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

Journal of Soft Computing in Civil Engineering

关键词: Cold drawing;    Springback;    Taguchi;    Particle Swarm Optimization;    Genetic Algorithm;    Simulated Annealing;   

DOI  :  10.22115/scce.2018.136009.1072

学科分类：工程和技术（综合）

来源: Pouyan Press

【 摘 要 】

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.

【 授权许可】

CC BY