Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

摘要

Taguchi’s design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (), feed (), and depth of cut (), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (). The machining is conducted with Taguchi L9 orthogonal array, and based on the analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, . Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, . Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach.