Research on automatic analysis and layout system of the stamping process for automotive panels and its key technologies

Author:

Kong Chuipin,Lei Jialin,Chao Jiale,Zhou Xiong Hui1

Affiliation:

1. Shanghai Jiao Tong University

Abstract

Abstract The stamping process analysis and layout of automotive panels are extremely complex and time-consuming, which directly affects the quality and cycle of product development. Based on the CAGD theory of complex curves and surfaces, process design knowledge, and multidisciplinary optimization techniques, an intelligent automatic process analysis and layout system has been developed. The process feature analysis method based on discretization and merging idea has been proposed to accurately and automatically identify process features such as piercing, trimming, flanging and restricting. The process feature dispersion method based on curvature and normal variation of the forming surface is proposed to ensure the accuracy of feature dispersion. The combinatorial optimization algorithm is proposed to merge the discrete features according to the stamping direction and the geometric parameters of the features to reduce the number of process steps as much as possible. Moreover, a process constraint diagram with combined features is constructed, which is used as the initial solution and sequence constraint conditions for the process layout to effectively ensure the rationality of the process layout. Based on the die design rules, the simplified tools of the process features are created, and the rapid interference detection algorithm of the tools is proposed to realize the automatic layout and optimization of the stamping process. Finally, the aforementioned algorithms are seamlessly integrated into the NX software to develop an automatic analysis and layout system for the automotive panel stamping process. The feasibility, accuracy and efficiency of the system have been demonstrated through the example of the wing panel and the system has been successfully applied in enterprises.

Publisher

Research Square Platform LLC

Reference35 articles.

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