Digital Twin for Production of an Industrial Paper Impregnation Process

Drying is one of the most widespread and energy intensive processes in industry. Therefore, even a small improvement in energy efficiency of the drying processes in general may lead to significant energy and GHG emissions savings. This work was developed as a part of a project which aims to decrease the energy consumption of an industrial resin impregnation plant dryer. For this purpose, two interconnected models were created. The first one describes the evaporation and heat transfer processes at the surface of the paper throughout the drying machine. The second one takes the resulting evaporation profile as an input and predicts the concentration of the evaporated solvents, water and methanol, in various parts of the drying machine. The model was then fitted using available operational data from the production plant, where the drying machine is situated. Two optimization measures were considered using the fitted model, both of which dealt with the reduction of input drying air flow. A significant potential for the reduction of used drying air, and therefore also energy demand, taking into account the lower explosive limit of methanol, was identified. The model will further be implemented in a digital twin of the drying machine, which will take real-time operational data as an input.