An Hybrid Taguchi -Grey Relational Technique and Cuckoo Search Algorithm for Multi Criteria Optimization in Hard Turning of AISI D3 Steel

In this work, under varying machining conditions the performance of multilayered coated carbide inserts are experimentally investigated using a hybrid Taguchi-Grey relational analysis. Two multi-layered coated inserts TiN/TiCN/Al2O3 and TiN/TiCN/Al2O3/TiN are used for turning AISI D3 Die steel. Taguchi?s mixed level of Design of Experiments (DoE) are used, for machining parameters varied through four levels and coated cutting inserts varied through two levels, an L16 Orthogonal Array (OA) is selected. Experiments were conducted on a CNC turning centre and output responses flank wear, surface roughness and Material Removal Rate (MRR) are determined. For multi-response optimization, initially Signal-to-Noise (S/N) ratio is calculated and then Grey Relational Analysis (GRA) is applied to simultaneously optimize the output responses. Significance of input parameters on the overall grey relational grade is evaluated using Analysis of Variance (ANOVA). Empirical models are developed for the grey relational grade to predict the output responses using multiple linear regression models. Confirmation experiment performed with the optimum conditions shows a reduction in flank wear and surface roughness with an increase in MRR.