This paper presents an experimental investigation on the coated carbide cutting tool performance of aluminium alloy AA6061-T6 machining through end mill processes using the minimum quantity lubrication (MQL) technique. The process parameters including the cutting speed, depth of cut and feed rate are selected. The effect of the base fluid ratio (water: EG) to the hybrid nanocoolant was investigated in this experiment. The hybrid nanocoolant with 80:20 of volume concentration up to 0.1% was prepaid with a 21 nm particle size of TiO2 and 10-30 nm ZnO nanoparticle for measurement purposes and tested at cnc end milling machines. The analysis of the variance method is utilised to validate the experimental data and to check for adequacy. The response surface method was used to develop the mathematical models and to optimise the machining parameters. It is observed that the material removal rate depends significantly on the depth of cut and feed rate, followed by the spindle speed. The results can be used as an example of the minimum quantity lubricants (MQL) technique applied to the machining of aluminium alloys, providing economic advantages in terms of reduced the machining costs and better machinability.

This paper presents the optimization of the grinding parameters of ductile cast iron in wet conditions and with the minimum quantity lubrication (MQL) technique. The objective of this project is to investigate the performance of ductile cast iron during the grinding process using the MQL technique and to develop artificial neural network modeling. In this project we used the DOE method to perform the experiments. Analysis of variance with the artificial neural network method is used to investigate significant effects on the performance characteristics and the optimal cutting parameters of the grinding process. Ductile cast iron was used in this experiment and the ethanol glycol was applied in the conventional method and compared with the MQL method. During conventional grinding, a dense and hard slurry layer was formed on the wheel surface and the performance of the ductile cast iron was very low, threatening the ecology and health of the workers. In order to combat the negative effects of conventional cutting fluids, the MQL method was used in the process to formulate modern cutting fluids endowed with user-and eco-friendly properties. Aluminum oxide was used as the grinding wheel (PSA-60JBV). This model has been validated by the experimental results of ductile cast iron grinding. Each method uses two passessingle-pass and multiple-pass. The prediction model shows that depth of cut and table speed have the greatest effect on the surface roughness and material removal rate for the MQL technique with multiple-passes by showing improved surface roughness, preventing workpiece burning and enabling a more friendly environment. Thus, various other parameters need to be added for further experiments, such as the wheel speed, distance from the wheel to the workpiece zone contact, and the geometry of the nozzle.