Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches
Eidan, A., Mansour, E., Zaian, S. (2019). Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches. EKB Journal Management System, 41(1), 40-46. doi: 10.21608/erjsh.2019.406647
A. A. Eidan; E. H. Mansour; S. A. Zaian. "Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches". EKB Journal Management System, 41, 1, 2019, 40-46. doi: 10.21608/erjsh.2019.406647
Eidan, A., Mansour, E., Zaian, S. (2019). 'Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches', EKB Journal Management System, 41(1), pp. 40-46. doi: 10.21608/erjsh.2019.406647
Eidan, A., Mansour, E., Zaian, S. Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches. EKB Journal Management System, 2019; 41(1): 40-46. doi: 10.21608/erjsh.2019.406647

Optimization of the Machining Parameters for Surface Roughness and Flatness of Aluminum Silicon Alloy reinforced by Aluminum Oxide Nano Particulates in End Milling Using Taguchi and ANOVA Approaches

Engineering Research Journal (Shoubra)
Volume 41, Issue 1, July 2019, Page 40-46  XML PDF (639.44 K)
Document Type: Research articles
DOI: 10.21608/erjsh.2019.406647
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Authors
A. A. Eidan; E. H. Mansour; S. A. Zaian
Mechanical Engineering Department, Shoubra Faculty of Engineering, Benha University, Cairo, Egypt.
Abstract
In this paper, Taguchi method has been used to identify the optimal combination of influential factors in the end milling process. The experiments have been performed on aluminum silicon (Al-Si) alloy reinforced by aluminum oxide nanoparticles. A Taguchi orthogonal array L27 was selected for various combinations of different controllable factors (number of flutes of end mill, volume fraction of nanoparticles, spindle speed and feed rate). The process responses, i.e. surface roughness, material removal rate(MRR) and flatness error are measured and recorded for each experiment. The results are analyzed by Taguchi S/N ratio and then the optimal combination of controllable factors and their contributions are identified. The results showed that, minimum surface roughness(Ra= 0.736um) was obtained at optimal parametric combination is A2B2C3D1, for maximum (MRR= 291.97080mm3/min), optimal levels are A3 B2C1D3while minimum flatness error(0.080μm) was obtained at level A2B3C2D3.The result from ANOVA showed that feed rate was the most significant parameter on surface roughness. Feed rate was the most significant parameter on MRR followed by volume fraction of nanoparticles. The most significant parameter on flatness error was number of flutes followed by volume fraction of Al2O3 nanoparticles.
Keywords
End milling; Nanocomposites; Surface roughness; Flatness error; ANOVA
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