Taguchi- Grey Theory Based Harmony Search Algorithm (GR-HSA) for Predictive Modeling and Multi-Objective Optimization in Drilling of Polymer Composites

This paper deals with a new hybridization methodology of Grey integrated Harmony search algorithm (GR-HSA) for predictive modeling. Simultaneously, parametric optimization during drilling of Graphite reinforced epoxy composites using the TiAlN coated SiC drill. Three process constraints namely spindle speed (N), feed (F), and wt.% of Graphite (G%), varied at four discrete levels, and Taguchi-based L-16 orthogonal array used for experimentation. Machining performance is considered as material removal rate (MRR), thrust force (Th), torque (T), and surface roughness (Ra). A statistical model was established between input and output functions. Multiple performances are aggregated into an objective function known as Grey relation grade (GRG). Non-linear regression analysis inveterates the fitness function to the implementation of the Harmony search algorithm. The outcome revealed that the GR-HSA module shows the higher application potential with an improvement of 3.55% over the traditional GRA-Taguchi method. Further, high resolution scanning analysis was made to evaluate the quality of the drilled hole. The results inferred that spindle speed in the case of GR-HSA (2500 rpm) increases the temperature between the machining interface, which softens the polymeric material of the machining zone. This, in turn, gives a lower value of thrust force with improved surface finishing. The results of the scanning test demonstrate the feasibility of the GR-HSA hybrid method.