Multi-Objective Optimization of Milling Process by Using Grey Fuzzy Logic Hybrid Approach

Cutting force investigation of the milling machine is one of the major areas for designs/manufacturing. In the present work influence of cutting parameters (speed, feed, and depth of cut) on cutting forces and Material removal rate (MRR) has been analyzed in a Milling machine. During the current study grey fuzzy logic method hybrid optimization technique is utilized to determine the optimal settings of milling process parameters with an aim to improve cutting force and material removal rate (MRR). Taguchi design of experiment techniques a total of 8 tests were carried out, optimum level for MRR and cutting force were chosen from the three levels of cutting parameters considered. Experimental were conducted on tool dynamometer and the influence of cutting parameter was studied using analysis of variance (ANOVA) based on adjusted approach. Grey relational analysis (GRA) combined with fuzzy-logic is used to determine grey fuzzy reasoning grade (GFRG). In the using for GFRG value the optimum level of machining parameters are calculated.