Speaker
Description
Physicists are naturally equipped with a versatile toolkit for solving complex, non-linear problems. However, the connection between academic research and industrial engineering is not always explicitly highlighted. This presentation explores how FINSA (Financiera Maderera, S.A.), a relevant and well-established company in the wood manufacturing sector, translates these analytical and computational skills into real-world industrial value.
The talk will focus primarily on the deployment of Machine Learning (ML) algorithms on the factory floor, demonstrating how data-driven models are used to predict material properties, and control variables in real-time. In addition, we will look at how these predictive models are complemented by physics-based tools like Computational Fluid Dynamics (CFD) to refine complex thermal and aerodynamic processes. By bridging the gap between theoretical modeling and industrial reality, this presentation aims to prove that the analytical skills developed during a physics degree are highly valuable, transferable, and critical for the future of smart manufacturing.