Surface Roughness, Flatness Error and Material Removal Rate Optimization in End Milling Operation Using Taguchi Method | ||||
| Engineering Research Journal (Shoubra) | ||||
| Volume 44, Issue 1, April 2020, Page 65-70 PDF (732.58 K) | ||||
| Document Type: Research articles | ||||
| DOI: 10.21608/erjsh.2020.405704 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| M. H. Hamad; E. H. Mansour; S. A. Zaian; A. M. Gaafer | ||||
| Mechanical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt. | ||||
| Abstract | ||||
| Taguchi design of experiments and analysis of variance (ANOVA) are introduced to investigate the effect of the end milling parameters on surface quality. Spindle speed, feed rate, number of flutes of end mill are selected as the control parameters. An aluminum silicon (Al-Si) alloy reinforced with different volume fraction of MWCNTs was used as a workpiece material. The machining responses were surface roughness, flatness error and material removal rate of the machined workpieces. An orthogonal array L27 of the Taguchi technique and S/N ration were selected to investigate and analyze the effect of the different control parameters on the process responses. The results of the study indicated that feed rate is the most significant factor on MRR, followed by number of flutes. Feed rate is the most significant factor on surface roughness followed by spindle speed. Number of flutes is the most significant factor on flatness error followed by spindle speed. The optimal levels of control parameters are determined from main effects plot for SN ratios for different responses, for maximum MRR (277.1363 mm3/min) at the optimal levels are A3 B2C1D3, for minimum surface roughness (0.492um) at level A2B2C3D1and minimum flatness error (0.064 um) at A3B3C2D1. | ||||
| Keywords | ||||
| End milling; Nanocomposites; Surface roughness; Flatness error- Design of experiments | ||||
|
Statistics Article View: 51 PDF Download: 21 |
||||
