An Open-sourced Digital Twin Model of an Industrial Dryer

In this paper a digital twin model of a drying machine is presented to accurately predict its temperature and humidity based on experimental data. The prediction facilitates energy-efficiency of the industrial dryer IQ6 for disinfecting surgical instruments, e.g., forceps. The model is achieved by integrating a simplified thermodynamic model and a Data-Driven Physics-Informed Neural Networks (DD-PINNs). Our contribution to the state-of-the-art is to provide and open-source a digital twin model of an industrial dryer. The shared model and data can be extended and reused for other energy-efficient drying applications.