A systematic approach to numerical analysis and validation for industrial oven design and optimization

Abstract

Abstract This article presents a study on optimizing the internal velocity and heat distribution in an industrial belt oven with forced convection. The oven is primarily used for drying and cooking legumes. Computational fluid dynamics (CFD) and the Taguchi design of experiment methods were employed to determine the influential design variables. The 3D CFD model was then compared with experimental results to validate its accuracy. The oven comprises a permeable stainless-steel belt and axial fans with stick-type heaters, which facilitate the circulation of hot air. By assessing the fans' locations and the back chamber geometry, the internal flow patterns were analyzed to enhance airflow distribution. Design variables including the number of fans, the distance between fans, and the distance from fans to the belt surface were considered. Evaluation criteria encompassed belt surface temperature deviation and belt surface velocity deviation. An experimental oven design was developed based on optimal signal-to-noise (S/N) ratios, and the numerical findings were corroborated through experimental measurements, demonstrating a strong agreement. The proposed approach, encompassing the design, manufacturing, and analysis stages, can be applied to diverse industrial oven designs.