Sustainability and carbon emissions assessment in nanofluids-assisted MQL turning of AISI 316 L stainless steel

Abstract

Machining hard-to-cut materials such as AISI 316 L austenitic stainless steel remains challenging due to the high cutting forces and severe thermal conditions involved. In this study, sustainable turning experiments were carried out under three lubrication conditions: dry cutting, minimum quantity lubrication (MQL), and MQL assisted with multi-walled carbon nanotube (MWCNT) nanofluids, at varying cutting speeds (Vc) and feed rates (f). Cutting forces were experimentally measured and subsequently used to analytically estimate both the total carbon emissions (CO2) and the overall machining costs. A multi-objective optimization model was then developed to simultaneously minimize CO2 emissions (Kg CO2) and machining cost ($). The optimal machining parameters were found to be a cutting speed of 130 m/min and a feed rate of 0,16 mm/rev, achieved under MWCNT-assisted MQL for minimum CO2 emissions, and under dry cutting for minimum machining cost. These results highlight the potential of nanofluid-assisted MQL to enhance both the sustainability and efficiency of turning stainless steels.