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  KEYWORD

Machine learning techniques to evaluate the performance of drilling machines and supporting predictive maintenance through IoT

azienda Tesi esterna in azienda    


Parole chiave INDUSTRY 4.0, MACHINE LEARNING, AI, IOT, MACHINE LEARNING, MAINTENANCE PROCEDURES

Riferimenti ALESSANDRO RIZZO

Riferimenti esterni Dr. Elia Abdo, Drillmec S.p.A.

Tipo tesi APPLIED, EXPERIMENTAL, INDUSTRIAL, INTERNSHIP

Descrizione The thesis will explore machine learning techniques to evaluate the performance of drilling machines and supporting predictive maintenance through IoT. The student is expected to move at the industry sit in Gariga di Podenzano (Piacenza). A monthly reimbursement will be allocated. The selection will be performed by the company.


Scadenza validita proposta 04/07/2021      PROPONI LA TUA CANDIDATURA