Experimental and numerical investigation of dry turning AISI 1030 carbon steel using CNC lathe machining

Abstract

Nowadays, modern metal industries have difficulty obtaining the required surface quality during machining. This is because various process parameters affect the quality of the surface. The aim of study to examine and enhance the impact of cutting-speed, cutting-depth, and feed rate during dry turning of AISI 1030 carbon steel experimentally and numerically (by DEFORM 3D) to get a better output response like minimal surface roughness, tool temperature, and maximum MRR. Taguchi-based grey relational analysis optimization technique was used for the experimental design and to determine the optimum solution of the multi-response. ANOVA was utilized to assess the contribution of the cutting parameters. Based on the results, cutting speed was the most important parameter that influenced the multiple responses of the grey-relational analysis, with a significance of 56.85%. The optimum parametric combination of multi-responses was 90 m min−1, 0.25 mm, and 0.15 mm/rev. With a minimum average relative error, the Taguchi prediction and finite element simulation were in excellent agreement with the experimental result.