Skip to main content
SpringerLink
Log in

Influence of Key Parameters of Medicinal Aluminum Tube on Automatic Casing Process

  • Regular Paper
  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

In the process of automatically casing medicinal aluminum tubes with an inner plastic liner, the mechanical conditions and intrinsic characteristics significantly influence the outcome, often resulting in poor alignment accuracy and issues like squashing or bending of the plastic tube. To address this, based on the establishment of mechanical mathematical models for one-point and two-points contact assembly stages, a multi-stage assembly process mechanical analysis method for the automatic casing process was proposed. Initially, an automatic casing module and method utilizing a transitional tube for assistance were developed, considering the actual discontinuous production characteristics of casing. Subsequently, by integrating the automatic casing process, mechanical mathematical models for one-point and two-points contact assembly stages were constructed based on the mechanical equilibrium equation, accurately describing the representation of various parameter characteristics during the casing process. Following this, the impact of the plastic tube’s initial position and insertion speed on the automatic casing characteristics was analyzed, combining the mechanical model and finite element dynamic contact analysis model. Based on these results, optimized parameter conditions meeting the casing process requirements were provided. Finally, after verification through casing experimental setups, it was found that the process parameter characteristics extracted by the proposed method exhibit significant effectiveness, with the success rate of using transitional assistance for casing substantially outperforming the direct insertion of plastic tubes into aluminum tubes. The proposed method offers certain theoretical guidance for optimizing both the initial posture and casing speed in the casing process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Deshwal, G. K., & Panjagari, N. R. (2020). Review on metal packaging: Materials, forms, food applications, safety and recyclability. Journal of food science and technology, 57, 2377–2392. https://doi.org/10.1007/s13197-019-04172-z

    Article  Google Scholar 

  2. Iversen, L. J., Rovina, K., Vonnie, J. M., Matanjun, P., Erna, K. H., ‘Aqilah, N. M., Felicia, W. X., & Funk, A. A. (2022). The emergence of edible and food-application coatings for food packaging: A review. Molecules, 27(17), 5604. https://doi.org/10.3390/molecules27175604

    Article  Google Scholar 

  3. Sun, H. Y. (2003). Research on the development of medicines soft packaging. Package Engineering, 24(4), 113–115. https://doi.org/10.3969/j.issn.1001-3563.2003.04.046

    Article  MathSciNet  Google Scholar 

  4. Akram, N., Saeed, M., Mansha, A., Bokhari, T. H., & Ali, A. (2023). Metal packaging for food items advantages, disadvantages and applications. In Green sustainable process for chemical and environmental engineering and science (pp. 129–141). Elsevier. https://doi.org/10.1016/B978-0-323-95644-4.00019-X

  5. Soares, D. S., Bolgar, G., Dantas, S. T., Augusto, P. E., & Soares, B. M. (2019). Interaction between aluminium cans and beverages: Influence of catalytic ions, alloy and coating in the corrosion process. Food Packaging and Shelf Life, 19, 56–65. https://doi.org/10.1016/j.fpsl.2018.11.012

    Article  Google Scholar 

  6. Alamri, M. S., Qasem, A. A., Mohamed, A. A., Hussain, S., Ibraheem, M. A., Shamlan, G., Alqah, H. A., & Qasha, A. S. (2021). Food packaging’s materials: A food safety perspective. Saudi Journal of Biological Sciences, 28(8), 4490–4499. https://doi.org/10.1016/j.sjbs.2021.04.047

    Article  Google Scholar 

  7. Liu, Z., Song, L., Hou, Z., Chen, K., Liu, S., & Xu, J. (2019). Screw insertion method in peg-in-hole assembly for axial friction reduction. IEEE Access, 7, 148313–148325. https://doi.org/10.1109/ACCESS.2019.2946406

    Article  Google Scholar 

  8. Chernyakhovskaya, L. B., & Simakov, D. A. (2020). Peg-on-hole: Mathematical investigation of motion of a peg and of forces of its interaction with a vertically fixed hole during their alignment with a three-point contact. The International Journal of Advanced Manufacturing Technology, 107(1–2), 689–704. https://doi.org/10.1007/s00170-019-04806-8

    Article  Google Scholar 

  9. Wang, X., Wang, X., Ren, T., Wang, Y., Lou, Z., & Luo, Y. (2019). The measurement technology for precision peg-in-hole assembly. In Tenth international symposium on precision engineering measurements and instrumentation (Vol. 11053, pp. 184–194). SPIE. https://doi.org/10.1117/12.2512439

  10. Wang, L. (1999). Mechanical analyses of peg—Hole compliant assembly. Journal of Harbin University of Science and Technology, 4(1), 42–47.

    Google Scholar 

  11. Wu, Y. (2007). Study on detecting assembly force system for axies (Master’s thesis, Dalian Jiaotong University).

  12. Vartanov, M. V. (2022). Identify the position of the shaft and hole using a force-torque sensor in three-point contact assembly operations. In 2022 international ural conference on electrical power engineering (UralCon) (pp. 295–300). IEEE. https://doi.org/10.1109/UralCon54942.2022.9906711

  13. Hoffman, R., & Asada, H. H. (2021). Control strategy for jam and wedge-free 3D precision insertion of heavy objects suspended with a multi-cable crane. IEEE Robotics and Automation Letters, 6(4), 7453–7460. https://doi.org/10.1109/LRA.2021.3093860

    Article  Google Scholar 

  14. Lee, H., Park, S., Jang, K., Kim, S., & Park, J. (2022). Contact state estimation for peg-in-hole assembly using Gaussian mixture model. IEEE Robotics and Automation Letters, 7(2), 3349–3356. https://doi.org/10.1109/LRA.2022.3146949

    Article  Google Scholar 

  15. Wang, S. M., Lee, C. Y., Gunawan, H., & Yeh, C. C. (2022). On-line error-matching measurement and compensation method for a precision machining production line. International Journal of Precision Engineering and Manufacturing-Green Technology, 9(2), 493–505. https://doi.org/10.1007/s40684-021-00336-5

    Article  Google Scholar 

  16. Selvaraj, V., & Min, S. (2023). Ai-assisted monitoring of human-centered assembly: A comprehensive review. International Journal of Precision Engineering and Manufacturing-Smart Technology, 1(2), 201–218. https://doi.org/10.57062/ijpem-st.2023.0073

    Article  Google Scholar 

  17. Shen, T. H., & Lu, C. (2023). Assembly accuracy analysis of cylindrical parts based on skin model shapes considering form deviations and local surface deformations. Precision Engineering, 80, 256–273. https://doi.org/10.1016/j.precisioneng.2023.01.004

    Article  Google Scholar 

  18. Shen, T., & Lu, C. (2023). An approach of assembly deviation analysis based on Jacobian model and skin model shapes. In 2023 IEEE international conference on mechatronics and automation (ICMA) (pp. 1557–1562). IEEE. https://doi.org/10.1109/ICMA57826.2023.10216112

  19. Xing, M., Zhang, Q., Jin, X., & Zhang, Z. (2020). Optimization of selective assembly for shafts and holes based on relative entropy and dynamic programming. Entropy, 22(11), 1211. https://doi.org/10.3390/e22111211

    Article  MathSciNet  Google Scholar 

  20. Liu, Y., Zhao, Y., Lin, Q., Liu, S., Ge, E., & Wang, W. (2023). Optimization method for the assembly pose of parts considering manufacturing deviations and contact deformations. Robotic Intelligence and Automation. https://doi.org/10.1108/RIA-10-2022-0249

    Article  Google Scholar 

  21. Hu, C., Yu, H., Xia, Z., & Gu, B. (2023). Flexible assembly research for cylindrical interference fit with form error in shaft-hole structures. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 237(1–2), 203–215. https://doi.org/10.1177/09544054221100

    Article  Google Scholar 

  22. Gao, H., Shen, F., Zhang, F., & Zhang, Z. (2022). A high precision and fast alignment method based on binocular vision. International Journal of Precision Engineering and Manufacturing, 23(9), 969–984. https://doi.org/10.1007/s12541-022-00674-7

    Article  Google Scholar 

  23. Wang, P., & Zhang, Y. (2020). Study on prediction of hole shaft fit accuracy and tolerance design based on joint surface error modeling. In 2020 5th international conference on smart grid and electrical automation (ICSGEA) (pp. 166–170). IEEE. https://doi.org/10.1109/ICSGEA51094.2020.00043

  24. Zhang, J., Hu, L., Yao, X., & Yang, B. (2018). Study on assembly state identification and automatic assembly of shaft hole parts. In IOP conference series: Earth and environmental science (Vol. 108, No. 5, p. 052049). IOP Publishing. https://doi.org/10.1088/1755-1315/108/5/052049

  25. Chen, C., Zhang, C., & Pan, Y. (2023). Active compliance control of robot peg-in-hole assembly based on combined reinforcement learning. Applied Intelligence, 53(24), 30677–30690. https://doi.org/10.1007/s10489-023-05156-5

    Article  Google Scholar 

  26. Zhang, T., Liang, X., & Zou, Y. (2022). Robot peg-in-hole assembly based on contact force estimation compensated by convolutional neural network. Control Engineering Practice, 120, 105012. https://doi.org/10.1016/j.conengprac.2021.105012

    Article  Google Scholar 

  27. Xia, Y., Yin, Y., Huo, H., & Cheng, Z. (2004). Study on methodology of setting active compliance center for peg-in-hole assembly task. Zhongguo Jixie Gongcheng/China Mech. Eng., 15(11), 1015–1017. https://doi.org/10.3321/j.issn:1004-132X.2004.11.020

    Article  Google Scholar 

  28. Song, Y. M., Guo, Z., Wang, P. F., Sun, T., & Lian, B. (2020). Type synthesis of hybrid compliant mechanisms for peg-in-hole assembly. Journal of Tianjin University Science and Technology, 53(6), 582–592. https://doi.org/10.11784/tdxbz201906034

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by major project for technological innovation of Hubei Province of China(2023BAB088); Hubei Provincial Technical Innovation Project (Major Project) (2022BEC012); Hubei Province Support Enterprise Technological Innovation and Development Project(2021BAB010); Scientific Research Foundation for Doctoral Program of Hubei University of Technology (XJ2022001001).

Author information

Author notes

  1. Zhengjun Ming, Junhong Zhou, Qi Tao and Shihuang Li contributed equally to this work.

Authors and Affiliations

  1. School of Mechanical Engineering, Hubei University of Technology, Wuhan, 430068, China

    Guoping Yan, Zhengjun Ming, Junhong Zhou, Qi Tao & Shihuang Li

  2. Hubei Key Laboratory of Modern Manufacturing Quantity Engineering, Hubei University of Technology, Wuhan, 430068, China

    Guoping Yan, Zhengjun Ming, Junhong Zhou, Qi Tao & Shihuang Li

Authors
  1. Guoping Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhengjun Ming
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junhong Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qi Tao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shihuang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guoping Yan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yan, G., Ming, Z., Zhou, J. et al. Influence of Key Parameters of Medicinal Aluminum Tube on Automatic Casing Process. Int. J. Precis. Eng. Manuf. (2024). https://doi.org/10.1007/s12541-024-01031-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12541-024-01031-6

Keywords

Search

Navigation