Crossmark

Machine Learning-Driven Approach for Reducing Tool Wear in Die-Sinking Electrical Discharge Machining

Crossref DOI link: https://doi.org/10.1007/s13369-025-10010-6

Published Online: 2025-02-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Cogun, Can

Ayli, Ece https://orcid.org/0000-0002-6209-161X
Funding

Funding for this research was provided by:

Cankaya University
License Information

Text and Data Mining valid from 2025-02-10

Version of Record valid from 2025-02-10
More Information

Article History

Received: 27 May 2024

Accepted: 23 January 2025

First Online: 10 February 2025