat exchangers cleaning. Applied Thermal Engineering. 2021;182.