Uncertainty conditions of input variables in the steel sector: application of Monte Carlo Simulation to an Italian Company

This thesis aims to study how variation in input variables affects the economic performance for a steel organization, using Electric Arc Furnace (EAF) referred to as X.Y.Z Co for confidentiality. Italy is the leading user of EAF in Europe holding a robust manufacturing cycle also aligning with goals of achieving reducing carbon emissions and sustainability as requested by EU Green Deal aiming for Carbon Neutrality by 2050. Steel sector is subjected to great variation of input variables due to raw material prices, energy costs, market demand, technological advancements and environmental Sustainability. This thesis focuses on analysing the variation of the input parameters specifically involved in the production due to market changes by employing Monte Carlo simulation; Several scenarios are simulated in order to study which are the inputs that has the most impactful on the business sustainability and whether with different forthcoming scenarios, the business can withstand its threshold profit. As a result we achieve valuable insights and recommendations for optimizing steel production processes for the specific Company. Scenarios are based on the variation of important inputs of this type of steel production that are metal scrap and energy. The impact on profit is analysed in terms of variation along the year. The developed model can help the company to define scenarios based on the behaviour of these variables along the years and to manage budget in a more precise way. It can be used both by the production and by the financial managers to merge together information about production, purchasing prices and target expectation from the company board to arrive to the definition of the budget. Ultimately, this research contributes to the advancement of resilience practices in the steel organization and informs decision-making in the complex economic landscape.