Experimental Investigation of Surface Roughness and Tool Life in Hard Turning of AISI M2 Steel Using CBN Insert

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This research work is focused on hard turning of AISI M2Steel using Cubic Boron Nitrate (CBN) cutting inserts. The experiments were planned using Response surface method (RSM) called Central Composite Design (CCD) procedure. The experiments were performed on a KIROLOSKAR model centre lathe using three input cutting parameters ,cutting speed, feed and depth of cut at lower levels(-1) and higher levels(+1). The output responses measured were surface roughness (Ra) and tool life (TL) .Mathematical model for these responses were developed using response surface methodology (RSM). An optimal process condition was identified such that to attain a good quality of hard turned surface. Models were developed using two methodologies, ie. response surface methodology (RSM) and fuzzy Logic (FL). In RSM, regression equations are obtained, which relates the hard turning parameters with each response. The adequacy of the model was checked using R-squared values. The response values predicted by developed model were compared against the experimental values and found that they are in good agreement with each other. In fuzzy logic, with the range of input machining parameters and if then rules, output response parameters are obtained and verified against the experimental values and found that they are also in good agreement with the each other. Triangular type membership functions of fuzzy logic were used in this study. Then both the methodologies were compared with the experimental values and best method was identified for modeling to achieve a better result. Then the interaction effects of various hard turning parameters on each response were also studied using analysis of variance (ANOVA) and interaction plots. Genetic algorithm(GA) was used to identify the optimal hard turning parameters in such a way to produce a good quality machined surface in hard turning AISI M2Steel using CBN(non coated) cutting tools
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AISI M2 Steel; CCD; Fuzzy Logic; Genetic Algorithm; Hard Turning; RSM

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