Correlation between Surface Roughness Characteristics in CO2 Laser Cutting of Mild Steel

Abstract

CO2 laser oxygen cutting of mild steel is widely used industrial application. Cut surface quality is a very important characteristic of laser cutting that ensures an advantage over other contour cutting processes. In this paper mathematical models for estimating characteristics of surface quality such as average surface roughness and ten-point mean roughness in CO2 laser cutting of mild steel based on laser cutting parameters were developed. Empirical models were developed using artificial neural networks and experimental data collected. Taguchi’s orthogonal array was implemented for experimental plan. From the analysis of the developed mathematical models it was observed that functional dependence between laser cutting parameters, their interactions and surface roughness characteristics is complex and non-linear. It was also observed that there exist region of minimal average surface roughness to ten-point mean roughness ratio. The relationship between average surface roughness and ten-point mean roughness was found to be nonlinear and can be expressed with a second degree polynomial.

Keywords

• Surface Roughness
• CO2 Laser Cutting
• Artificial Neural Networks Modeling
• Correlation