Multi-Objective optimization of Forming Process for Auto-body Panel Based on Springback Control

Abstract

Abstract: Selection criteria of objective function in the optimization model aimed to reduce springback for auto-body panel were discussed. Taking the automobile roof panel as an example, a multi-objective optimization model was established to control springback. The design of experiment (DOE),radial basis function neural networks (RBF) and non-dominated sorting genetic algorithm (NSGA-II) were employed to solve the model. The solution was compared with that of the corresponding singleobjective optimization models to analyze the influence of forming process on springback. The results show that blankholder force influences the amount of plastic deformation significantly, and thus the amount of springback. large plastic deformation would occur and springback would decrease rapidly with increasing blankholder force, but when it increases to a certain extent springback would also increase slightly, while drawbead forces have great effect on the internal stress distribution of the sheet metal, thus eventually influence trimming springback. Compared with corresponding single-objective optimization models, the proposed multi-objective optimization model considers forming defects more comprehensively and is more reasonable for application.

Key words: springback, optimization, sheetmetal stamping, forming process

CLC Number:

TG386

References

［1］Hayashi H, Nakagawa T. Recent trends in sheet metals and their formability in manufacturing automotive panels ［J］. Materials Processing Technology, 1994, 46(34): 455487.

［2］Wang H, Li G Y, Zhong Z H. Optimization of sheet metal forming processes by adaptive response surface based on intelligent sampling method ［J］. Journal of Materials Processing Technology, 2008, 197(13): 7788.

［3］Ohata T, Nakamura Y, Katayama T, et al. Development of optimum process design system for sheet fabrication using response surface method ［J］. Journal of Materials Technology, 2003, 143144: 667–672.

［4］Kazan R, Firat M, Tiryakia A E. Prediction of springback in wipebending process of sheet metal using neural network ［J］. Materials and Design, 2009, 30(2): 418423.

［5］朱东波, 马雷, 李涤尘, 等. 复杂形状板料冲压件回弹评价指标研究［J］. 机械科学与技术, 2000, 19 (6): 953955.

ZHU Dongbo, MA Lei, LI Dichen, et al. On springback evaluation for 3D sheet metal stamping parts ［J］. Mechanical Science and Technology, 2000, 19(6): 953955.

［6］Liu W, Yang Y Y, Xing Z W, et al. Springback control of sheet metal forming based on the responsesurface method and multiobjective genetic algorithm ［J］. Materials Science and Engineering: A, 2009， 499(12):325–338.

［7］郑超, 刘全坤, 胡龙飞, 等. 基于回弹控制的汽车横梁拉延成形工艺多目标优化研究［J］. 合肥工业大学学报, 2008, 31(1): 8992.

ZHENG Chao, LIU Quankun, HU Longfei, et al. Study on multiobjective optimization of stamping of the cross member based on springback control ［J］. Journal of Hefei University of Technology, 2008, 31(1):8992.

［8］Song J H, Huh H, Kim S H. Stressbased springback reduction of a channel shaped autobody part with highstrength steel using response surface methodology ［J］. Journal of Engineering Materials and Technology, 2007, 129(3): 397406.

［9］Ingarao G, Lorenzo R D, Micari F. Analysis of stamping performances of dual phase steels: A multiobjective approach to reduce springback and thinning failure ［J］. Materials and Design, 2009, 30: 44214433.

［10］陈劼实, 周贤宾, 刘长丽. 数值模拟中应用最小厚度准则预测板料成形极限［J］. 中国机械工程, 2006, 17(S1): 6770.

CHEN Jieshi, ZHOU Xianbin, LIU Changli. Sheet metal forming limit prediction with minimum thickness criterion in numerical simulation ［J］. China Mechanical Engineering, 2006, 17(S1): 6770.

[1]	FU Yang, DING Zhiyin, MI Yang. Frequency Control Strategy for Interconnected Power Systems with Time Delay Considering Optimal Energy Storage Regulation [J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1128-1138.
[2]	WANG Hong, QI Yankun, HE Yong, YANG Guojun. Multi-Stage Opportunistic Maintenance Decision-Making for Electric Multiple Unit Systems with Bi-Objective Optimization [J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1276-1284.
[3]	HUANG Yuhao, HAN Chao, ZHAO Minghui, DU Qiankun, WANG Shigang. Multi-Objective Optimization Strategy of Trajectory Planning for Unmanned Aerial Vehicles Considering Constraints of Safe Flight Corridors [J]. Journal of Shanghai Jiao Tong University, 2022, 56(8): 1024-1033.
[4]	LI Dechang, YANG Hualong, DUAN Jingru. A Joint Optimization of Vessel Scheduling and Refueling Strategy for Container Liner Shipping with Cooperative Agreements [J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 953-964.
[5]	YAN Qing, LU Jiansha, JIANG Weiguang, SHAO Yiping, TANG Hongtao, LI Yingde. Path Optimization of Stacker in Compact Storage System with Dual-Port Layout [J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 858-867.
[6]	OUYANG Xuyu, CHANG Haichao, LIU Zuyuan, FENG Baiwei, ZHAN Chengsheng, CHENG Xide. Application of Adaptive Sampling Method in Hull Form Optimization [J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 937-943.
[7]	FU Lia (傅莉), LONG Xia∗ (龙洗), HE Wenbinb (何文斌). Air Combat Assignment Problem Based on Bayesian Optimization Algorithm [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 799-805.
[8]	LI Shiqi (李世其), LI Xiao∗ (李肖), HAN Ke (韩可), XIONG Youjun (熊友军), XIE Zheng (谢铮), CHEN Jinliang (陈金亮). Path Planning and Optimization of Humanoid Manipulator in Cartesian Space [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 614-620.
[9]	HUANG Yinghao1,2 (黄颖浩), WU Yi3 (吴怡), YAO Lixiu2 (姚莉秀), CAI Yunze1,2∗ (蔡云泽). A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 671-679.
[10]	WANG Xiaojian, HONG Jun, CHEN Jinghua, LI Hongguang. Weight Reduction Study of Box Structure Based on Parametric Modeling and Response Surface Optimization [J]. Air & Space Defense, 2022, 5(4): 60-66.
[11]	ZENG Bo, MU Hongwei, DONG Houqi, ZENG Ming. Optimization of Active Distribution Network Operation Considering Decarbonization Endowment from 5G Base Stations [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 279-292.
[12]	MA Zhoujun, WANG Yong, WANG Jie, CHEN Shaoyu. A Dual Cooperative Optimization for Optimal Redundancy Quantity of MMC Submodules of Flexible Controller [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 325-332.
[13]	WANG Ning, FU Yunpeng, LI Ting, LI Tie, YI Ping. Optimization of Control Scheme for Large Flow Seawater Cooling System Based on FloMaster-Simulink Co-Simulation [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 379-385.
[14]	XU Shengguan, CHEN Hongquan, ZHANG Jiale, GAO Huanqin, JIA Xuesong. Study of the Efficient Global Optimization with High Accuracy and Its Applications in Aerodynamic [J]. Air & Space Defense, 2022, 5(3): 65-72.
[15]	LIU Jiea (刘洁), ZHANG Baojib∗ (张宝吉). Multiobjective Optimization of Hull Form Based on Global Optimization Algorithm [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(3): 346-355.