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Machining characteristics of various powder-based additives, dielectrics, and electrodes during EDM of micro-impressions: a comparative study

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submitted on 2025-05-27, 07:31 and posted on 2025-05-27, 07:32 authored by Kashif Ishfaq, Muhammad Asad Maqsood, Muhammad Arif Mahmood

Electric discharge machining (EDM) has great acceptance in different application sectors to wipe out intrinsic problems, like product miniaturizing and tight tolerances, during the fabrication of micro-size products. Many researchers have worked well in the micro-cutting of various alloys through the EDM process. However, limited work has been reported on the EDM of SS 316 for micro-impression fabrication using EDM. The selection of the best dielectric, electrode material, and powder-based additives has never been targeted so far to have dimensionally accurate micro-impression at an appreciable cutting rate with no/less electrode damage in the EDM of the said alloy. Therefore, in this research, the collective influence of various dielectrics (kerosene oil, transformer oil, and canola oil), powders (alumina, graphite, and silicon carbide), and electrodes (copper, brass, and aluminum) have been comprehensively examined for the fabrication of micro-impressions in AISI 316 using EDM. Taguchi L9 orthogonal technique was applied to study the effect of four input parameters on material removal rate, overcut, and tool wear rate. Results were statistically explored using main effect plots and supplemented by scanning electron microscopy, surface profilometry, and optical microscopy. The results show that material removal and tool wear rates notably improved from the mean value by 29% and 89.4%, respectively, when the machining is carried out under silicon carbide mixed kerosene dielectric against silicon carbide the aluminum tool at a pulse time ratio of 1.5. Furthermore, for dimensional overcut, 5.3 times lesser value is observed from the average magnitude of 0.189 mm when the proposed EDM setup is employed for cutting AISI 316. An optimized setting has also been proposed by grey relational analysis and then validated through a confirmation experiment.

Other Information

Published in: The International Journal of Advanced Manufacturing Technology
License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: https://dx.doi.org/10.1007/s00170-022-10254-8

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Springer Nature

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Texas A&M University at Qatar

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