Investigation on the effect of hybrid nanofluid in MQL condition in orthogonal turning and a sustainability assessment

Abstract

The installation of cost- and energy-efficient chip removal processes is the key point for sustainability. In the literature, many sustainability assessments have been made for minimum quantity lubrication (MQL) and mono nanofluid-assisted MQL (N-MQL) methods, considering energy consumption and costs. However, there are deficiencies in the assessment of sustainability in terms of machining cost and carbon emission amount in studies using the hybrid nanofluid MQL (HN-MQL) method. In the presented study, the Taguchi experiment design was established with different cutting conditions (dry, MQL, 0.2% MWCNT nanoparticle reinforced N-MQL, 0.1% MWCNT+0.1% MoS2 nanoparticle reinforced HN-MQL), different cutting speeds (175, 225, 275 and 325 m/min), and different feed values (0.1, 0.15, 0.2 and 0.25 mm/rev) in the orthogonal turning of S235JR structural steel, and optimum cutting parameters were determined in terms of cutting temperature and cutting forces by ANOVA analysis. This was followed by the sustainability assessment of the experiments conducted to quantify the sustainability aspect of machining in terms of total machining costs and total carbon emissions. While assessing machinability parameters, it was found that the best results out of all the performed experiments for both cutting forces and cutting temperatures were obtained under N-MQL conditions. It was determined that the most effective parameter on cutting force and thrust force was feed with 86.8% and 65% contribution ratios, respectively, and cutting conditions had the most effect on cutting temperature with 93.2% contribution ratio. The total machining cost were lowered by significant amount (up to 76%, 73% and 61% in comparison with dry, MQL and HN-MQL) under N-MQL cutting environment owing to the reduction in energy consumption and better tool life in comparison with other parameters. The overall carbon emissions were also most optimal (better by up to 60% and 37% in comparison with MQL and HN-MQL) under the N-MQL cutting environment in comparison with other cutting environments. The sustainable aspects of the machining process were enhanced more under higher cutting speeds than under lower cutting speeds.