铁区一体化智能配矿及成本预测模型

利用大数据技术结合配矿工艺机理，开发各工序配料优化及成本预算系统，支撑企业制定合理的采购策略，从采购端科学降本基于数据挖掘和智能算法，为公司提供精准且极具竞争力的配矿方案；对配矿方案进行跟踪和效果评价系统性提升“计划-测算-方案-采购-执行-复盘”配矿业务链的决策运转效率，最终起到降低铁水生产成本的作用。

Leveraging big data technology combined with the ore blending process mechanism, an ore blending optimization and cost budgeting system covering each production step has been developed. This system supports enterprises in formulating rational procurement strategies to achieve scientific cost reduction from the procurement end. Powered by data mining and intelligent algorithms, it provides the company with accurate and highly competitive ore blending schemes. Furthermore, by tracking ore blending schemes and evaluating their implementation effects, the system systematically enhances the decision-making and operational efficiency of the entire ore blending business chain spanning "planning, calculation, scheme formulation, procurement, execution and post-review", ultimately reducing the production cost of hot metal.