The main objective of this research work is to demonstrate the potential for improvement that techniques and methodologies related to prescriptive analytics can provide in industrial maintenance applications.
Context- and Template-Based Data Compression Approach to Improve Resource-Constrained IoT Systems Interoperability
In this thesis, we present a novel data compression approach for text-based data formats, namely Context- and Template-based Compression (CTC), which is specially designed taking into account the limitations of resource-constrained devices and networks.
Como resultado principal de esta tesis, se presenta una metodología para asistir el desarrollo de sistemas innovadores, heterogéneos y confiables. La metodología propuesta combina y adapta: modelos para el desarrollo de nuevo producto; aproximaciones para el desarrollo de sistemas confiables; enfoques para el desarrollo de sistemas complejos; y técnicas de control estadístico de procesos e indicadores clave de rendimiento.
This PhD study aims to improve the accuracy of MTs and also to develop knowledge for traceable coordinate measurement machine (CMM) measurements on MTs. The technology to run a dimensional measurement on an MT already exists but the knowledge to do traceable measurements is under research, as it is reported in this thesis.
The main objective of this thesis is to develop and characterize the scope of a novel and edge-cutting approaches based on markerless photogrammetric solutions. Hence, the presented study is focused on going beyond the state of art limitations of industrial photogrammetry avoiding or reducing considerably the employment of artificial targets.
Development of a high torque density and efficiency axial flux switched reluctance motor for electric vehicle
This research is focussed on the development of a high torque density and efficiency motor, suitable for cost-effective mass production.