Track: Manufacturing and Design

Abstract

The research presented successfully applies fuzzy logic and Grey Relational Analysis (GRA) for optimization of turning process carried out on cylindrical bars of Aluminium 6061. Pre-recorded responses (Material Removal Rate & Surface Roughness) subject to three level control factor (Rake Angle, Feed Rate & Speed) variation in accordance with Taguchi’s L27 orthogonal array have been utilized for the present research. The data was converted into Grey Relational Coefficients (GRC) using larger-the-better and smaller-the-better techniques for MRR and surface roughness respectively. These GRCs were input into Mamdani type Fuzzy Inference System (FIS) to compute Multi Performance Characteristic Index (MPCI) and Signal to Noise (S/N) Ratios were calculated for each set of responses. Analysis of Variance (ANOVA) was carried out using Main Effects Plot of S/N ratios for MPCI to optimize the cutting parameters by maximization of MRR and minimization of surface roughness. The combination of cutting parameters, A1B3C3 i.e. rake angle of 2°, speed of 710 RPM and feed of 0.4 mm/rev was concluded as the optimum setting if the prime requirement is the maximization of MRR and A1B3C1, i.e. 2º rake angle, 710 rpm and 0.2 mm/rev when the prime requirement is the minimization of surface roughness for the given operation.