An Original Machine Learning-Based Approach for the Online Monitoring of Refill Friction Stir Spot Welding: Weld Diagnostic and Tool State Prognostic-Reference-Cited by-同舟云学术

An Original Machine Learning-Based Approach for the Online Monitoring of Refill Friction Stir Spot Welding: Weld Diagnostic and Tool State Prognostic

Published:2023-03-27 Issue: Volume: Page:
ISSN:1059-9495
Container-title:Journal of Materials Engineering and Performance
language:en
Short-container-title:J. of Materi Eng and Perform

Author:

Dahmene Fethi^ORCID,Yaacoubi Slah,El Mountassir Mahjoub,Porot Gaëlle,Masmoudi Mohamed,Nennig Pascal,Suhuddin Uceu Fuad Hasan,Dos Santos Jorge Fernandez

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://link.springer.com/content/pdf/10.1007/s11665-023-08102-1.pdf

Reference55 articles.

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4. U. Suhuddin, R. Mesquita, and J.F. Santos, Friction Spot Welding of Similar Aluminum Alloys AA6082-T6 for Application in Automotive Industry. Int. Automot. Congr.-IABC. (2016)

5. E. Boldsaikhan, S. Fukada, M. Fujimoto, K. Kamimuki, and H. Okada, Refill Friction Stir Spot Welding of Surface-Treated Aerospace Aluminum Alloys with Faying-Surface Sealant, J. Manuf. Process., 2019, 42, p 113–120.