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

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