Marcos Alonso Nieto: "Robust Laser-Based Optical Measurement in Industrial  Harsh Environments".
Zuzendariak_Directores: Manuel María Graña Romay.
2022_10_11, 11:00  Sala Ada Lovelace aretoa.

ABSTRACT:

"In the metal parts manufacturing industry, maximising the throughput, manufacturing on time and on budget, and ensuring  zero-defect products are among the most significant aspects of the production chain. The purpose of Quality Control is to prevent defects, i.e, ensure that the parts are made to comply with design specifications and will function properly as part of larger assemblies, such as a car transmission, engine, car body, just to cite some. Quality Control also contributes to product safety and prevents reliability issues, which can often increase costs, lead to product recalls, or trigger issues that endanger final consumers.

This thesis reports on the design and experimental assessment of reliable dimensional control using laser based optical devices. Modeling and calibration of such systems, as well as the 

filtering of the delivered data, has been one of the primary motivations. In particular, modern AI-based algorithms such as Deep Learning and Machine Learning have made these processes faster and easier. Two scenarios were chosen to validate experimentally this work. The former consists of an in-line inspection where complex warm forged revolution parts for automotive propulsion systems are measured. The latter computes the flatness and the surface quality of metal sheets produced by a cut to length production line, where the entire process of unwinding, fattening, cutting and stacking metal sheets takes place."