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Projecte llegit

Títol: Detection of unsupervised anomalies in light sensors.

Estudiants que han llegit aquest projecte:


Departament: DAC

Títol: Detection of unsupervised anomalies in light sensors.

Data inici oferta: 19-09-2022     Data finalització oferta: 19-04-2023

Estudis d'assignació del projecte:
Tipus: Individual
Lloc de realització: Fora UPC    
        Supervisor/a extern: Marta Couto Garcia
        Institució/Empresa: Giesecke & Devrient
        Titulació del Director/a: Grado e Telecomunicaciones
Paraules clau:
Web app, unsupervised anomaly detection
Descripció del contingut i pla d'activitats:
Overview (resum en anglès):
This project aims to investigate and create a solution to a problem that the
company Giesecke & Devrient has in one of the quality control processes. The
base of one of its products is made up of a metallic foil of a certain color that
has to meet quality standards, but producing it requires a complex process
where errors appear.
The project aims to use data collected from 11 sensors that measure the foil
wavelength to identify these errors. However, there is a challenge as there are
no established values for what is considered acceptable, and the sensors used
do not work in optimal conditions, which generates measurement errors in the
data set.
To tackle this challenge, extensive data analysis was performed to understand
the system. Different techniques and principles have also been applied for the
detection of anomalies, analyzing and comparing the results. Ultimately, a
prototype tool was developed to integrate these techniques and improve the
quality control process

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