Optimization of polypropylene surface texturing with ultrafast lasers. A semi-empirical and computational methodology for wettability control
Author: Julen Molinuevo López
2024
Thesis director
Carlos Molpeceres Álvarez, Universidad Politécnica de Madrid, y Eva Rodríguez, Tekniker
The main objective is to provide a guide for future materials and feature geometries, showing the steps to follow to study the effect of different topographical parameters that define a texture on the contact angle, as well as introducing a simulation modelling tool to predict which type of texture and/or dimensions offer the best results.
Análisis de la viabilidad del magnetron sputtering como método de fabricación de catalizadores alternativo
Author: Antía Villamayor Dono
2024
Thesis director
Victoria Laura Barrio, UPV/EHU y Eva Gutiérrez, Tekniker
En esta Tesis se analiza la validez y versatilidad del magnetron sputtering como método alternativo de fabricación de catalizadores empleados en tecnologías de interés medioambiental.
Advances in flexible manipulation through the application of AI-based techniques
Author: Ander Iriondo Azpiri
2023
Thesis director
Elena Lazkano, Facultad de Informática, EHU/UPV; Ander Ansuategi, Tekniker.
We are in the transition between Industry 4.0 and 5.0, where in addition to productivity, flexibility is also sought to adjust processes to specific customer needs.
Physicochemistry of non-immersion ultrasonic cleaning
Author: Jon Ander Sarasua
2023
Thesis director
Leire Ruiz, EHU/UPV y Estíbaliz Aranzabe, Tekniker
This thesis focuses on the study and scaling of a disruptive technology called "non-immersion ultrasonic cleaning".
Deep Learning Algorithms in Industry 4.0; Application of Surface Defect Inspection for Quality Control
Author: Vignesh Sampath
2023
Thesis director
Juan José Aguilar Martín, Universidad de Zaragoza; Iñaki Maurtua, Tekniker
This PhD thesis aims to develop an automated method for defect identification based on the magnetic particle technique using deep learning.
Contributions to time series analysis, modelling and forecasting to increase reliability in industrial environments
Author: Meritxell Gómez
2023
Thesis director
Basilio Sierra Araujo, Facultad de Informática, UPV/EHU; Susana Ferreiro, Tekniker
The integration of the Internet of Things in the industrial sector is considered a prerequisite for achieving intelligence in a company. To obtain this, AI systems with analytical and learning capabilities are required for the optimisation of industrial processes.