Parametric Optimization of Cylindrical Grinding Process through Hybrid Taguchi Method and RSM Approach using Genetic Algorithm

The present investigation proposes a hybrid technique: Taguchi method, response surface methodology (RSM) and genetic algorithm (GA), to analyze, model and predict vibration and surface roughness in traverse cut cylindrical grinding of aluminum alloy. Experiments have been conducted as per L9 orthogonal array of Taguchi methodology using several levels of the grinding parameters. Analysis of variance has been done to identify the influential process parameters on output variables. RSM has been applied to develop relationship between output responses with input parameters. Multi-objective overlaid contour plots have been made to study the interaction effects on both responses simultaneously. Developed models are then solved individually, first and then combinedly by GA, for process optimization. Predicted output responses are then confirmed by confirmatory experiments.