New methodology for estimating the influence of Cu content of Ferrous Scrap materials in the Total Cost of Operation (TCO) of scrap mix in Electric Arc Furnace steelmaking

Abstract

Scrap is the main raw material of the electric arc furnace (EAF) route of steelmaking and an important one in the primary route. The decarbonisation commitment acquired by the most relevant steelmaking companies, will only increase the amount of scrap used by both routes, making it a critical component to succeed in the worldwide challenge of reducing CO2 emissions. While being a very relevant material, scrap characterisation is complex due to its heterogeneity, but furthermore, its quality is worsening as its demand increases. This includes the sterile content, such as copper. Higher sterile content scrap comes at a lower price, while scrap with a lower content in undesired elements is most costly. Being able to balance the cost and benefit of purchasing scrap with a higher or lower content of copper with a respective, lower or higher purchase cost would be of interest to optimise the mix and produce the required quality steel at the lowest possible cost. Nowadays, this cost benefit analysis can only be done by performing Total Cost of Operation (TCO) calculations that require a considerable amount of information, including but not limited to the complete chemical composition of scrap, market parameters, production forecast and other relevant data; moreover, involving an arduous optimization process. Based on a parametric study of the TCO calculation, this work proposes a mathematical model to estimate the impact on the TCO of a predefined scrap mix when only modifying the specifics of one given scrap type. The results would facilitate the decision making by comparing the two scenarios as a factor of cost. This mathematical model can be easily programmed and requires only 5 parameters to be run, while providing a low error result.