Abstract: To address a series of challenges such as high control difficulty, low manual efficiency, excessive reagent and energy consumption, and unstable product quality, the Panji Coal Preparation Plant has constructed an intelligent system covering the entire washing and separation process. By building intelligent control systems for heavy medium separation, flotation, and coal slime separation, the plant innovated a management model that substitutes functional workstations for fixed positions. Furthermore, it established an intelligent management and control framework comprising a data lake system, a comprehensive energy consumption management subsystem, and an equipment remote diagnosis system, thereby enhancing intelligent operation levels and overall production benefits. The effectiveness of the intelligent construction was quantitatively verified and analyzed through comparative tests of “sampling, preparation, and assaying” flotation reagent dosage, and coal slime screening, utilizing the statistical method of paired-sample t-tests. The results indicate that the single detection time of the intelligent sampling, preparation, and assaying system was reduced to within 30 min, with detection efficiency increasing by 75% compared to manual methods. The qualification rate of flotation clean coal rose to 95% (a 15 percentage point increase over manual dosing), while the dosages of foaming agents and collectors decreased by 4% and 2%, respectively. Additionally, coal slime with a particle size of > 0.125 mm was almost entirely recovered. At the operational level, labor requirements were reduced by 52% compared to the designed staffing level. Power consumption per ton of coal decreased from 11.63 kW·h to 11.38 kW·h, and heavy medium consumption fell from 0.98 kg to 0.70 kg. The accident impact time per 10,000 tons of raw coal was shortened from 0.57 h to 0.43 h, and the moisture content of dry coal slime products was reduced to below 18%. Panji Coal Preparation Plant has successfully developed an intelligent construction model characterized by technical adaptation, personnel transformation, data integration, and cost control. The resulting engineering experience is replicable and scalable, providing a reference and demonstration for the intelligent upgrading of the domestic coal preparation industry.