Crossmark

Feasibility study on machine learning methods for prediction of process-related parameters during WAAM process using SS-316L filler material

Published Online: 2024-10-31

Published Print: 2024-12

Authors

Subadra, Sharath P. https://orcid.org/0000-0002-7558-638X
Mayer, Eduard

Wachtel, Philipp

Sheikhi, Shahram
Funding

Funding for this research was provided by:

Forschungszentrum Jülich

Bundesministerium für Wirtschaft und Klimaschutz

Hochschule für Angewandte Wissenschaften Hamburg (HAW Hamburg)
License Information

Text and Data Mining valid from 2024-10-31

Version of Record valid from 2024-10-31
More Information

Article History

Received: 15 August 2024

Accepted: 15 October 2024

First Online: 31 October 2024

Declarations

:

: The authors declare no competing interests.

Document is current