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Application of Geometric Simulation for Determination of Dynamic Undeformed Chip Thickness in Milling

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Języki publikacji
EN
Abstrakty
EN
Self-excited vibration is a significant constraint on productivity and production quality, which makes various forms of virtual machining widely used to find stable conditions before starting the actual machining operation. Numerical simulation of self-excited vibration, although much slower than analytical solutions, makes it possible to consider the nonlinearity of the process and its continuous variation. In 5-axis milling, predicting the instantaneous cross-sections of the uncut chip is very difficult, so geometric simulation is readily used to check the correctness of the NC program and the obtained shape of the workpiece. However, the known solutions take into consideration only programmed movements of the tool relative to the workpiece without considering vibrations, and those in which attempts have been made to consider vibrations have significant limitations. This paper uses a Geometric Simulator that determines the nominal positions of the tool relative to the workpiece, to which the displacements due to vibration, determined by the Dynamic Simulator, are added, making it possible to effectively determine the dynamic thickness of the cut layer and the trace on the workpiece material left by the vibrating tool. The use of geometric simulation, in which the material is represented by discrete voxels, introduces signal quantization, that is, the limited resolution of undeformed chip thickness and trace left on the machined surface. The paper presents the effect of voxel dimension on the accuracy of the simulation of self-excited vibrations.
Twórcy
  • Kazimierz Pulaski University of Technology and Humanities in Radom, ul. Stasieckiego 54, 26-600 Radom, Poland
  • Warsaw University of Technology, ul. Narbutta 86, 02-524 Warsaw, Poland
Bibliografia
  • 1. Zhu L., Liu C. Recent progress of chatter prediction, detection and suppression in milling. Mechanical Systems and Signal Processing 2020; 143: 106840.
  • 2. Altintas Y., Stepan G., Budak E., Schmitz T., Kilic Z. M. Chatter Stability of Machining Operations. Journal of Manufacturing Science and Engineering 2020; 142(11): 110801.
  • 3. Munoa J., Beudaert X., Dombovari Z., Altintas Y., Budak E., Brecher C., Stepan G. Chatter suppression techniques in metal cutting. CIRP Annals – Manufacturing Technology 2016; 65(2): 785–808.
  • 4. Bąk P.A., Jemielniak K. Self-excited vibrations avoidance methodology in non-linear numerical simulation environment. Procedia CIRP 2017; 62: 245–249.
  • 5. Jemielniak K., Widota A. Numerical simulation of non-linear chatter vibration in turning, I International Journal of Machine Tools and Manufacture 1989; 29: 239–247.
  • 6. Altintas Y., Kersting P., Biermann D., Budak E., Denkena B., Lazoglu I. Virtual process systems for part machining operations, CIRP Annals-Manufacturing Technology 2014; 63: 585–605.
  • 7. Yang Y., Zhang W., Wan M., Ma Y. A solid trimming method to extract cutter–workpiece engagement maps for multi-axis milling, The International Journal of Advanced Manufacturing Technology 2013; 68: 2801–2813.
  • 8. Yousefian O.,Balabokhin A., Tarbutton J. Point-by-point prediction of cutting force in 3-axis CNC milling machines through voxel framework in digital manufacturing. Journal of Intelligent Manufacturing 2020; 31: 215–226.
  • 9. Xi X., Cai Y., Wang H., Zhao D. A prediction model of the cutting force–induced deformation while considering the removed material impact. The International Journal of Advanced Manufacturing Technology 2022; 119: 1579–1594.
  • 10. Nishida I., Okumura, Sato R., Shirase K. Cutting Force and Finish Surface Simulation of End Milling Operation in Consideration of Static Tool Deflection by Using Voxel Model. Procedia CIRP 2018; 77: 574–577.
  • 11. Li J., Kilic Z.M., Altintas Y. General Cutting Dynamics Model for Five-Axis Ball-End Milling Operations. ASME. J. Manuf. Sci. Eng. 2020; 142(12): 121003.
  • 12. Denkena B., Grove T., Pape O. Optimization of complex cutting tools using a multi-dexel based material removal simulation. Procedia CIRP 2019; 82: 379–382.
  • 13. Denkena B., Pape O., Krödel A., Böß V., Ellersiek L., Mücke A. Process design for 5-axis ball end milling using a real-time capable dynamic material removal simulation. Production Engineering 2021; 15: 89–95.
  • 14. Engin S., Altintas Y. Generalized modeling of milling mechanics and dynamics: Part I–Helical end mills. American Society of Mechanical Engineers Manufacturing Engineering Division MED 1997; 10345: 352.
  • 15. Zhu L., Liu C. Recent progress of chatter prediction, detection and suppression in milling. Mechanical Systems and Signal Processing 2020; 143: 06840.
  • 16. Tlusty J., Ismail F. Basic Non-linearity in Machining Chatter. CIRP Annals – Manufacturing Technology, 1981; 30: 21–25.
  • 17. Tunc L.T., Mohammadi Y., Budak E. Destabilizing effect of low frequency modes on process damped stability of multi-mode milling systems. Mechanical Systems and Signal Processing 2018; 111: 423–441.
  • 18. Altintas Y. Manufacturing automation: Metal cutting mechanics machine tool vibrations and CNC design. Cambridge University Press, 2012.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-0d545bd9-85f2-48d4-b98e-94d072b63de7
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