ANALYSIS OF MACHINING CHARACTERISTICS OF Al7075 HYBRID METAL MATRIX COMPOSITES
Prof. Naveenkumar .K
, Prof. Vinoth .R
Al7075, HMMC, EDM, SiC, TiC, Surface Roughness and Material Removal Rate.
The composite materials are extensively used globally in major industries. It is very difficult to machine the metal matrix composite materials impeded with reinforcement by conventional machining methods [1]. Hence non conventional machining techniques are employed to overcome these difficulties. The influence of process parameters of Electrical discharge machining such as current, pulse on- time and pulse -off time on Metal Removal Rate (MRR) and Surface Roughness (SR) were analysed for Al7075 hybrid metal matrix composite reinforced with Silicon carbide (SiC) and Titanium carbide (TiC) in this paper. The hybrid metal matrix composite was fabricated using stir casting process and machining was performed by EDM using copper tool with the machining parameters and the run order obtained from design expert software [3]. The machining characteristics for different set of experiments were analysed. The optimum parameters were identified with the help of design expert software and the optimum values were verified. It has been observed that the metal removal rate decreases when the weight fraction of reinforcement increases and surface roughness increases.
"ANALYSIS OF MACHINING CHARACTERISTICS OF Al7075 HYBRID METAL MATRIX COMPOSITES", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.565 - 572, May-2016, Available :https://ijsdr.org/papers/IJSDR1605108.pdf
Volume 1
Issue 5,
May-2016
Pages : 565 - 572
Paper Reg. ID: IJSDR_160343
Published Paper Id: IJSDR1605108
Downloads: 000347058
Research Area: Engineering
Country: Kanjikoil, Erode (D.T), Tamil Nadu, Indian
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave