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Optimization of Die Design Parameters in Blanking Operation Using Genetic Algorithm

R.S. Mohan Kumar*, C. Velmurugan**, 0***

* Assistant professor, Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore, T.N, India.

** Professor, Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore, T.N, India.

*** P. G. Scholar, Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore, T.N, India.

Periodicity:February - April'2016
DOI : https://doi.org/10.26634/jme.6.2.4890

Abstract

In the blanking operation, the quality of the product and the tool life mainly depends upon the punch and die clearance. The main objective of the study is to improve the quality of the product and also the tool life by optimizing the punch and die clearance and sheet thickness. The quality of the product and tool life mainly depends upon the punch and dies clearance. If the punch and die clearance is too large, it leads to large burrs and poor quality, otherwise if the clearance is too small, it results in part with poor edge quality, reducing the tool life and leading to more frequent tool component replacement. By using optimal amount of die clearance, the shear cracks join; this balances the punching force and optimizes part quality and tool life. By getting the optimal amount, the optimization is used; in that genetic algorithm is a simple but powerful tool to get the optimal clearance value. This experimentation is carried out with the help of regression equation and genetic algorithm to optimize the punch and die clearance.

Keywords

Blanking, Punch and DIE Clearance, Optimization, Genetic Algorithm

How to Cite this Article?

Kumar, R. S. M., Velmurugan, C., and Sangeevi, C. (2016). Optimization of Die Design Parameters in Blanking Operation Using Genetic Algorithm. i-manager’s Journal on Mechanical Engineering, 6(2), 30-36. https://doi.org/10.26634/jme.6.2.4890

References

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Optimization of Die Design Parameters in Blanking Operation Using Genetic Algorithm

Abstract

Keywords

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References

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