Proceedings of the Korean Society for Technology of Plasticity Conference (한국소성가공학회:학술대회논문집)
- 2007.05a
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- Pages.285-288
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- 2007
A study on the Effects of Input Parameters on Springback Prediction Accuracy
스프링백 해석 정도 향상을 위한 입력조건에 관한 연구
Abstract
The use of commercial finite element analysis software to perform the entire process analysis and springback analysis has increased fast for last decade. Pamstamp2G is one of commercial software to be used widely in the world but it has still not been perfected in the springback prediction accuracy. We must select the combination of input parameters for the highest springback prediction accuracy in Pamstamp2G because springback prediction accuracy is sensitive to input parameters. Then we study the affect of input parameters to use member part for acquiring high springback prediction accuracy in Pamstamp2G. First, we choose important four parameters which are adaptive mesh level at drawing stage and cam flange stage, Gauss integration point number through the thickness and cam offset on basis of experiment. Second, we make a orthogonal array table L82[(7)] which is consist of 8 cases to be combined 4 input parameters, compare to tryout result and select main factors after analyzing affect factors of input parameters by Taguchi's method in 6 sigma. Third, we simulate after changing more detail the conditions of parameters to have big affect. At last, we find the best combination of input parameters for the highest springback prediction accuracy in Pamstamp2G. The results of the study provide the selection of input parameters to Pamstamp2G users who want to Increase the springback prediction accuracy.
Keywords
- Springback;
- Input parameters;
- Adaptive Mesh Level;
- Gauss Integration Point Number through the thickness;
- Cam offset;
- Affect Factors;
- 6 Sigma