Machinability and parametric optimization of aluminum silicon carbide metal matrix composite (Al-SiC MMC) machined through µ-EDM

Aluminum silicon carbide metal matrix composite (Al-SiC MMC) is widely used because of its exceptional mechanical and thermal properties. Some engineering applications include aerospace, automobile, electronics, and medical devices. In the present investigation, aluminum 7075 alloy (Al-7075) as a matrix material with reinforcement particles of 10% silicon carbide (SiC) is fabricated using stir casting. The developed Al-SiC MMC is machined using an in-house developed micro-electro discharge machine (µ-EDM) setup. Experiments are carried out with input parameters—voltage (V), capacitance (µF), and pulse-on time (µs)—to analyze the responses such as hole depth (HD), material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and circularity error (CE). Taguchi L₁₆ orthogonal array is adopted to conduct 16 experiments with varying process parameters for 5 minutes’ duration with a copper tool electrode of Ø720 µm on the Al-SiC MMC workpiece of size 20 mm × 20 mm × 2.5 mm. The dielectric medium used for all experimentation is EDM oil. The resultant blind holes are characterized using scanning electron microscopy (SEM) images and a 3D profilometer. Later, the signal-to-noise (S/N) ratio technique is used to optimize the process parameters to enhance individual output responses. The obtained results are discussed in the article. Further, analysis of variance (ANOVA) is performed to find out the contribution of each parameter to the output responses. Grey relational analysis (GRA) is also used for multiobjective optimization to get quality blind holes. The best parametric combination obtained through GRA are at 28 V, 100 µF, and 100 µs, resulting in 823 µm of HD, 0.38 mg/min of MRR, 0.10 mg/min of TWR, 8.98 µm of SR, and 48.37 µm of CE.