No abstract

No abstract

CNC turning is one among the metal cutting process in which quality of the finished product depends mainly upon the machining parameters such as feed, speed, depth of cut, type of coolant used, types of inserts used etc. Similarly the work piece material plays an important role in metal cutting process. This study involves in indentifying the optimized parameters in CNC turning of Brass. To identify and measure the formation of burrs in the turned samples, are examined under scanning electron microscope (SEM). The optimization techniques used in this study are Response surface methodology, and Genetic algorithm. Several comparisons were made between cutting parameters with surface roughness. These optimization techniques are very helpful in indentifying the optimized control factors with high level of accuracy.

No 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.