Multi-objective optimization of MQL mist parameters for eco-friendly grinding

Abstract

Nowadays, Minimum Quantity Lubrication (MQL) technique with eco-friendly groundnut oil is adopted in precision machining to tackle the operator health and environmental issues owing to petroleum based cutting fluid. The effectiveness of this technique depends on mixture quality of MQL mist. Hence, the objective of present work is to optimize the MQL mist parameters i.e. air pressure (P), flow rate (Q), and stand-off distance (ds) to minimize the effect of MQL based plunge grinding on hardened AISI H13 tool steel in terms of lowest grinding force, specific energy, grinding temperature, and surface roughness using grey relational analysis. Taguchi's L16 orthogonal array was utilized for conducting the final experiments and mist parameters varied through four levels include P (2, 3, 4, and 5 bar), Q (50, 100, 150, and 200 L/h) and ds (40, 50, 60, and 70 mm). Further, experimental analysis was carried out to compare the effect of optimal and worst mist parameters on ground surface and microchip by using microhardness, scanning electron microscope, and atomic force microscopy. According to validation test, P: 4 bar, Q:200 mL/h, and ds:50 mmare optimal mist parameters for multi-response variables of MQL grinding. Effective mist quality i.e. average droplet size of 51.03 μm was obtained at nozzle angle of 12°. Excellent ground surface quality with negligible microhardness variation and no wear tract microchip were observed under optimal mist setting. © 2020 The Society of Manufacturing Engineers