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Design and prototyping of new Machine Learning algorithms for Predictive Maintenance purposes

Miguel Angel Garcia Varela

Design and prototyping of new Machine Learning algorithms for Predictive Maintenance purposes.

Rel. Edoardo Patti, Santa Di Cataldo. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2020

Abstract:

The Thesis Objective is to study and test different Machine Learning Algorithms suitable for Predictive Maintenance. Posteriorly, joining forces with Zirak’s ML Backend architecture, to develop a prototype of a Predictive Maintenance Framework for Real Case Implementation. This framework should have modular Architecture that allows fast set up and deployment, high scalability and adaptability, also simple maintenance, in order to be effectively flexible against the variety of use cases in the Industry.

Relators: Edoardo Patti, Santa Di Cataldo
Academic year: 2019/20
Publication type: Electronic
Number of Pages: 64
Additional Information: Tesi secretata. Fulltext non presente
Subjects:
Corso di laurea: Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro)
Classe di laurea: New organization > Master science > LM-27 - TELECOMMUNICATIONS ENGINEERING
Aziende collaboratrici: Zirak S.r.l.
URI: http://webthesis.biblio.polito.it/id/eprint/15368
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