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Around 80% of the FeCr produced worldwide is utilized in stainless steelmaking. Thus, the growth of the stainless‐steel industry is directly related to FeCr production. Although the FeCr production in submerged arc furnace (SAF) is fairly stabilized, new challenges have emerged in the furnace operation due to the depletion of lumpy ores, high SiO2 content, and lower Cr/Fe ratio in the low‐grade ores. In this regard, the addition of various fluxes such as quartz, magnesite, and bauxite are considered to improve the Cr recovery in SAF operation, particularly in the context of low‐grade ores. In this study, thermodynamic calculations are performed to discuss the effect of various additives (MgO in magnesite, Al2O3 as bauxite, and SiO2 in quartz form) on Cr recovery and slag formation temperature. In addition, a comprehensive thermodynamic‐based process model has been developed for FeCr operation that captures the most important thermochemical reactions. The modeling results are compared with the plant data, and suitable modifications in the slag compositions are made to maximize Cr recovery. Moreover, new plant trials are performed with modified slag composition, and its effect on Cr recovery is also discussed. [ABSTRACT FROM AUTHOR]

Improving the quality of stainless-steel hinges significantly on precisely managing decarburisation within the argon-oxygen decarburisation (AOD) process. This study introduces a dynamic model capable of accurately predicting the composition and weight of steel and slag. To thoroughly investigate the refining processes, a systematic analysis was conducted, integrating three essential adiabatic zones within the AOD converter: the continuous stirred-tank reactor, slag bath and plug flow reactor, supported by circulation and recirculation streams. FactSageTM software and its macro facility were utilised to identify the different phases present in steel and slag. This dynamic model not only forecasts critical process parameters like temperature, composition and volume of multiple phases but also enables the prediction of the final chromium content for different initial carbon inputs, specifically at 2%, 1.5% and 1 wt.%. By comparing the model's predictions with actual plant data, it was observed that the transient compositions of steel and slag exhibited consistency, confirming the model's validity and reliability in simulating AOD refining processes. [ABSTRACT FROM AUTHOR]