Investigation of Machining Parameters in CNC Turning of EN3 Low Carbon Steel Using Genetic Algorithm and Response Surface Methodology

Abstract

Burrs are bottleneck of precision machining and automation production. Burrs are formed in every edges and faces, during the turning process, which affects the quality level of surface roughness. In this paper the experimental study of EN3 low carbon steel were carried out to minimize the surface roughness using response surface methodology and genetic algorithm. Tungsten Carbide was used as a cutting tool for this turning operation. Machined samples are examined under Scanning Electron Microscope (SEM) for burr formation. A wide variety of analysis between cutting parameters have been shown graphically. The minimization of burr was achieved and hence better surface quality was obtained by optimizing the cutting parameters like cutting speed, feed, and depth of cut, with the aid of Genetic Algorithm (GA) & Response Surface Methodology (RSM) Techniques.

Optimization of Cutting Parameters during Turning of AISI-310 Using Response Surface Methodology

“…Feed is the major influencing parameter in turning steel. Ravi Kumar et al [9] experimented turning process on low carbon steel EN3 and found the spindle speed, feed and depth of cut as impelling parameters. The optimal input parameters were found by applying genetic algorithm (GA) and response surface methodology (RSM).…”