Turning is one of the precise machining processes, which are widely used at present for many industrial applications. Titanium alloy Ti6Al4V is widely implemented in the field of aerospace, structural, automotive and biomedical applications. In this study, the most significant factor of Cutting Force, Cutting Temperature and Material Removal Rate is considered the most responsible for determining the desirable input factors to the titanium Ti6Al4V alloy in the turning process. Initially, the design of the experiment was conducted for speed, cutting feed, axial depth of cut and the environmental eco-friendly coolant oil concentration of Multi-Walled Carbon Nanotubes nano-fluid are input parameters of machining process were studied in turning of titanium Ti6Al4V alloy to achieve sustainable production. Desirability Function Analysis was used to predict the mathematical model and ANOVA was used to analyze the contribution percentages of the machining parameters. Since the influence of the machining parameters of the Cutting Force, Tool Temperature and Material Removal Rate are conflicting in nature; the problem was considered a Multi-objective evaluator algorithm-based analysis of the problem. Hence, Desirability Function Analysis was adapted to predict the optimal set of input parameters. The interactive plots reveal that MWCNT’s nanofluid improves the result in terms of the maximum rate of removed material with minimum cutting force and cutting temperature. Based on multi-objective optimizations of RSM based DFA the optimal results confirm that 1% of MWCNT’s concentration reduces the cutting temperature and improves the removal of material when MWCNTs are used as cutting fluid

Keywords: Ti-6Al-4V, MWCNT, RSM, MRR, DFA, ANOVA etc