Influence of Wire Type on WEDM Machining Performance of Inconel 718
Wire Electrical Discharge Machining (WEDM) is a promising method for machining superalloys, such as Inconel 718, which is widely used in aerospace and high-performance applications. This study focuses on wire selection for Inconel 718 machining with WEDM. In this work, three types of wire—brass wire, copper wire with ZnCu coating, and plain copper wire—have been evaluated for their effects on machining productivity, quality, and their influence on the property of the processed surface. A series of experiments was designed and conducted. The experimental results reveal that ZnCu-coated copper wire achieved the highest productivity and demonstrated the best capability for controlling the recast layer. However, the WEDM process caused a reduction in hardness on both the machined surface and subsurface area, as well as some Zn and Cu contamination, regardless of the wire type. Moreover, similar residual tensile stress in the normal direction was detected on the machined surface, with no significant shear stress observed. These findings indicate that, among the three types of wire in this study, ZnCu-coated copper wire is the optimal choice for machining Inconel 718 in WEDM. This work provides a valuable reference for future wire selection in Inconel 718 machining with WEDM.
Authors
- Xiaoming Duan (ORCID: https://orcid.org/0000-0002-3668-0912)
- J.M. Ramos
- Ízaro Ayesta (ORCID: https://orcid.org/0000-0002-0873-9040)
- S. Caneda (ORCID: https://orcid.org/0009-0004-4295-6657)
- Jun Wang (ORCID: https://orcid.org/0000-0002-7574-9468)
- Xiaodong Yang (ORCID: https://orcid.org/0000-0003-3689-0976)
Institutions
- Harbin Institute of Technology (CN)
- ONA Electroerosion (Spain) (ES)
- Achucarro Basque Center for Neuroscience (ES)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.01.116
- Citations
- 1
- Primary Topic
- Advanced Machining and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- Agencia Estatal de Investigación