Taguchi-fuzzy multi-response optimization in fly cutting process and applying in the actual hobbing process

Abstract

Applying nanofluid made by adding alumina nanoparticles to industrial oil may reduce the cutting force, friction, and cutting temperature and, from that, improve the tool life in the hobbing process. However, it is difficult to set up the experiment for the actual gear hobbing process, because measuring the cutting force and temperature in the hobbing process is very complicated and expensive. Therefore, a fly hobbing test on the horizontal milling machine was performed to simulate the actual hobbing process.

In this research, the fuzzy theory was combined with the Taguchi method in order to optimize multi-responses of the fly hobbing process as the total cutting force, the force ratio F_z/F_y, the cutting temperature, and the surface roughness.

The optimal condition—A1B1C3 (the cutting speed 38?mpm\, the nanoparticle size 20?nm, and concentration 0.5%)—was determined by analyzing the performance index (FRTS) of the fuzzy model. Furthermore, this condition was applied to the actual hobbing process in the FUTU1 Company and compared with the actual conditions of this company and other conditions using the nanolubricant with 0.3% Al₂O₃, 20?nm. The results show that it can reduce a maximum 39.3% of the flank wear and 59.4% of the crater wear on the hob when using the optimal conditions.

The study indicates that the optimal condition determined by using Taguchi-Fuzzy method can be applied in the FUTU1 company with the high efficiency.