Formability evaluation of 3D closed section parts from sheet metal based on geometrical information

被引:1
|
作者
Tokugawa, Akihiro [1 ]
Sato, Masahiko [2 ]
Kuriyama, Yukihisa [1 ]
Suzuki, Katsuyuki [1 ]
机构
[1] Univ Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 2778568, Japan
[2] Nippon Steel & Sumitomo Met Corp, Steel Res Labs, 20-1 Shintomi, Futtsu, Chiba 2938511, Japan
关键词
sheet metal; bending; formability; Gaussian curvature; metric tensor; DEFORMATION; PLATES;
D O I
10.1016/j.proeng.2017.04.020
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
For successful sheet metal forming, a complex design and trial process are inevitably necessary. That complex process is geometrical design, forming process selection, tool / die face design and forming condition. It may take couple of months to carry out this process, and at the end of this process try out may result in unsuccessful. The cause of this unsuccessful try out is difficult to find out because of the complexity of the design and try out process. It is proposed that a new evaluation methodology can provide semi-quantitate evaluation for the forming difficulty of the sheet. The proposed method evaluates only geometry of sheet metal parts, starting with Riemann curvature, which is decomposed into Gaussian curvature and metric tensor. Because the nature of sheet metal forming failure (breakage and wrinkle) are mainly related to in-plane deformation and not so much related to out of plane bending. Gaussian curvature is an excellent index for in-plane deformation caused by geometry angulation. Metric tensor provide quantitative evaluation for in-plane deformation. Computational time for this proposed method is a couple of minutes and is suitable for the evaluation and modification of the upstream design. (C) 2017 Published by Elsevier Ltd.
引用
收藏
页码:101 / 106
页数:6
相关论文
共 50 条
  • [41] Experimental investigation on 3D laser forming of metal sheet
    Yang, LJ
    Wang, Y
    Djendel, M
    Qi, LT
    ADVANCES IN MATERIALS MANUFACTURING SCIENCE AND TECHNOLOGY, 2004, 471-472 : 568 - 572
  • [42] Automatic generation of 3d spiral tool path for incremental sheet metal forming of mechanical parts with complex geometry
    Frikha, Sirine
    Giraud-Moreau, Laurence
    Bouguecha, Anas
    Haddar, Mohamed
    INTERNATIONAL DEEP-DRAWING RESEARCH GROUP CONFERENCE (IDDRG 2022), 2022, 1238
  • [43] Geometrical Benchmarking evaluation of ProJet 3D printer using proposed simplified 3D Artifact
    Tanveer, Md Qamar
    Suhaib, Mohd
    Haleem, Abid
    ENGINEERING RESEARCH EXPRESS, 2019, 1 (02):
  • [44] Polishing of metal 3D printed parts with complex geometry: Visualizing the influence on geometrical features using centrifugal disk finishing
    Lussenburg, Kirsten
    van Starkenburg, Remi
    Bruins, Mathijs
    Sakes, Aimee
    Breedveld, Paul
    PLOS ONE, 2023, 18 (08):
  • [45] 3D reconstruction from section plane views based on ES
    Wu, HX
    Xie, DR
    Xue, HF
    SYSTEM SIMULATION AND SCIENTIFIC COMPUTING, VOLS 1 AND 2, PROCEEDINGS, 2005, : 46 - 50
  • [46] Evaluation of Discrimination Power of Facial Parts from 3D Point Cloud Data
    Amin, Rafiul
    Shams, A. Farhan
    Rahman, S. M. Mahbubur
    Hatzinakos, Dimitrios
    2016 9TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2016, : 602 - 605
  • [47] 3D LADAR ATR based on recognition by parts
    Sobel, E
    Douglas, J
    Ettinger, G
    AUTOMATIC TARGET RECOGNITION XIII, 2003, 5094 : 29 - 40
  • [48] Implementation of virtual models from sheet metal forming simulation into physical 3D colour models using 3D printing
    Junk, S.
    NUMISHEET 2016: 10TH INTERNATIONAL CONFERENCE AND WORKSHOP ON NUMERICAL SIMULATION OF 3D SHEET METAL FORMING PROCESSES, PTS A AND B, 2016, 734
  • [49] Parts-based 3D object classification
    Huber, D
    Kapuria, A
    Donamukkala, R
    Hebert, M
    PROCEEDINGS OF THE 2004 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 2, 2004, : 82 - 89
  • [50] 3D Object Classification Based on Volumetric Parts
    Xing, Weiwei
    Liu, Weibin
    Yuan, Baozong
    INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE, 2008, 2 (01) : 87 - 99