Experimental and Statistical Investigation of the Effect of Nanoparticle Minimum Quantity Lubrication (nano-MQL) Method on Cutting Performance

Authors : Fuat Kara

Pages : 102-113

View : 29 | Download : 77

Publication Date : 2024-04-30

Article Type : Research Paper

Abstract :In this study, two distinc cutting tools, coated carbide and cermet, were used in turning 20NiCrMo2 case-hardened steel. Turning experiments were carried out with these tools at three distinc cooling methods (dry, MQL, nano-MQL), three distinc cutting speeds (80, 120, 160 m/min) and three distinc feed rates (0.125, 0.167, 0.2 mm/rev) has been carried out. As a result of the experiments, the effects of cutting parameters, cutting tool type and cooling method type on the average surface roughness (Ra) and cutting zone temperature (Ctemp) were examined. In the study, the Taguchi optimization method was also applied to the experimental Ra and Ctemp results. As a result of Taguchi optimization, the most effective cutting parameters on Ra and Ctemp were determined. This result was confirmed by ANOVA analysis. Optimum parameters for Ra; cermet cutting tool, nano-MQL cooling method, 160 m/min cutting speed and 0.12 mm/rev feed rate. Optimum parameters for Ctemp; carbide cutting tool, nano-MQL cooling method, 80 m/min cutting speed and 0.12 mm/rev feed rate. Ideal numbers for both Ra and Ctemp were not found in the 18 turning experiments performed. Therefore, the 19th experiment was conducted for both output parameters. The average surface roughness value for optimum parameters was measured as 1.08 µm. For optimum parameters, the cutting zone temperature was measured as 122 °C.
Keywords : ANOVA, MQL, nano MQL, Kesme sıcaklığı, Taguchi analizi, Yüzey pürüzlülüğü