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Copyright © 2022 Juxian Wang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0/

Abstract

Out-of-tolerance is one of the most common problems in mold processing. For the out-of-tolerance problem in mold processing, the cold stamping die for motorcycle fuel tank shell is taken as the research object to solve the problem of out-of-tolerance, that is, easy to occur in the process of mold forming. Based on knowledge engineering, case-based reasoning (CBR) and numerical simulation are combined to study the intelligent design method of stamping die. The factors of overtolerance in stamping die processing are analyzed, and combined with the stamping process, the intelligent design system framework of cold stamping die for fuel tank shells is constructed. Numerical simulation of the double-cover forming (DCF) process of the fuel tank shell shows that sidewall wrinkling and local cracking are the main defects. Through the analysis of orthogonal table data and evaluation indicators, the optimal parameter scheme is F = 250 kN and H = 5 mm. At this time, the interaction effect (K2 = 0.738) of the two is the largest. Through test verification, the distribution trend of the simulated thickness is consistent with the experimental thickness, and the deviation range is within 10%. According to the numerical simulation results, the reasoning mechanism of an intelligent design system including instance and rule knowledge is designed, and an uncertain knowledge reasoning algorithm based on the reliability factor is proposed to improve the accuracy of mold size and reduce the overtolerance of the mold.

Details

Title
Research and Analysis of Out-of-Tolerance Problem in Mold Processing Based on Intelligence
Author
Wang, Juxian 1   VIAFID ORCID Logo 

 Anhui Vocational and Technical College, Department of Mechanical Engineering, Hefei 230000, China 
Editor
Tao Zhou
Publication year
2022
Publication date
2022
Publisher
John Wiley & Sons, Inc.
ISSN
16875680
e-ISSN
16875699
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2717518348
Copyright
Copyright © 2022 Juxian Wang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0/