Multi-Objective Optimization of Machining Parameters on Drilling of GFRP Composites using Hybrid GRA-PCA Techniques

In this research, exhibits an optimal combination of process parameters so as to minimize the surface roughness and circularity deviation during conventional drilling of GFRP composites. In order to multi-objective optimization of process parameters, taguchi based Grey relational analysis (GRA) coupled with principal component analysis (PCA)methodology has been proposed in this work. The number of experiments confirmed is based on L9 orthogonal array as per the taguchi method, depends on the control factors such as cutting speed, feed, specimen thickness and fiber orientation. From the ANOVA it reveals that cutting speed and feed are the most influencing parameters on surface roughness and circularity error. Using GRA multi response parameters are normalized and further applied PCA to evaluate the weighting values of corresponding responses. From the analysis the optimal combination of process parameters are selected.