As the core equipment of the domestically developed hot-state triple-furnace continuous copper smelting system, the multi-lance top-blown furnace still requires further improvement in process monitoring and intelligent decision-making capabilities. Current challenges include delayed parameter adjustments, pronounced fluctuations in furnace conditions, and suboptimal continuity in production. This research developed a decision optimization system for top-blown furnace operations by integrating metallurgical modeling, industrial data acquisition, and software development. Based on the metallurgical reaction mechanism, the input-output mathematical model of the top-blown furnace was established to enable quantitative determination of core operating parameters such as flux dosage and oxygen volume. A calculation model for key process parameters was created to overcome limitations in real-time process state perception during continuous smelting. Through systematic integration, modules for data acquisition and model computation were encapsulated into a comprehensive decision optimization system. The system provided accurate calculation and decision support for core control parameters. It significantly reduced the uncertainty associated with manual operations but also provided effective technical support for dynamic multi-process coordination and control within the hot-state triple-furnace continuous copper smelting process.