Indian Journal of Science and Technology

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Effect of Machining Parameters and Optimization of Machining Time in Facing Operation using Response Surface Methodology and Genetic Algorithm


Affiliations
1 Department of Mechanical Engineering, Karunya School of Mechanical Sciences, Karunya University, Coimbatore - 641114, Tamil Nadu, India, India
2 Department of Mechanical Engineering, Sree Sakthi Engineering College, Karamadai, Coimbatore - 641104, Tamil Nadu, India
3 Bimetal Bearings Limited, Coimbatore - 641 018, Tamil Nadu, India
 

Optimum selection of machining parameters and its cutting conditions plays a major role in increase of productivity and minimization of total machining time. A significant improvement in process may lead to increase the process efficiency and low cost of manufacturing. In this research, Spindle speed, Feed rate, Depth of cut and End relief angle is considered as an input parameter for facing the A22E Bimetal bearing material using M42 HSS tool material. A second order mathematical model is developed using Design of Experiments (DoE) of Response Surface Methodology (RSM) to predict machining time on bimetal bearing material using special Industrial type of CNC lathe. The Analysis of Variance (ANOVA) was used to study the performance characteristics in facing operation. The values of Prob>F less than 0.05 indicate model terms are significant. Design Expert software is used to analyze the direct and interaction effects of the machining parameter. The genetic algorithm (GA) is trained and tested using MATLAB 7.0. The GA recommends 1.169 seconds as the best minimum predicted machining time value. The confirmatory test shows the second order regression predicted values and experimental values were very close and good agreement.


Keywords

Depth of Cut, End Relief Angle, Feed Rate, Genetic Algorithm (GA), Machining Time, Response Surface Methodology (RSM), Spindle Speed.
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  • Effect of Machining Parameters and Optimization of Machining Time in Facing Operation using Response Surface Methodology and Genetic Algorithm

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Authors

R. Babu
Department of Mechanical Engineering, Karunya School of Mechanical Sciences, Karunya University, Coimbatore - 641114, Tamil Nadu, India, India
D. S. Robinson Smart
Department of Mechanical Engineering, Karunya School of Mechanical Sciences, Karunya University, Coimbatore - 641114, Tamil Nadu, India, India
G. Mahesh
Department of Mechanical Engineering, Sree Sakthi Engineering College, Karamadai, Coimbatore - 641104, Tamil Nadu, India
M. Shanmugam
Bimetal Bearings Limited, Coimbatore - 641 018, Tamil Nadu, India

Abstract


Optimum selection of machining parameters and its cutting conditions plays a major role in increase of productivity and minimization of total machining time. A significant improvement in process may lead to increase the process efficiency and low cost of manufacturing. In this research, Spindle speed, Feed rate, Depth of cut and End relief angle is considered as an input parameter for facing the A22E Bimetal bearing material using M42 HSS tool material. A second order mathematical model is developed using Design of Experiments (DoE) of Response Surface Methodology (RSM) to predict machining time on bimetal bearing material using special Industrial type of CNC lathe. The Analysis of Variance (ANOVA) was used to study the performance characteristics in facing operation. The values of Prob>F less than 0.05 indicate model terms are significant. Design Expert software is used to analyze the direct and interaction effects of the machining parameter. The genetic algorithm (GA) is trained and tested using MATLAB 7.0. The GA recommends 1.169 seconds as the best minimum predicted machining time value. The confirmatory test shows the second order regression predicted values and experimental values were very close and good agreement.


Keywords


Depth of Cut, End Relief Angle, Feed Rate, Genetic Algorithm (GA), Machining Time, Response Surface Methodology (RSM), Spindle Speed.



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i36%2F130031