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Mathematical Modeling and Numerical Simulation of Fixtures for Fork-Type Parts Manufacturing

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Industry 4.0: Trends in Management of Intelligent Manufacturing Systems

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Abstract

The chapter presents the mathematical models of free and forced oscillations of the comprehensive mechanical system “fixture–workpiece” describing the proposed adjustable locating-and-clamping module with a high level of flexibility for providing CNC multiaxis machining operation. With the aim to increase the fixture rigidity and detuning from a resonance mode, the eigenfrequencies and maximum displacements are determined using the numerical simulation model realized by the ANSYS software. The proposed mathematical model is proved by the results of numerical simulation on the example of fork-type parts considering contact stiffness of functional elements and values of clamping and cutting forces and moments. As a result, the advantage of the proposed manufacturing process in comparison on the typical one is justified. Particularly, the first eigenfrequency for the proposed manufacturing process is 1.64 times more than the same frequency for the typical manufacturing process. Additionally, the rigidity of a new fixture design is significantly increased, as well as detuning from a resonance mode is ensured. The proposed methodology allows estimating physical parameters of the proposed mathematical model by the results of numerical simulation and experimental research for ensuring dynamic stability of the highly complicated mechanical system “CNC machine tool–flexible fixture–spatial workpiece–precise cutting tool.”

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References

  1. Bi, Z. M., & Zhang, W. J. (2001). Flexible fixture design and automation: Review, issues and future directions. International Journal of Production Research, 39, 2867–2894. https://doi.org/10.1080/00207540110054579.

    Article  Google Scholar 

  2. Trojanowska, J., Kolinski, A., Galusik, D., et al. (2018). A methodology of improvement of manufac-turing productivity through increasing operational efficiency of the production process. In A. Hamrol, O. Ciszak, S. Legutko, & M. Jurczyk (Eds.), Advances in Manufacturing (pp. 23–32). New York: Springer. https://doi.org/10.1007/978-3-319-68619-6_3.

    Chapter  Google Scholar 

  3. Gameros, A., Axinte, D., Siller, H. R., et al. (2017). Experimental and numerical study of a fixturing system for complex geometry and low stiffness components. Journal of Manufacturing Science and Engineering, 139(4), 045001-01–045001-12. https://doi.org/10.1115/1.4034623.

    Article  Google Scholar 

  4. Gothwal, S., & Raj, T. (2017). Different aspects in design and development of flexible fixtures: Review and future directions. International Journal of Services and Operations Management, 26(3), 386–410. https://doi.org/10.1504/IJSOM.2017.081944.

    Article  Google Scholar 

  5. Ansaloni, M., Bonazzi, E., Leali, F., et al. (2013). Design of fixture systems in automotive manufac-turing and assembly. Advanced Materials Research, 712-715, 2913–2916. https://doi.org/10.4028/www.scientific.net/AMR.712-715.2913.

    Article  Google Scholar 

  6. Forstmann, R., Wagner, J., Kreiskother, K., et al. (2017). Design for automation: The rapid fixture approach. Procedia Manufacturing, 11, 633–640. https://doi.org/10.1016/j.promfg.2017.07.161.

    Article  Google Scholar 

  7. Karpus, V. E., & Ivanov, V. A. (2012). Choice of the optimal configuration of modular reusable fixtures. Russian Engineering Research, 32(3), 213–219. https://doi.org/10.3103/S1068798X12030124.

    Article  Google Scholar 

  8. Pehlivan, S., & Summers, J. (2008). A review of computer-aided fixture design with respect to infor-mation support requirements. International Journal of Production Research, 46(4), 929–947. https://doi.org/10.1080/00207540600865386.

    Article  MATH  Google Scholar 

  9. Boyle, I., Rong, Y., & Brown, D. (2011). A review and analysis of current computer-aided fixture de-sign approaches. International Journal of Robotics and Computer-Integrated Manufacturing, 27(1), 1–12. https://doi.org/10.1016/j.rcim.2010.05.008.

    Article  Google Scholar 

  10. Bakker, O. J., Papastathis, T. N., Ratchev, S. M., & Popov, A. A. (2013). Recent research on flexible fixtures for manufacturing processes. Recent Patents on Mechanical Engineering, 6(2), 107–121. https://doi.org/10.2174/2212797611306020003.

    Article  Google Scholar 

  11. Tohidi, H., & AlGeddawy, T. (2016). Planning of modular fixtures in a robotic assembly system. Pro-cedia CIRP, 41, 252–257. https://doi.org/10.1016/j.procir.2015.12.090.

    Article  Google Scholar 

  12. Hui, L., Weifang, C., & Shengjie, S. (2016). Design and application of flexible fixture. Procedia CIRP, 56, 528–532. https://doi.org/10.1016/j.procir.2016.10.104.

    Article  Google Scholar 

  13. Posindu, B. A., Janaka, E. B., Kasun, D. T., et al. (2017). A novel fixturing system for complex shaped components. In IEEE (Ed.), 2017 Moratuwa Engineering Research Conference (pp. 221–224). Moratuwa: IEEE. https://doi.org/10.1109/MERCon.2017.7980485.

    Chapter  Google Scholar 

  14. Mohring, H.-C., Gessler, W., Konig, A., et al. (2017). Modular intelligent fixture system for flexible clamping of large parts. Journal of Machine Engineering, 17(4), 29–39. https://doi.org/10.5604/01.3001.0010.7003.

    Article  Google Scholar 

  15. Erdem, I., Levandowski, C., Berlin, C., et al. (2017). A novel comparative design procedure for re-configurable assembly fixtures. CIRP Journal of Manufacturing Science and Technology, 19, 93–105. https://doi.org/10.1016/j.cirpj.2017.06.004.

    Article  Google Scholar 

  16. Gothwal, S., & Raj, T. (2018). Conceptual design and development of pneumatically controlled flexible fixture and pallets. International Journal of Services and Operations Management, 29(2), 147–162. https://doi.org/10.1504/IJSOM.2018.089246.

    Article  Google Scholar 

  17. Ivanov, V., & Zajac, J. (2018). Flexible fixtures for CNC machining centers in multiproduct manufacturing. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 4(12), e4. https://doi.org/10.4108/eai.10-1-2018.153552.

    Article  Google Scholar 

  18. Liao, Y., & Hu, S. (2001). An integrated model of a fixture – workpiece system for surface quality prediction. International Journal of Advanced Manufacturing Technology, 17(11), 810–818. https://doi.org/10.1007/s001700170108.

    Article  Google Scholar 

  19. Kumbhar, N., et al. (2012). Finite element modelling and analysis of workpiece – fixture system. International Journal of Applied Research in Mechanical Engineering, 2(2), 60–65.

    Google Scholar 

  20. Kang, Y., et al. (2003). Computer-aided fixture design verification. Part 3. Stability analysis. The International Journal of Advanced Manufacturing Technology, 21(10), 842–849. https://doi.org/10.1007/s00170-002-1401-4.

    Article  Google Scholar 

  21. Asante, J. N. (2010). Effect of fixture compliance and cutting conditions on workpiece stability. The International Journal of Advanced Manufacturing Technology, 48(1), 33–43. https://doi.org/10.1007/s00170-009-2284-4.

    Article  Google Scholar 

  22. Cioata, V., & Kiss, I. (2009). The machining error due to contact deformation of workpiece—fixture system. Acta Technica Corviniensis – Bulletin of Engineering, 2(1), 33–36.

    Google Scholar 

  23. Zheng, Y. (2005). Finite element analysis for fixture stiffness. PhD Thesis. Worcester: Worcester Polytechnic Institute.

    Google Scholar 

  24. Asada, H., & By, A. (1985). Kinematic analysis of workpart fixturing for flexible assembly with automatically reconfigurable fixtures. IEEE Journal on Robotics and Automation, 1(2), 86–94. https://doi.org/10.1109/JRA.1985.1087007.

    Article  Google Scholar 

  25. Rong, Y., & Bai, Y. (1997). Automated generation of fixture configuration design. Journal of Manufacturing Science and Engineering, 119(2), 208–219. https://doi.org/10.1115/1.2831097.

    Article  Google Scholar 

  26. Chou, Y. C. (1993). Automated fixture design for concurrent manufacturing planning. Concurrent Engineering, 1(4), 219–229. https://doi.org/10.1177/1063293X9300100405.

    Article  Google Scholar 

  27. Wu, Y., et al. (1997). Automated generation of dedicated fixture design. International Journal Computer Application in Technologies, 10(3–4), 213–235. https://doi.org/10.1504/IJCAT.1997.062249.

    Article  Google Scholar 

  28. Trappey, A. J. C., et al. (1995). Computer-aided fixture analysis using finite element analysis and mathematical optimization modeling. Journal of Manufacturing Science and Engineering, 2-1, 777–787.

    Google Scholar 

  29. Deng, H. (2006). Analysis and synthesis of fixturing dynamic stability in machining accounting for material removal effect. Ph.D. Thesis. Atlanta: Georgia Institute of Technology.

    Google Scholar 

  30. 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: Machado J., Soares F., Veiga G. (eds.) Innovation, Engineering and Entrepreneurship. HELIX 2018. Lecture Notes in Electrical Engineering, 2019, 505, 299–306. https://doi.org/10.1007/978-3-319-91334-6_41.

    Google Scholar 

  31. Slabbert, E., Walker, A., Bright, G. (2017). Modal analysis of machining processess on an automated flexible fixture for a reconfigurable manufacturing system. In: 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). IEEE. doi: https://doi.org/10.1109/M2VIP.2017.8211498.

  32. Ivanov, V., Pavlenko, I. (2018). Comprehensive approach for mathematical modeling of mechanical systems: Fixture design case study. In: Knapcikova L., Balog M. (eds.) Proceedings of 2nd EAI Int. Conf. on Management of Manufacturing Systems, MMS-2017, pp. 1–19. doi: https://doi.org/10.4108/eai.22-11-2017.2274154.

  33. Ivanov, V., & Pavlenko, I. (2018). Fundamental approach for analysis of dynamic characteristics of fixtures. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 4(13), e1. https://doi.org/10.4108/eai.20-3-2018.154366.

    Article  Google Scholar 

  34. Pavlenko, I., Simonovskiy, V., Ivanov, V. et al. (2019). Application of artificial neural network for identification of bearing stiffness characteristics in rotor dynamics analysis. In: Ivanov V. et al. (eds.) Advances in Design, Simulation and Manufacturing. DSMIE-2018. Lecture Notes in Mechanical Engineering, 2019, pp. 325–335. doi: https://doi.org/10.1007/978-3-319-93587-4_34.

    Google Scholar 

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Acknowledgements

The achieved results were partially funded by the Ministry of Education and Science of Ukraine within the research project “Development and Implementation of Energy Efficient Modular Separation Devices for Oil and Gas Equipment” of the Faculty of Technical Systems and Energy Efficient Technologies at Sumy State University (State registration number 0117U003931).

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Correspondence to Vitalii Ivanov .

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Ivanov, V., Pavlenko, I., Kuric, I., Kosov, M. (2019). Mathematical Modeling and Numerical Simulation of Fixtures for Fork-Type Parts Manufacturing. In: Knapčíková, L., Balog, M. (eds) Industry 4.0: Trends in Management of Intelligent Manufacturing Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-14011-3_12

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  • DOI: https://doi.org/10.1007/978-3-030-14011-3_12

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  • Online ISBN: 978-3-030-14011-3

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