Multi-Response Optimization in MQLC Machining Process of Steel St50-2 Using Grey-Fuzzy Technique

Abstract

In this paper MQLC turning process of steel St 50-2 is presented. Experimentations were performed using Taguchi L9 orthogonal array by varying two process parameters such as oil and water quantity while other parameters such as cutting speed, feed rate and depth of cut were kept constant. Process responses that were analyzed in this paper are surface roughness Ra and resultant cutting force Frez. In order to quantify significance of each process parameter on analyzed response ANOVA was conducted. Fuzzy logic modelling technique was used to describe the effects of process parameters and to create response surface plots. Finally, in order to find out process parameters values that lead simultaneously to optimal surface roughness and resultant cutting force, multi-objective optimization of process responses was conducted by using grey relational analysis (GRA) combined with fuzzy logic technique.