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Optimization of Machining Parameters for CNC Turning Process Through Hybrid Approach


Affiliations
1 Dept. of Mechanical Engg., Sona College of Technology, Salem, Tamil Nadu, India
2 Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, India
     

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This paper describes the combination of Genetic Algorithm (GA) and Artificial Neural Network (ANN) based hybrid approach in real data based optimization. Power consumption, cutting force and surface roughness are the major constraints which directly influence the operating parameters. Many researchers have developed mathematical model of the CNC turning process for the purpose of optimizing the operating parameters. But this will be highly suitable for a particular combination of cutting tool and workpiece. In order to avoid this problem, hybrid approach is proposed in this work (i.e) Genetic algorithm and ANN. GA is used for solving the optimization machining cost and ANN is used for the constraints evaluation. Experimental results demonstrate that this hybrid optimization approach can accurately estimate machining cost without violating those constraints.
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  • Optimization of Machining Parameters for CNC Turning Process Through Hybrid Approach

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Authors

J. S. Senthilkumar
Dept. of Mechanical Engg., Sona College of Technology, Salem, Tamil Nadu, India
P. Asokan
Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, India
R. M. Arunachalam
Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, India
D. Suresh Babu
Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, India
V. Manickam
Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, India

Abstract


This paper describes the combination of Genetic Algorithm (GA) and Artificial Neural Network (ANN) based hybrid approach in real data based optimization. Power consumption, cutting force and surface roughness are the major constraints which directly influence the operating parameters. Many researchers have developed mathematical model of the CNC turning process for the purpose of optimizing the operating parameters. But this will be highly suitable for a particular combination of cutting tool and workpiece. In order to avoid this problem, hybrid approach is proposed in this work (i.e) Genetic algorithm and ANN. GA is used for solving the optimization machining cost and ANN is used for the constraints evaluation. Experimental results demonstrate that this hybrid optimization approach can accurately estimate machining cost without violating those constraints.