Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite
The mechanical, physical and interfacial properties of aluminum alloys are improved by reinforcing the silicon carbide particles (SiC<sub>p</sub>). Machinability of such alloys by traditional methods is challenging due to higher tool wear and surface roughness. The objective of research...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/abb4e6dcd73041c99e42a59e347331bf |
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| Sumario: | The mechanical, physical and interfacial properties of aluminum alloys are improved by reinforcing the silicon carbide particles (SiC<sub>p</sub>). Machinability of such alloys by traditional methods is challenging due to higher tool wear and surface roughness. The objective of research is to investigate the machinability of SiC<sub>p</sub> reinforced Al6061 composite by Wire-Electrical Discharge Machining (wire-EDM). The effect of wire-EDM parameters namely current (I), pulse-on time (T<sub>on</sub>), wire-speed (W<sub>s</sub>), voltage (I<sub>v</sub>) and pulse-off time (T<sub>off</sub>) on material removal rate (MRR) is investigated and their settings are optimized for achieving the high MRR. The experiments are designed by using Taguchi L<sub>16</sub> orthogonal arrays. The MRR obtained at different experiments are analyzed using statistical tools. It is observed that all the chosen process parameters showed significant influence of on the MRR with contribution of 27.39%, 22.08%, 21.32%, 15.76% and 12.94% by I, I<sub>v</sub>, T<sub>off</sub>, T<sub>on</sub> and W<sub>s</sub>, respectively. At optimum settings, the Wire-EDM resulted in MRR of 65.21 mg/min and 62.41 mg/min for samples with 4% and 8% SiC<sub>p.</sub> The results also indicated reinforcing SiC<sub>p</sub> upto 8% showed marginally low influence on MRR. Microstructural investigation of the cut surface revealed the presence of craters with wave pattern on its surface. The top surface of the crater is featured by the recast layers connecting adjacent craters. Further, the statistical model is developed using linear regression to predict the MRR (?<sup>2</sup>—73.65%) and its predicting accuracy is verified by the confirmation trials. The statistical model is useful for predicting the MRR for different settings of the process parameters. The optimized settings can be used to improve the machining productivity by increasing the MRR while machining of Al6061-SiC<sub>p</sub> (upto 8 wt. %) alloy by wire-EDM industries. |
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