Sidenor has identified the necessity of tools for the improvement and optimization of the environmental footprint and the energy efficiency during the steelmaking process. This production route has undergone continuous improvement for decades through the development of remarkable technologies, which have facilitated significant advancements in energy consumption. However, certain energy inefficiencies persist and their optimization is a challenge.In fact, the factors why the energy consumption between two apparently identical production batches is significantly different, are currently being studied.. The focus is on the two steelmaking processes with the highest impact on energy consumption; these are the electric arc furnace and the secondary metallurgy. DENIM system will include process predictive models (both process performance and energy consumption models) and optimizers which will collect the data, process, and provide important information for helping the operators in the decision-making process for a more energy-efficient steelmaking management. In the case of Sidenor, the models will predict energy consumption and process performance, such as temperature and key chemical elements, during the electric arc furnace and the secondary mealurgy processes taking into account all the raw materials and energy inputs. The system will display relevant information at each process step. The integration of these models with optimization algorithms will allow defining the optimal values of key parameters to reduce the energy consumption ensuring a good performance of the process. The LCA will be other relevant parameter to be considered.