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Abstract
The present paper depicts an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the machining factors in turning of titanium (Grade-II) alloy using cubic boron nitride insert tool under minimum quantity lubricant (MQL) environment. The three machining factors, i.e., cutting speed (Vc), feed rate (f) and side cutting edge angle (approach angle π), are designed as three factors by using RSM design, which is withal subject to several constraints including tangential force (Fc), tool wear (VBmax), surface roughness (Ra) and tool-chip contact length (L). The multiple regression technique was used to establish the interaction between input parameters and given responses. Moreover, the results have been presented and optimized process parameters are acquired through multi-response optimization via desirability function as well as the PSO technique. The lower values of Vc (200 m/min), f (0.10 mm/rev) and higher values of ϕ (90°) are the optimum machining factors for minimizing the aforementioned responses. It was also observed that the selected responses predicated on PSO are much closer as that of the values acquired in view of the desirability function approach. Henceforth, PSO has the potential to cull appropriate machining factors while turning titanium (Grade-II) alloys under MQL conditions.