Abstract
This paper presents a novel approach in parametric optimization of machining LM 25 aluminium alloy by Taguchi based grey relational analysis. The optimization of cutting speed (V), feed rate (F), depth of cut (D), and cutting fluid flow rate (R) is performed taking into account the surface roughness (Ra) and the material removal rate (MRR). Ahonol- 7 is the cutting fluid utilized for machining operation. The optimum machining parameters are determined based on the grey relational grade (GRG) values. A statistical technique comprising of orthogonal array and analysis of variance (ANOVA) is employed in order to find the significant contribution of parameters. A Confirmation test is conducted in order to validate the optimal machining parameters. From this analysis, it is predicted that cutting fluid flow rate is the most influential parameter that affects the turning of LM 25 Aluminum alloy. Cutting fluid flow rate influences R (47.70%) more, followed by feed rate F (35.94 %), depth of cut D (12.16%) and cutting speed V (3.02 %).
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