Surface roughness optimization of milling process of AISI 1045 steel with Taguchi technique

Abstract

This study aims to optimize milling parameters depend on the Taguchi method for minimizing surface roughness (Ra). The experiments were conducted using the L18 orthogonal array in a CNC milling machine with respect to three different cutting parameters. These parameters were cutting depth, cutting speed and feed rate. Dry milling tests were performed on hardened AISI 1045 (42HRC) with APTK 1705 LT 30 carbide inserts as a cutting condition in order to reduce optimization parameters such as the coolant. Each experiment was repeated five times and a new insert was used for each test to ensure accurate readings of surface roughness. In addition, the statistical methods of signal to noise ratio (SNR) and analysis of variance (ANOVA) were carried out to investigate the effects of cutting parameters on surface roughness. As a result of the experiment, the feed rate has the most dominant effect on average surface roughness. The effects of interactions of factors appear to be important, especially cutting speed-feed rate pair. These statistical methods can be used in manufacturing industries to optimize the manufacturing processes.