Multi optimization of nano fluid based machining of titanium alloy: A green manufacturing approach

Abstract

Environmental friendly machining (EFM) is an instrumental member of green manufacturing. Green manufacturing is the sub set of green engineering that sets goal for minimizing of pollution and waste. In machining, despite of advantages of cutting fluids it posses the risks of health hazards to machine operator and disposal of cutting fluid are one of the major challenges. Dry machining, mist lubrication and minimum quantity lubrication (MQL) are some of the approaches are being employed to minimize the use of cutting fluids. In this work, it has been attempted to present optimization study of machining parameters in turning commercially available Titanium alloy (grade 2) material using nano fluid based in MQL environment. The effect of three process parameters viz., cutting speed (v), feed rate (f) and tool approach angle (∅) on machining performance measure viz. surface roughness, cutting force, tool-chip temperature and tool wear are investigated. Box Behnken design of experimental runs with three factors at three levels each, requiring 27 experiments was used. Response surface methodology (RSM) based predicative modeling was developed to predict process responses and the effect of parameters was studied. ANOVA results show that v and f are found to be most influencing parameters on the process responses. Simultaneous optimization to minimize Ra, Fc, T and Vb using desirability analysis obtain optimum parameters as v = 200 m/min; f = 0.10 mm/rev; ∅ = 78.2 degree employing graphite nano fluid based machining environment. The validation of optimized result with experimental result shows a maximum error percentage of 9.22%.