DOI: 10.5937/jaes0-46706
This is an open access article distributed under the CC BY 4.0
Volume 21 article 1160 pages: 1203 -1214
In this work, the tool rotational speed (T), dielectric pressure (W), feed rate (F), and voltage (V) of the electrical discharge drilling (EDD) operation are optimized to decrease the extension of the drilled hole (EH) and improve the material removal rate (MRR). The Kriging models were utilized to present performance measures, while the Entropy approach and improved quantum-behaved particle swarm optimization algorithm (IQPSO) algorithm were employed to compute the weights and determine optimal factors. The findings presented that the optimal T, W, F, and V are 550 rpm, 36 kg/cm2, 30 µm/s, and 70 V, respectively. The EH is reduced by 33.0%, while the MRR is enhanced by 39.4%, as compared to the common values. The Kriging models provided acceptable accuracy for the prediction purpose. The V and F had significant impacts on the EH and MRR. The optimal data could be utilized to enhance the performance measures for the practical EDD process. The method comprising the Kriging, Entropy, and IQPSO was a prominent solution to deal with complicated optimization issues for the EDD operation.
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