CNC MACHINING OF ALLOY STEEL 4130 AND OPTIMIZATION OF PROCESS PARAMETERS

Abstract

The surface finish have been identified as quality attribute and is assumed to be directly related to productivity. In order to build up a bridge between quality and productivity, and an attempt is made to optimize aforesaid quality attributes in small and medium size companies involved with heterogenic product demand. This study is carried out to observe the optimal effect of parameters like using the CNC End Milling operation, combined speed, feed and Depth of Cut and its influence on the surface roughness result. In machining, the surface roughness value is targeted as low as possible and is given by the value of the optimal cutting conditions. The Genetic Algorithm (GA) and Simulated Annealing (SA) optimization techniques were used for optimizing the cutting conditions of Alloy Steel 4130. Therefore, the present study on end milling machining parameter, GA and SA using to find the optimal solution of the cutting process parameters for giving the optimum value of surface roughness and Torque. By referring to the real machining case study, the regression model is developed. The best regression model is determined to formulate the fitness function of the GA and SA. The analysis of this study has proven that the GA and SA technique are capable of estimating the optimal cutting conditions that yield the optimal surface roughness and Torque. From the model it was found that feed and speed plays the most dominating role on surface finish and Torque. The roughness tends to decrease with decreasing feed and increasing cuttings peed.