Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Determination of contact points between workpiece and fixture elements as a tool for augmented reality in fixture design

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Fixtures play a significant role in ensuring the quality of products in manufacturing engineering. The paper considers fork-type parts that have a complex spatial configuration and needs to be machined by drilling-milling-boring equipment in one setup. In fixture design, it is necessary to provide wide tool accessibility, and therefore the choice of locating surfaces of the workpiece is an important step. The mathematical approach for determining the coordinates of contact points between the workpiece and the locating and clamping elements fixtures in the coordinate system is developed in this paper. The geometric parameters of the workpiece are taken into account in determining the coordinates. It allows to apply the proposed approach for parts of another standard size, but the same design and technological features. The technology of augmented reality is an effective tool at the design stage of fixtures and allows to visualize the developed fixture configurations. This approach has been successfully applied for such parts as levers, connecting rods, flat parts.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Ivanov, V. (2019). Process-oriented approach to fixture design. In Ivanov V. et al. (Eds.), Advances in design, simulation and manufacturing (pp. 42–50). DSMIE 2018. Lecture Notes in Mechanical Engineering. Springer. https://doi.org/10.1007/978-3-319-93587-4_5.

  2. Ivanov, V., Pavlenko, I., Liaposhchenko, O., Gusak, O., & Pavlenko, V. (2018). Computer-aided positioning of elements of the system “fixture - workpiece”. In 3rd EAI international conference on management of manufacturing systems (MMS-2018), 2279706. http://doi.org/10.4108/eai.6-11-2018.2279706.

  3. Qin, G., Zhang, W., & Wan, M. (2005). Analysis and optimal design of fixture clamping sequence. Journal of Manufacturing Science and Engineering, 128(2), 482–493. https://doi.org/10.1115/1.2162908.

    Article  Google Scholar 

  4. Liu, S.-G., Zheng, L., Zhang, Z.-H., Li, Z.-Z., & Liu, D.-C. (2006). Optimization of the number and positions of fixture locators in the peripheral milling of a low-rigidity workpiece. The International Journal of Advanced Manufacturing Technology, 33, 668. https://doi.org/10.1007/s00170-006-0507-5.

    Article  Google Scholar 

  5. Krol, O., & Sokolov, V. (2018). Development of models and research into tooling for machining centers. Eastern-European Journal of Enterprise Technologies, 3(1–93), 12–22. https://doi.org/10.15587/1729-4061.2018.131778.

    Article  Google Scholar 

  6. Xiong, C.-H., Wang, M. Y., & Xiong, Y.-L. (2008). On clamping planning in workpiece-fixture systems. IEEE Transactions on Automation Science and Engineering, 5(3), 407–419. https://doi.org/10.1109/TASE.2008.921483.

    Article  Google Scholar 

  7. Qin, G., Ye, H., & Rong, Y. (2014). A unified point-by-point planning algorithm of machining fixture layout for complex workpiece. International Journal of Production Research, 52(5), 1351–1362. https://doi.org/10.1080/00207543.2013.842020.

    Article  Google Scholar 

  8. Tarelnyk, V., Martsynkovskyy, V., & Dziuba, A. (2014). Applied Mechanics and Materials, 630, 388–396. https://doi.org/10.4028/www.scientific.net/AMM.630.388.

    Article  Google Scholar 

  9. Cioata, V. G. (2008). Determining the machining error due to workpiece—Fixture system deformation using the finite element method. In Intelligent manufacturing and automation: Focus on next generation of intelligent systems and solutions (pp. 253–254).

  10. Asante, J. N. (2008). A combined contact elasticity and finite element-based model for contact load and pressure distribution calculation in a frictional workpiece-fixture system. The International Journal of Advanced Manufacturing Technology, 39, 578. https://doi.org/10.1007/s00170-007-1187-5.

    Article  Google Scholar 

  11. Zhou, X. H., Liu, W., Niu, Q., Wang, P., & Jiang, K. (2014). Locator layout optimization for checking fixture design of thin-walled parts. Key Engineering Materials, 572, 593–596. https://doi.org/10.4028/www.scientific.net/KEM.572.593.

    Article  Google Scholar 

  12. Satyanarayana, S., & Melkote, S. N. (2004). Finite element modeling of fixture–workpiece contacts: Single contact modeling and experimental verification. International Journal of Machine Tools and Manufacture, 44(9), 903–913. https://doi.org/10.1016/j.ijmachtools.2004.02.010.

    Article  Google Scholar 

  13. Rao, B. S., Malkapuram, D., & Ramjee, E. (2018). Force and deformation analysis for determination of optimum fixture configuration. International Journal of Applied Engineering Research, 13(7), 4675–4681.

    Google Scholar 

  14. Liao, X., & Wang, G. G. (2006). Simultaneous optimization of fixture and joint positions for non-rigid sheet metal assembly. The International Journal of Advanced Manufacturing Technology, 36(3–4), 386–394. https://doi.org/10.1007/s00170-006-0827-5.

    Article  Google Scholar 

  15. Karpus, V. E., & Ivanov, V. A. (2012). Locating accuracy of shafts in V-blocks. Russian Engineering Research, 32(2), 144–150. https://doi.org/10.3103/S1068798X1202013X.

    Article  Google Scholar 

  16. Mohring, H.-C., & Wiederkehr, P. (2016). Intelligent fixtures for high performance machining. In 7th HPC 2016—CIRP conference on high performance cutting, Procedia CIRP (Vol. 46, pp. 383–390). https://doi.org/10.1016/j.procir.2016.04.042.

  17. Yang, B., Wang, Z., Yang, Y., Jing, Z., & Kang, Y. (2016). Determination of the number of fixture locating points for sheet metal by grey model. In MATEC Web of conferences (Vol. 95, p. 07018).

  18. Chaari, R., Abennadher, M., Louati, J., & Haddar, M. (2014). Mathematical methodology for optimization of the clamping forces accounting for workpiece vibratory behaviour. International Journal for Simulation and Multidisciplinary Design Optimization, 5, A13. https://doi.org/10.1051/smdo/2013005.

    Article  Google Scholar 

  19. Pavlenko, I., Trojanowska, J., Ivanov, V., & Liaposhchenko, O. (2019). Scientific and methodological approach for the identification of mathematical models of mechanical systems by using artificial neural networks. In 3rd Conference on innovation, engineering and entrepreneurship (Vol. 505, pp. 299–306). Regional HELIX 2018, Lecture Notes in Electrical Engineering. https://doi.org/10.1007/978-3-319-91334-6_41.

  20. Kumar, E. R., & Annamalai, K. (2014). Investigation into optimal fixturing cost of an assembly using genetic algorithm. Engineering Review, 34(2), 85–91.

    Google Scholar 

  21. Vishnupriyan, S., Majumder, M. C., & Ramachandran, K. P. (2010). Optimization of machining fixture layout for tolerance requirements under the influence of locating errors. International Journal of Engineering, Science and Technology, 2(1), 152–162.

    Article  Google Scholar 

  22. Hajimiri, H., Abedini, V., Shakeri, M., & Siahmargoei, M. H. (2018). Simultaneous fixturing layout and sequence optimization based on genetic algorithm and finite element method. The International Journal of Advanced Manufacturing Technology, 97(9–12), 3191–3204. https://doi.org/10.1007/s00170-018-1706-6.

    Article  Google Scholar 

Download references

Acknowledgements

The results of the paper were partially obtained within the National Scholarship Programme of the Slovak Republic (the research project “Identification of Parameters for Technological Equipment using Artificial Neural Networks”), as well as partially funded by the Ministry of Education and Science of Ukraine (The Project No. 0117U003931).

Author information

Authors and Affiliations

  1. Sumy State University, 2 Rymskogo-Korsakova St., Sumy, 40007, Ukraine

    Vitalii Ivanov, Ivan Pavlenko, Oleksandr Liaposhchenko & Oleksandr Gusak

  2. Machine-Building College of Sumy State University, 17 Shevchenka Ave., Sumy, 40000, Ukraine

    Vita Pavlenko

Authors
  1. Vitalii Ivanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ivan Pavlenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Oleksandr Liaposhchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Oleksandr Gusak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Vita Pavlenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vitalii Ivanov.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ivanov, V., Pavlenko, I., Liaposhchenko, O. et al. Determination of contact points between workpiece and fixture elements as a tool for augmented reality in fixture design. Wireless Netw 27, 1657–1664 (2021). https://doi.org/10.1007/s11276-019-02026-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-019-02026-2

Keywords

Search

Navigation