Hybrid GRA-PCA and modified weighted TOPSIS coupled with Taguchi for multi-response process parameter optimization in turning AISI 1040 steel

Hybrid GRA-PCA and modified weighted TOPSIS coupled with Taguchi for multi-response process parameter optimization in turning AISI 1040 steelThe objective of the present study is to optimize multiple process parameters in turning for achieving minimum chip-tool interface temperature, surface roughness and specific cutting energy by using numerical models.The proposed optimization models are offline conventional methods, namely hybrid Taguchi-GRA-PCA and Taguchi integrated modified weighted TOPSIS.For evaluating the effects of input process parameters both models use ANOVA as a supplementary tool.Moreover, simple linear regression analysis has been performed for establishing mathematical relationship between input factors and responses.A total of eighteen experiments have been conducted in dry and cryogenic cooling conditions based on Taguchi L18 orthogonal array.The optimization results achieved by hybrid Taguchi-GRA-PCA and modified weighted TOPSIS manifest that turning at a cutting speed of 144 m/min and a feed rate of 0.16 mm/rev in cryogenic cooling condition optimizes the multi-responses concurrently.The prediction accuracy of the modified weighted TOPSIS method is found better than hybrid Taguchi-GRA-PCA using regression analysis.