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Material removal rate (MRR) and surface roughness are investigated.
The main parameter that determines the material removal rate in the process is the current intensity.
Surface roughness (Ra) and Material Removal Rate (MRR) were the output responses.
Analysis of variance (ANOVA) is employed to optimize the material removal rate and surface roughness.
Three objectives, such as surface roughness, material removal rate and cutting energy, are simultaneously optimized.
Its advantages compared to conventional abrasives are higher material removal rate and less wear.
Machining parameters which are investigated in this work are Material Removal Rate (MRR) and surface roughness.
The major performance characteristic that is evaluated is Material Removal Rate (MRR).
The results identify the most important parameters to maximize material removal rate and minimize surface roughness.
The machining simulation is carried out to predict the flank wear and material removal rate (MRR).
The measure of performance is undercut (UC) and material removal rate (MRR).
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