Abstract: In industrial production, the inefficient removal of dust particles poses a significant barrier to operational productivity. Consequently, an in-depth analysis and upgrade of industrial dust removal components is critical. This research employs computational fluid dynamics with discrete particle modeling (CFD-DPM) alongside particle image velocimetry (PIV) to investigate the airflow dynamics throughout the flow domain of dust removal components, comparing the effects of both the original and optimized designs on dust particle behavior. By integrating numerical simulations with experimental validation, we explore the movement characteristics of compressed air and dust particles within the dust removal components. Our goal is to optimize the performance of existing dust removal components, thereby determining the most effective dust removal strategy. The results demonstrate that the optimized design markedly improves the external flow structure of the dust removal components. Through balancing the turbulent kinetic energy of the gas flow at the outlet, the optimized component enhances the flow velocity and expands the high-speed flow area, effectively minimizing dust particle entry into the component. These improvements collectively achieve a more efficient dust removal outcome, highlighting the potential for optimized design to support higher productivity in industrial settings.