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.
Contributions to autonomous robust navigation of mobile robots in industrial applications
Author: Iker Lluvia
2023
Thesis director
Elena Lazkano, Facultad de Informática, EHU/UPV; Ander Ansuategi, Tekniker.
A large part of this research work presented in this document focuses on quantifying the error committed by the main mapping and localisation methods, offering different alternatives for improving their positioning.
Physicochemistry of non-immersion ultrasonic cleaning
Author: Jon Ander Sarasua
2023
Thesis director
Leire Ruiz, Facultad de Ciencia y Tecnología de la EHU/UPV; Estíbaliz Aranzabe, Tekniker
This thesis focuses on the study and scaling of a disruptive technology called "non-immersion ultrasonic cleaning".
Medical devices with embedded electronics: design and development methodology for start-ups
Author: Nerea Arandia
2023
Thesis director
Jose Ignacio Garate Añibarro, Escuela de Ingeniería, EHU/UPV; Jon Mabe Álvarez, Tekniker.
This thesis presents a methodology for start-ups that outlines the steps to design and develop embedded medical devices.
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.