Taguchi-based optimization of CNC turning parameters to enhance surface finish of AISI 1045 steel

Abstract

Surface roughness is a critical indicator of machining quality, directly affecting the functional performance and service life of manufactured components. This study aims to optimize the surface roughness of AISI 1045 steel by varying parameters (cutting speed, feed rate, and depth of cut) using Taguchi L9 orthogonal array. Experiments were conducted on a FANUC 0i-Mate CNC lathe using Al-TiN-coated VNMG inserts. Moreover, the surface roughness was measured in accordance with ISO standards. Analysis of Variance (ANOVA) revealed the depth of cut was the most influential factor (45.21%), followed by cutting speed and feed rate. The Signal-to-Noise (S/N) ratio was identified as optimal surface roughness of 0.323 µm (N5 grade) at the parameter, with a cutting speed of 240 mm/min, a feed rate of 0.2 mm/rev, and a depth of cut of 0.6 mm. The novelty of this study is the demonstration that Taguchi's design and ANOVA combined can achieve reliable optimization results with considerably reduced experimental effort and offer practical industrial deployment, including for Small and Medium-sized Enterprises (SMEs).