In response to climate change mitigation and the pursuit of circularity, Tata Steel Netherlands plans to construct an Electric Arc Furnace (EAF) to replace the carbon-based blast furnace. Initially, the EAF will operate with a ratio of 70% Direct Reduced Iron (DRI) and 30% steel scrap, with future intentions to increase scrap input for enhanced circularity. However, the capacity of an EAF to effectively handle significant changes in the scrap ratio remains uncertain. This thesis includes a detailed literature review addressing this gap by exploring the implications of Scrap and DRI, in the EAF operations, covering various fundamentals of the EAF process - raw materials, operating regimes, melting practices, metallurgy, slag engineering, and furnace constructions, with a specific focus on Consteel technology. For optimal EAF operation, fine-tuning slag chemistry is essential to achieve the desired balance of slag basicity, foaming, volume, and ensuring long refractory life of the furnace. Slag composition can vary widely due to multiple process variables including the type of charge mix, charge composition, charge feeding rate, oxygen lancing, carbon injection/addition, fluxing agents, and refractory erosion. These variables cause slag composition and rates to be transient parameters that evolve throughout the heating process, leading to dynamic changes in all related phenomena and outcomes. To accurately capture these effects and realistically simulate EAF operations, especially in the absence of real plant data, a dynamic process model is essential. This thesis investigates the operational implications of varying the Scrap:DRI ratio in an EAF process with continuous raw material charging using the dynamic Effective Equilibrium Reaction Zone (EERZ) model. This model allows for a comprehensive analysis of the transient behavior of slag composition and its impact on EAF performance. This thesis examines three cases of charge mix: 70% DRI with 30% scrap, 50% DRI with 50% scrap, and 30% DRI with 70% scrap. Pilot EAF trial data will be used for the validation of the model. Overall, the thesis aims to provide insights into optimizing Scrap:DRI ratios for sustainable and efficient steelmaking.