Dynamic scheduling optimization model coupling material-flow laminarization and temperature drop for iron-steel interface

To address the challenges of logistical disorder, low hot-metal ladle turnover rate, and significant temperature drop at the iron-steel interface under the “One-Ladle-to-the-End” process, this paper proposes a dynamic scheduling optimization method that couples material-flow laminarization with molten-iron temperature-drop mechanisms. First, based on metallurgical process engineering theory, a quantitative index for cross-coupling degree of material flow was defined, and a blast-furnace-to-steelmaking matching rule base oriented toward laminar flow was constructed. Second, through months of on-site continuous temperature measurement campaigns, the nonlinear mechanisms by which runner residual iron mixing, empty-ladle waiting, and tail-ladle handling affect hot-metal temperature drop are revealed, and a composite temperature-drop prediction model based on dynamic operation time was established. On this basis, a multi-objective dynamic scheduling optimization model minimizing both temperature-drop penalty and ladle turnover time was formulated, and a hybrid solution strategy combining a rule engine with discrete-event simulation iteration was designed. Industrial validation using actual production data from three 2 900 m³ blast furnaces and two steelmaking plants at HBIS Tangsteel New District demonstrates that, compared with traditional empirical scheduling, the proposed model reduces the average turnover cycle of 260 t ladles by 44 min, decreases the additional temperature drop caused by tail ladles by approximately 38 ℃, and improves the desulfurization station entry temperature compliance rate (≥1 380 ℃) by 22 percentage points, confirming the effectiveness and significant economic value of the method in complex iron-steel interface dynamic scheduling.