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Abstract
Surface roughness is an important assessment of metal cutting. This paper presents an empirical investigation of cutting conditions on the surface roughness in hard milling SKD61 steel. The cutting speed, feed rate, depth of cut, and nanoparticle concentration were taken as the parameters in experimental setup. The mixer of SiO2 particles with a size of 100nm based on cutting oil CT232 was used with 3 levels of concentration: 0, 2, and 4wt%. Twenty-seven experiments were carried out based on the DOE method developed by G. Taguchi. The best model from response surface methodology (RSM) was developed regarding the surface roughness. Further analysis with ANOVA method was performed to confirm the significant of the achieved model as well as machining parameters. According to experiment results, the weight percent of nanoparticles concentration had a great impact on the surface roughness, only after the feed rate. Additionally, the excellent effectiveness in reducing the roughness of MQL nanofluid has been demonstrated when compared with conventional MQL.
Keywords
hard milling
hardened SKD61 tool steel
SiO2 nanoparticles
MQL
RSM
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