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Soft Computing in Civil Engineering
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Karanjule, D., Bhamare, S., Rao, T. (2018). Process Parameter Optimization for minimizing Springback in Cold Drawing Process of Seamless Tubes using Advanced Optimization Algorithms. Soft Computing in Civil Engineering, 2(3), 72-90. doi: 10.22115/scce.2018.136009.1072
D. B. Karanjule; S. S. Bhamare; T. Rao. "Process Parameter Optimization for minimizing Springback in Cold Drawing Process of Seamless Tubes using Advanced Optimization Algorithms". Soft Computing in Civil Engineering, 2, 3, 2018, 72-90. doi: 10.22115/scce.2018.136009.1072
Karanjule, D., Bhamare, S., Rao, T. (2018). 'Process Parameter Optimization for minimizing Springback in Cold Drawing Process of Seamless Tubes using Advanced Optimization Algorithms', Soft Computing in Civil Engineering, 2(3), pp. 72-90. doi: 10.22115/scce.2018.136009.1072
Karanjule, D., Bhamare, S., Rao, T. Process Parameter Optimization for minimizing Springback in Cold Drawing Process of Seamless Tubes using Advanced Optimization Algorithms. Soft Computing in Civil Engineering, 2018; 2(3): 72-90. doi: 10.22115/scce.2018.136009.1072

Process Parameter Optimization for minimizing Springback in Cold Drawing Process of Seamless Tubes using Advanced Optimization Algorithms

Article 6, Volume 2, Issue 3 - Serial Number 5, Summer 2018, Page 72-90  XML PDF (1.07 MB)
Document Type: Regular Article
DOI: 10.22115/scce.2018.136009.1072
Authors
D. B. Karanjule 1; S. S. Bhamare2; T. Rao3
1Sinhgad College of Engineering,Vadgaon,Pune,M.S.,India
2Registrar,Dr.Babasaheb Ambedkar Technological University,Lonere, M.S., India, 402103
3Former Director,R and D Department, I.S.M.T. Limited, Ahmednagar, M.S.,India,414003
Receive Date: 11 April 2018,  Revise Date: 08 June 2018,  Accept Date: 14 June 2018 
Abstract
In tube drawing process, a tube is pulled out through a die and a plug to reduce its diameter and thickness as per the requirement. Dimensional accuracy of cold drawn tubes plays a vital role in further quality of end products and controlling rejection in manufacturing processes of these end products. Springback phenomenon is the elastic strain recovery after removal of forming loads, causes geometrical inaccuracies in drawn tubes. Further this leads to difficulty in achieving close dimensional tolerances. In the present work springback of EN 8 D tube material is studied for various cold drawing parameters. The process parameters in this work include die semi angle, land width and drawing speed. The experimentation is done using Taguchi’s L36 orthogonal array and then optimization is done in data analysis software Minitab 17.The results of ANOVA shows that 15 degree die semi angle,5 mm land width and 6 m/min drawing speed yields least springback. Furthermore, optimization algorithms named Particle Swarm Optimization (PSO),Simulated Annealing (SA) and Genetic Algorithm (GA) are applied which shows that 15 degree die semi angle, 10 mm land width and 8 m/min drawing speed results in minimal springback with almost 10.5 % improvement. Finally the results of experimentation are validated with Finite Element Analysis technique using ANSYS.
Keywords
Cold drawing; Springback; Taguchi; Particle Swarm Optimization; Genetic Algorithm; Simulated Annealing
Main Subjects
Structural Optimization
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