Abstract
Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology
Highlights
Waste fly ash reinforced aluminum matrix composites (AMC) are significant for their light weight, superior tribological properties, low material costs, savings in ash disposal costs, energy savings, environmental benefits and good corrosion resistance behavior (Rohatgi et al, 2006), for which they are increasingly being used in automobile, marine and aerospace industries (Anasyida et al, 2010).Due to some enormous properties like high wear resistance, low thermal expansion coefficient, good corrosion resistance, and improved mechanical properties at a wide range of temperatures, the Al-Si alloy was normally selected as matrix material (Saheb et al, 2001)
This paper describes the mathematical model developed by Multiple Linear Regression Analysis to predict the machinability characteristics at 95% confidence level by response surface and face centered central composite methodology
The metal matrix composite prepared with waste fly ash has shown better machining performance in comparison to that for virgin Al-Si alloy
Summary
Waste fly ash reinforced aluminum matrix composites (AMC) are significant for their light weight, superior tribological properties, low material costs, savings in ash disposal costs, energy savings, environmental benefits and good corrosion resistance behavior (Rohatgi et al, 2006), for which they are increasingly being used in automobile, marine and aerospace industries (Anasyida et al, 2010).Due to some enormous properties like high wear resistance, low thermal expansion coefficient, good corrosion resistance, and improved mechanical properties at a wide range of temperatures, the Al-Si alloy was normally selected as matrix material (Saheb et al, 2001). Some researchers evaluated the mechanical properties (Rohatgi et al, 2002; Bienias et al, 2003; Zuoyong Dou et al, 2007), thermal properties (Rohatgi et al, 2006), damping properties (Wu et al, 2006) and tribological properties (Surappa, 2008) with the use of fly ash as reinforcement in aluminum matrix composites (Senapati et al, 2015). These are difficult-to-machine materials due to the presence of very hard and brittle reinforcements, which. The results are analyzed using ANOVA technique, i.e. average surface roughness (Ra)and tool wear (VBc), while turning the composite in dry environment for the same machining parameters
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