In recent years, China has been committed to promoting energy-saving and emission-reduction measures across various industries. In the steel production process, wet dust removal technology is widely adopted. However, the existing dust removal equipment, particularly the cyclone separator, suffers from insufficient dewatering efficiency, leading to a "rain" phenomenon during waste gas emission, which in turn causes secondary environmental pollution. The design of the guide vane wheel is crucial for enhancing the dewatering efficiency of the cyclone separator. Therefore, this study, based on fluid mechanics and flow field analysis theories, utilizes the FLUENT software to simulate and analyze the blade angle and flow area of the guide vane wheel. By combining the flow field analysis and simulation results with the specific parameters of the equipment, the structure of the cyclone separator's guide vanes was optimized and applied to actual production. Practice has proven that the optimized cyclone separator significantly improved dewatering efficiency and effectively reduced the rain phenomenon around the chimney, thereby enhancing environmental quality. The research of this project is conducive to the later application of artificial intelligence, the Internet of Things, big data, cloud computing, and other technologies in the 5G+ smart steel factory of the steel industry. It lays the foundation for using digital twin technology to carry out 3D modeling of the plant area, in order to facilitate the reappearance and simulation of the entire production process.