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Forming characteristics of a novel robot-based tube bending process

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Abstract

With the advancement of ‘Industrial 4.0’, industrial robots are becoming increasingly widespread. Thus, this study proposes a novel robot-based tube bending forming technology (RTBF) to increase the flexibility of manufacturing thin-walled complex-shaped tubes and to improve their quality. The forming mechanism and characteristics of the proposed technology are investigated using finite element modelling. Besides, the theoretical models for calculating the tube’s inner and outer sides’ equivalent stress are also presented. The obtained results showed that the bending die feeds in the tube axis direction while rotating in the novel robot-based tube bending forming, and the axial tensile stress T on the tube during the bending process is reduced. Comparing these results with the traditional rotary draw bending (RDB), the tensile stress and strain on the outer side of the bent tube and the thinning wall rate are both lower. On the other hand, the compressive stress and strain on the inner side of the bent tube and the wall thickening rate are higher in the robot-based tube bending process. The maximum cross-sectional distortion of a bent tube in the robot-based tube bending forming process remains unchanged with increasing bending angle and is always smaller than in the RDB process: the larger the bending angle, the more noticeable the difference. In summary, the robot-based tube bending forming technology significantly reduces the small diameter tube’s wall thickness and cross-sectional distortion.

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Data availability

The datasets generated and/or analysed as well as the code used during the current study are available from the corresponding author on reasonable request.

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Funding

The authors greatly acknowledge the Fundamental Research Funds for the Central Universities (No. NS2021046), the National Natural Science Foundation of China (Nos. 52105362,52105360, 5201101342, and U1937206), the Natural Science Foundation of Jiangsu Province (Nos. BK20200453 and BK20210310), and the Brain Pool Program funded by the Ministry of Science and ICT through the National Research Foundation of Korea (grant number: NRF-2021H1D3A2A01100036).

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Authors and Affiliations

  1. College of Material Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 211106, China

    Zhenbiao Sun, Chunmei Liu, Xunzhong Guo, Zushu Huang, Shuo Zheng, Cheng Cheng & Jie Tao

  2. Department of Materials Science and Engineering & RIAM, Seoul National University, 1-Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea

    Ali Abd El-Aty

  3. Mechanical Engineering Department, Faculty of Engineering-Helwan, Helwan University, Cairo, Egypt

    Ali Abd El-Aty

Authors
  1. Zhenbiao Sun
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  2. Chunmei Liu
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  3. Xunzhong Guo
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  4. Zushu Huang
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  5. Shuo Zheng
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  6. Cheng Cheng
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  7. Jie Tao
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  8. Ali Abd El-Aty
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Contributions

Author 1: Zhenbiao Sun – Performed the experiments, collected the data, performed the analysis, and wrote the paper. Author 2: Chunmei Liu – conceived and designed the study, contributed data or analysis tools, performed the analysis, and wrote the paper. Author 3: Xunzhong Guo – conceived and designed the study, contributed data or analysis tools, revised the analysis, and proofed reading. Author 4: Zushu Huang – performed the experiments, collected the data, and contributed data or analysis tools. Author 5: Shuo Zheng – performed the experiments, collected the data, and performed the analysis. Author 6: Cheng Cheng – conceived and designed the study, contributed data or analysis tools, and performed the analysis. Author 7: Jie Tao – conceived and designed the study, contributed data or analysis tools, revised the analysis, and proofed reading. Author 8: Ali Abd El-Aty – conceived and designed the study, contributed data or analysis tools, revised the analysis, and proofed reading.

Corresponding authors

Correspondence to Chunmei Liu or Xunzhong Guo.

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Sun, Z., Liu, C., Guo, X. et al. Forming characteristics of a novel robot-based tube bending process. Int J Adv Manuf Technol 121, 6685–6702 (2022). https://doi.org/10.1007/s00170-022-09780-2

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  • DOI: https://doi.org/10.1007/s00170-022-09780-2

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