LAUSR

Abstract Eco-efficiency solutions have been more and more proposed by researcher and industry around the world in latest years in order to become the manufacturing systems cleaner and greener. This action is related to the global warning about the generation of greenhouse gases (GHGs), like CO2, as reported by Intergovernmental Panel on Climate Change (IPCC) . One of the most hazardous issue related to environmental risk in machining process is the application of metalworking fluids (MWFs), especially in grinding process in which MWFs are pivotal to control high generation of heat and avoid workpiece surface burns and microstructural changes. The minimum quantity lubrication (MQL) was broadly reported in the literature as a potential alternative lubri-cooling technique to the conventional technique (flood - F). However, the main drawback of MQL grinding is related to high generation of clogging phenomenon produced by the chips lodged on the grinding wheel active surface (GWAS) due to the low oil volume and consequently the low lubricating and cooling action. In order to propose improvements on MQL technique, increase its efficiency and viability and develop a potential greener lubri-cooling technique, this work aims to propose and evaluate the application of hybrid HMQL + WCJ technique combined oil and water at 1:5 oil-water in the Al2O3 grinding process of AISI 4340 steel. This technique was compared to flood F and the pure PMQL + WCJ (pure oil) techniques. Both MQL techniques (hybrid and pure) employed at 30, 60 and 120 mL/h. The PMQL + WCJ technique produced the worst results irrespective of the flow rate. The HMQL + WCJ at 120 mL/h (highest flow rate) presented similar performance to the F technique in terms of surface roughness, microhardness, clogging behavior on GWAS, workpiece form deviation, grinding power, generation of CO2 during the process and acoustic emission (AE) and outperformance in terms of G ratio. This indicates the eco-efficient potential to be widely employed in manufacturing industry and mitigate the environmental impact and carbon footprint of hybrid MQL + WCJ technique.