Optimization of Process Parameters for Surface Roughness and Material Removal Rate for SS410 Material During Turning operation

Machining of medium SS410 is very difficult. There are a number of parameters like cutting speed, feed and depth of cut etc. which must be given consideration during the machining of SS 410. The prediction of optimal machining conditions for good surface roughness and material removal rate plays a very important role in process planning. This study optimizes the process parameters for surface roughness and Material Removal Rate (MRR) in turning of SS 410 round bars on CNC machine. The experimentation was carried out with PVD-coated (WNMG) cutting tools; a first order mathematical model in terms of machining parameters was developed for surface roughness and material removal rate prediction using RSM. The multi response optimization problems i.e. Optimization of SR and MRR are solved by using Genetic Algorithm (GA). The optimization is done using twenty seven experimental runs based on L’27 orthogonal array. Analysis Of Variance (ANOVA) is also used to analyze the influence of cutting parameters during machining. Result outcomes from the ANOVA for surface roughness are that the Feed rate is found the most significant effect on surface roughness. Increase in feed rate, value of surface roughness is increase. for material removal rate is that the Feed and Depth of cut are found the most significant effect on material removal rate. Increase in feed and depth of cut, value of material removal rate is increase.