The influence of magnetic field on the material removal rate in electrochemical machining process
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Production Engineering and Metallurgy Dept., University of Technology – Iraq, Alsinaa street,10066 Baghdad, Iraq
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lara A. Salman
Production Engineering and Metallurgy Dept., University of Technology – Iraq, Alsinaa street,10066 Baghdad, Iraq
Adv. Sci. Technol. Res. J. 2025; 19(5):356-365
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ABSTRACT
One of the most advanced techniques for dealing with metal is electrochemical machining (ECM). Objects that are hard or impossible to make with traditional machining techniques can be machined utilizing this method. However, in order to increase performance and economy, new ECM approaches must be developed because to the growing need for complex components in industries like aerospace, automotive, and medical devices. Thus, the main goal of this study is to ascertain how the ECM affects the material removal rate (MRR) in the presence of a magnetic field. In particular, the tool was composed of copper, and the workpiece was formed of aluminum 6061 alloy, Al-Sic, and Al-B4C using a stir casting technique. The voltage, gap, electrolyte concentration, and material type are among the input process factors that are changed during the experiment. The software used was Minitab to examine the results of the Taguchi design experiment, which employed orthogonal arrays. On the basis of the Taguchi design, the process parameters were improved. Specifically, four input variables were examined in this experiment, each having values at the three-factor level.
According to the findings, the voltage was the most important factor. It contributed 50.12% for MRR without a magnetic field and 56.02% with one. The concentration came in second with 16.73% and 24.03% (without and with magnetic field), followed by the gap with 19.02 percent and 11.60% (without and with magnetic field), and the material type came in last with 1.35% and 0.57% (without and with magnetic field). Furthermore, the regression model's overall accuracy for the majority of experiments indicates that it is reasonably accurate with percent errors typically less than 1%.