Abstract
This paper emphases on the effect of various machining constraint on surface roughness and material removal rate in turning SiC reinforced Al alloy composite through taguchi orthogonal array based experimental analysis which has been further optimized using principal component analysis (PCA). Experimental investigation has been conducted under minimum quality lubricant (MQL) cutting environment. Palm oil has been used as lubricant where flow rate and pressure were kept at 120 ml/hr and 8 bar. The whole experiment has been designed using L25 orthogonal array having three input parameters and five different level to measure surface roughness and material removal rate. Taguchi S/N ratio-based optimization has been implemented where smaller the better criteria has been used for surface roughness whereas larger the better criteria has been used for material removal rate. From Analysis of variance, it is observed that cutting speed and feed rate are the most prominent factor for surface roughness. Nevertheless, Depth of cut and cutting speed are the most dominant factor for material removal rate. While comparing the predicted output values with experimental values, MAPE value is found in the range of 0.23 % for surface roughness and 0.045 % for material removal rate which is in very much tolerable range. Correlation coefficient value for experimental values of the resultant output is 0.98286 and 0.99869 respectively which signifies the effectiveness of the whole experiment. Subsequently, machining parameters were optimized using PCA technique. To attain satisfactory response values, depth of cut, cutting speed and feed rate need to be at 0.85 mm, 396 m/min and 0.16 mm/rev respectively. By applying the model, surface roughness of 0.7257 μm and MRR of 53856 mm3/min can be obtained. Keywords: SiC reinforced Al alloy; Turing; Minimum Quality Lubricant; Surface Roughness; MRR; Taguchi orthogonal array; Principal component analysis
Published Version
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