This initiative has enabled the company to reduce defects linked to metallurgical causes by up to 50%, significantly improving process stability in one of the most critical stages of foundry operations.<\/p>\n
Launched in 2024, with industrial implementation scheduled for 2026, the project integrates industrial sensors, data acquisition systems and machine learning algorithms. These tools allow the company to anticipate the evolution of molten metal composition and optimise furnace operations in real time.<\/p>\n
In addition to enhancing product quality, Optimodel has improved efficiency and sustainability. Key results include reductions of up to 15% in copper consumption and up to 50% in tin usage, as well as lower reliance on other ferroalloys.<\/p>\n
A major milestone of the project has been the development of predictive models capable of estimating material properties\u2014such as strength and hardness\u2014prior to manufacturing. This reduces uncertainty and minimises the need for post-production adjustments.<\/p>\n
The initiative has been carried out in collaboration with the Public University of Navarre (UPNA) and has received support from the Government of Navarre, reflecting the region\u2019s strong commitment to digitalisation and industrial R&D as key drivers of competitiveness.<\/p>\n
With this development, Tafalla Iron Foundry strengthens its position as a benchmark for industrial innovation within Navarre\u2019s ecosystem and moves towards full-scale implementation, consolidating a model based on intelligent decision-making and advanced technologies.<\/p>\n