Abstract
This work investigates the importance of micro-drilling in Hybrid aluminum metal matrix composites (HAMMCs), particularly for the aerospace and automotive industries. The HAMMCs (AA7075/5% ZrB2/2% fly) ash was fabricated using the ultrasonic assisted stir casting method. Taguchi’s design of experiments is employed to optimize the material removal rate (MRR) and tool wear rate (TWR). Analysis of variance (ANOVA) is then used to determine the significance of the model. The study also utilizes a hybrid artificial neural network-genetic algorithm (ANN-GA) approach to optimize both MRR and TWR. By optimizing machining processes for HAMMCs, manufacturers can achieve high-precision micro holes. The optimal input parameters were found to be a feed rate of 10 μm sec−1, a capacitance of 1 nF, and a voltage of 85 V, achieving the minimum TWR and maximum MRR.
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