EAF process optimization through a modular automation system and an adaptive control strategy

摘要

The complexity and variability of the Electric Arc Furnace process call for advanced monitoring and control solutions, in order to improve process performances, environmental compatibility and operator safety. The innovative Danieli Q-MELT Automatic EAF system addresses these aspects implementing a centralized control system which interacts with multiple technological packages. Each of these cutting-edge technologies focuses on one aspect of the EAF cycle, increasing machine availability and resource efficiency, by means of electrode regulation and foamy slag control, charging optimization, off-gas analysis and closed loop injectors control, on-line temperature measurement, automatic tapping and robotics. Moreover,these modules provide the process supervisor application (Melt Model) with important information regarding the process status, thus allowing the adoption of a unified control strategy. The supervisor implements a robust statistical approach to identify process deviations in real time. By means of advanced data collecting and data mining techniques, the available process data are clustered and filtered, and the expected trends of the key process variables are thus extracted. Melt Model applies this data-driven adaptive strategy to the oxygen injection management during the refining phase, optimizing the decarburization process and increasing the furnace performances. With such a modular and adaptive approach, Q-MELT aims to the “Zero Operator on Melting Floor" practice and allows multiple levels of process optimization, from a single process aspect to the entire EAF cycle.