PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

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

azienda Thesis in external company    


keywords INDUSTRY 4.0, MACHINE LEARNING, AI, IOT, MACHINE LEARNING, MAINTENANCE PROCEDURES

Reference persons ALESSANDRO RIZZO

External reference persons Dr. Elia Abdo, Drillmec S.p.A.

Thesis type APPLIED, EXPERIMENTAL, INDUSTRIAL, INTERNSHIP

Description 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.


Deadline 04/07/2021      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti