Skip to main content
SpringerLink
Log in

Geometrical Simulation Model for Milling of Carbon Fiber Reinforced Polymers (CFRP)

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

Abstract

This paper proposes a geometrical 3D milling simulation algorithm for Carbon Fiber Reinforced Polymer (CFRP) milling. In this simulation model, milling tools are simplified into layers of circles while CFRP lami- nates are simplified into layers of Dexel lines, which can realize simulations for various complex milling conditions. Significant geometrical parameters, for ex-ample, cutting angle and cutting length, can be computed with high efficiency. With some geometry-related physical models, the machining results can be pre-dicted for the entire milling process. The effectiveness of this simulation model has been validated by the milling force prediction and the delamination pre-diction. The performance of this simulation model benefits industrial CFRP manufacturing and provides a new method for online or long-time-interval simulation of CFRP machining.

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
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29

Similar content being viewed by others

Availability of data and materials

The machining results and prediction results have been presented in this research. Derived data supporting the findings of this study are available from the corresponding author Martin Byung-Guk Jun on request.

Code availability

The algorithm used to support the findings of this study is included within the article.

References

  1. Perner, M., Algermissen, S., Keimer, R., & Monner, H. P. (2016). Avoiding defects in manufacturing processes: A review for automated CFRP production. Robotics and Computer-Integrated Manufacturing, 38, 82–92.

    Article  Google Scholar 

  2. Birk, F., Ali, F., Weigold, M., Abele, E., & Schützer, K. (2020). Lightweight hybrid CFRP design for machine tools with focus on simple manufacturing. International Journal of Advanced Manufacturing Technology, 108(11), 3915–3924.

    Article  Google Scholar 

  3. James, S., Sonate, A., Dang, C. & De La Luz L. (2018). Experimental and simulation study of ultrasonic additive manufacturing of CFRP/Ti stacks. In International manufacturing science and engineering conference (Vol. 51388, pp. V004T03A044).

  4. Hintze, W., Hartmann, D., & Schütte, C. (2011). Occurrence and propagation of delamination during the machining of carbon fibre reinforced plastics (CFRPs)–an experimental study. Composites Science and Technology, 71(15), 1719–1726.

    Article  Google Scholar 

  5. Knops, M. (2008). Analysis of failure in fiber polymer laminates: the theory of Alfred puck. Springer.

    Google Scholar 

  6. Kerrigan, K., & O’Donnell, G. E. (2013). Temperature measurement in CFRP milling using a wireless tool-integrated process monitoring sensor. International Journal of Automation Technology, 7(6), 742–750.

    Article  Google Scholar 

  7. Rentsch, R., Pecat, O., & Brinksmeier, E. (2011). Macro and micro process modeling of the cutting of carbon fiber reinforced plastics using FEM. Procedia Engineering, 10, 1823–1828.

    Article  Google Scholar 

  8. Pecat, O., Rentsch, R., & Brinksmeier, E. (2012). Influence of milling process parameters on the surface integrity of CFRP. Procedia CIRP, 1, 466–470.

    Article  Google Scholar 

  9. Gao, C., Xiao, J., Xu, J., & Ke, Y. (2016). Factor analysis of machining parameters of fiber-reinforced polymer composites based on finite element simulation with experimental investigation. International Journal of Advanced Manufacturing Technology, 83(5–8), 1113–1125.

    Article  Google Scholar 

  10. Santiuste, C., Olmedo, A., Soldani, X., & Miguélez, H. (2012). Delamination prediction in orthogonal machining of carbon long fiber-reinforced polymer composites. Journal of Reinforced Plastics and Composites, 31(13), 875–885.

    Article  Google Scholar 

  11. Phadnis, V. A., Makhdum, F., Roy, A., & Silberschmidt, V. V. (2013). Drilling in carbon/epoxy composites: Experimental investigations and finite element implementation. Composites Part A, Applied Science and Manufacturing, 47, 41–51.

    Article  Google Scholar 

  12. Usui, S., Wadell, J., & Marusich, T. (2014). Finite element modeling of carbon fiber composite orthogonal cutting and drilling. Procedia CIRP, 14, 211–216.

    Article  Google Scholar 

  13. KoPlev, A. A., Lystrup, A., & Vorm, T. (1983). The cutting process, chips, and cutting forces in machining CFRP. Composites, 14(4), 371–376.

    Article  Google Scholar 

  14. Karpat, Y., Bahtiyar, O., & Değer, B. (2012). Mechanistic force modeling for milling of unidirectional carbon fiber reinforced polymer laminates. International Journal of Machine Tools and Manufacture, 56, 79–93.

    Article  Google Scholar 

  15. Voss, R., Seeholzer, L., Kuster, F., & Wegener, K. (2017). Influence of fibre orientation, tool geometry and process parameters on surface quality in milling of CFRP. CIRP Journal of Manufacturing Science and Technology, 18, 75–91.

    Article  Google Scholar 

  16. Haiyan, W., Xuda, Q., Hao, L., & Chengzu, R. (2013). Analysis of cutting forces in helical milling of carbon fiber–reinforced plastics. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 227(1), 62–74.

    Article  Google Scholar 

  17. Chao, P. Y., & Hwang, Y. D. (1997). An improved Taguchi’s method in design of experiments for milling CFRP composite. International Journal of Production Research, 35(1), 51–66.

    Article  MATH  Google Scholar 

  18. Zhao, W., & Qian, X. (2009). Mathematical Morphology in Multi-Dexel Representation. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 48999, 733–742.

    Google Scholar 

  19. Liu, S. Q., Ong, S.-K., Chen, Y. P., & Nee, A. Y. C. (2006). Real-time, dynamic level-of-detail management for three-axis NC milling simulation. Computer Design, 38(4), 378–391.

    Google Scholar 

  20. Stifter, S. (1995). Simulation of NC machining based on the dexel model: A critical analysis. International Journal of Advanced Manufacturing Technology, 10(3), 149–157.

    Article  Google Scholar 

  21. Konig, A. H., & Groller, E. (1998). Real time simulation and visualization of NC milling processes for inhomogeneous materials on low-end graphics hardware. IEEE.

    Book  Google Scholar 

  22. Sullivan, A., Erdim, H., Perry, R. N., & Frisken, S. F. (2012). High accuracy NC milling simulation using composite adaptively sampled distance fields. Computer Design, 44(6), 522–536.

    Google Scholar 

  23. Koenigsberger, F., & Sabberwal, A. J. P. (1961). An investigation into the cutting force pulsations during milling operations. International Journal of Machine Tool Design and Research, 1(1–2), 15–33.

    Article  Google Scholar 

  24. Budak, E., Altintas, Y., & Armarego, E. J. A. (1996). Prediction of milling force coefficients from orthogonal cutting data. Journal of Manufacturing Science and Engineering, 118(2), 216–224.

    Article  Google Scholar 

  25. Sheikh-Ahmad, J., Twomey, J., Kalla, D., & Lodhia, P. (2007). Multiple regression and committee neural network force prediction models in milling FRP. Machining Science and Technology, 11(3), 391–412.

    Google Scholar 

  26. Haiyan, W., & Xuda, Q. (2016). A mechanistic model for cutting force in helical milling of carbon fiber-reinforced polymers. International Journal of Advanced Manufacturing Technology, 82(9), 1485–1494.

    Article  Google Scholar 

Download references

Acknowledgements

This work is funded by the Ministry of Trade, Industry, and Energy (MOTIE, Korea).

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN, 47907, USA

    Xingyu Fu, Kyeongeun Song & Martin Byung-Guk Jun

  2. Indiana Manufacturing Competitiveness Center (IN-MaC), West Lafayette, IN, 47907, USA

    Martin Byung-Guk Jun

  3. School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, Jiangsu, 211800, China

    Zhengyang Kang

  4. Dongnam Division, Korea Institute of Industrial Technology, Jeongchon-myeon, Jinju-si, 52845, Gyeongsangnam-do, Republic of Korea

    Dong Min Kim

Authors
  1. Xingyu Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kyeongeun Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dong Min Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhengyang Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martin Byung-Guk Jun
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

XF contributed to the experimentation, programming of the software, writing of the research paper. KS contributed to the writing and experimentation. DMK contributed to the literature review and advising. ZK contributed to the writing of the manuscript. and MBJ provided the idea and supervised the work. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Martin Byung-Guk Jun.

Ethics declarations

Ethics approval and consent to participate

The research does not involve ethical issues.

Consent for publication

All the authors consent to publish this work.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

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

Fu, X., Song, K., Kim, D.M. et al. Geometrical Simulation Model for Milling of Carbon Fiber Reinforced Polymers (CFRP). Int. J. Precis. Eng. Manuf. 23, 1237–1260 (2022). https://doi.org/10.1007/s12541-022-00681-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-022-00681-8

Keywords

Search

Navigation