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Research on the intelligent design system for automotive panel die based on geometry and knowledge driven.

Authors :
Kong, Chuipin
Lei, Jialin
Zhou, XiongHui
Source :
International Journal of Advanced Manufacturing Technology. Jul2024, Vol. 133 Issue 1/2, p765-790. 26p.
Publication Year :
2024

Abstract

Automotive panel die design is a significant issue in vehicle development, playing a key role in refining quality and efficiency in the entire vehicle evolution process. It also contributes to reducing production costs and meeting the demands of the fashionable and dynamic vehicle market. This article delves into the intricacies of panel die design, focusing on essential issues such as complex three-dimensional (3D) curve and surface processing. A solution for intelligent die design based on geometry and knowledge-driven approaches is proposed. By thoroughly exploring the forming process of panel parts and incorporating die design expertise, a structured design knowledge base is established, which consolidates extensive experience and professional technology in this field. A curve offset algorithm based on progressive iteration is advocated. By adopting a dynamic error sampling algorithm that considers offset distance, the accuracy of the offset curve is ensured. In addition, the method of adjusting the offset direction is adopted to avoid the problem of overlapping offset curves and prevent distortion. Subsequently, a smooth surface is created based on the trimming curve and its offset curve to obtain a parameterized modeling of key non-standard components such as trimming tools. Furthermore, a solution strategy is proposed to handle these dynamic changes and constraints associated with parameter values, ranges, and accuracy requirements of standard components by developing a standard component computer-aided design (CAD) library, which can be seamlessly integrated into various CAD platforms through cloud-based deployment. By integrating die design knowledge, computer-aided geometric design (CAGD) theory, intelligent algorithms, and standard component libraries, a geometric and knowledge-based intelligent design system for automotive panel dies was successfully opened up. After example verification, the efficiency and quality of die design can be upgraded to a large extent. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
133
Issue :
1/2
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
177925536
Full Text :
https://doi.org/10.1007/s00170-024-13728-z