DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.
Title: Parametric optimization of rice husk ash, copper, magnesium reinforced aluminium matrix hybrid composite processed by EDM
Authors: Ram Narayan Muni, Jujhar Singh, Vineet Kumar, Shubham Sharma
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2019
Volume: 14
Issue: 22
Language: English
Industries have a challenge to develop material which is less costly, high strength, more hardness and more toughness and can be drawn from the wastage of any agro product. Further, production of complex shapes in such hard to machine material by traditional method is another challenge. In this study, the 3weight% (wt.%) Cu particulates were added with 6, 8 and 10wt.% Rice Husk Ash (RHA) to prepare the reinforcing phase and Al 6061 alloy was used as a matrix to fabricate auminium matrix hybrid composites using stir casting method. The 1wt. % Mg was added to improve the wettability between the Al matrix and reinforcements. Electric Discharge Machining (EDM) is considered as an important process for machining of such kind of materials. The objective of this work is to investigate the effect of different factors like Workpiece electrode (W), Peak current (I), Voltage (V), Duty factor (t), Pulse-on time (Ton), and Flushing pressure (P) with brass electrode on metal removal rate (MRR) on the machining of aluminium matrix hybrid composites by EDM using Taguchi’s approach. The L27 orthogonal array (OA), for the six factors at three levels each, was opted to conduct the experiments and ANOVA and S/N ratios were applied to identify the significant parameters and optimization of EDM parameters for maximum MRR. The S/N ratio response graph clearly indicated that MRR decreased with increase in the wt. % of RHA. It is also reported that MRR increased significantly with an increase in discharge current. The Scanning Electron Microscope (SEM) was used for microstructural characterization of machined specimens.
Loading PDF...
Loading Statistics...