Abstract
This article discusses an approach to developing digital twins for the food industry based on monitoring and numerical modeling of thermodynamic processes in a baking chamber (electric oven). The professional electric oven ASTAR, designed for the thermal processing of bakery products, was used as the experimental object. As part of the monitoring system, an infrared pyrometer (VICTOR 304F), a thermal imaging camera (UNI-T UTi120S), and an analog thermometer (MGprof) installed inside the oven chamber were employed. This setup allowed for the acquisition of reliable temperature data within the working chamber. Temperature data were collected periodically throughout the baking process, and based on these measurements, a temperature field map was generated. A mathematical model of heat transfer, implemented in two-dimensional (2D) format using MATLAB PDE Toolbox and incorporating Dirichlet and Neumann boundary conditions, was validated through comparison with the experimental results. The obtained results not only enable accurate modeling of temperature gradients and heat fluxes inside the baking chamber, but also lay the foundation for the creation of a digital twin capable of predicting system behavior in real time. The proposed approach can be applied to improve energy efficiency, automate quality control, and optimize technological processes in the food industry. This research contributes to addressing the challenges encountered in modeling and designing thermodynamic processes during the development of digital twins.