Abstract
In this study an experimental investigation of effects of cutting parameters on surface roughness during end milling of aluminium 6061 under dry condition and minimum quantity lubrication (MQL) condition were carried out. Spindle speed (N ), feed rate (f ), axial depth of cut (a ) and radial depth of cut (r ) were cutting parameters chosen as input variables in the investigation of the surface roughness quality. The experimental design adopted for this study was the central composite design (CCD) of response surface methodology. Thirty samples were run in a CNC milling machine for each condition and the surface roughness measured using Mitutoyo surface tester. A comparison showing the effects of cutting parameters on the surface roughness for dry and MQL conditions in end-milling of aluminium were evaluated. Surface roughness values for MQL condition were lower with up to 20% reduction when compared to dry conditions. MQL cutting condition was found to be better and more reliable because it is environmentally friendly and gives better surface finish. With the obtained optimum input parameters for surface roughness, production operations will be enhanced.
Highlights
The quality of machined surface is characterized by the accuracy of its manufacture with respect to the dimensions specified by the designer
The experimental plan was developed to assess the influence of spindle speed (N), feed rate ( f ), axial depth of cut (a) and radial depth of cut (r) on the surface roughness parameters (Ra)
The thirty experiments are carried out according to the blocked central composite design (CCD)
Summary
The quality of machined surface is characterized by the accuracy of its manufacture with respect to the dimensions specified by the designer. Central composite design (CCD) of response surface methodology (RSM) was employed to create an efficient analytical model for surface roughness in terms of cutting parameters: cutting speed, axial depth of cut, and feed per tooth. Arokiadass et al [13] studied the influence of four machining parameters including spindle speed (N), feed rate ( f ), depth of cut (d), and various percentage weight of silicon carbide (S) on surface roughness (Ra). The RSM was employed to establish the mathematical relationship between the response and the various process parameters The result they obtained showed that the quadratic model was statistically significant for analysis of surface roughness. The mathematical model developed by using least square approximation method shows accuracy of 89.5% which is reasonably reliable for surface roughness prediction
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