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Development of a predictive maintenance model based on combination of physics-based and data-driven methods: Comparison of R and Python implementation performances

Gayratkhuja Akhrarov

Development of a predictive maintenance model based on combination of physics-based and data-driven methods: Comparison of R and Python implementation performances.

Rel. Franco Lombardi, Giulia Bruno. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2022

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Abstract:

I am really keen to work in this field due to 2 years of experience as a CAD CAM engineer and my current study in Engineering and Management faculty. For me, it would be a great challenge to deepen in the field of PLM in order to build my career in the field of Industry 4.0. In addition, my Bachelor’s degree in Computer Engineering and current ongoing additional study of MachineLearning and Cloud computing will make this research topic even more attractive to me. Thank you for the opportunity.

Relators: Franco Lombardi, Giulia Bruno
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 38
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: Politecnico di Torino
URI: http://webthesis.biblio.polito.it/id/eprint/24315
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