EFFECT OF ORIENTATION DISTANCE ON TEMPERATURE INDUCED PROBLEMS IN MULTI-PART MANUFACTURING BY SELECTIVE LASER MELTING

Year 2021, , 43 - 55, 30.04.2021

Nihat Yılmaz , Mevlüt Yunus Kayacan

https://doi.org/10.46519/ij3dptdi.891800

Abstract

SLM methods are widely used to manufacture metal parts for functional use in mainly automotive, aerospace and medical industries. Besides many advantages of SLM, manufacturing times take long times and need many costs. In this study, nine samples were manufactured at the same time to set a scenario of multiple samples manufacturing and providing highly productive conditions. Some manufacturing problems such as internal stresses and dimensional distortions occurred during manufacturing. These problems were the result of heterogeneous temperature gradients and geometrical properties. FEA studies were carried out by “Netfabb Ultimate Simulation LT 2019”. Temperature changes were observed, and relations among these temperature changes, residual stresses, as well as dimensional distortions were evaluated. As a result, the orientation distance of samples was an important parameter due to residual stress and displacement. Unsuitable positioning distance between samples caused high dimensional distortion, macro cracks and residual stress. The plastic strain equation was correlated according to the results of the analysis with 7% difference (regression) to define the optimum distance between parts.

Keywords

powder bed fusion, SLM, Additive Manufacturing, Part orientation, residual stress

Supporting Institution

yok

Project Number

yok

Thanks

Authors are thankful to Autodesk for significant supports by supplying Netfabb Simulation Utility.

References

• 1. Bikas, H., Stavropoulos, R., Chryssolouris, G., “Additive manufacturing methods and modelling approaches: a critical review”, Int J Adv Manuf Technol, Vol.83, Pages 389–405, 2016.
• 2. Priarone, P.C., Lunetto, V., Atzeni, E., Salmi, A., “Laser powder bed fusion (L-PBF) additive manufacturing: On the correlation between design choices and process sustainability”, Procedia CIRP, Vol.78, Pages 85-90, 2018.
• 3. Singh, R., Davim, P., “Additive manufacturing: Application and innovations”, CRC Press, Taylor-Francis Group, 2019.
• 4. Lee, Y. S., Zhang, W., “Mesoscopic simulation of heat transfer and fluid flow in laser powder bed additive manufacturing. In International Solid Free Form Fabrication Symposium”, Austin Pages 1154-1165, 2015.
• 5. Manvatkar, V., De, A., DebRoy, T., “Heat transfer and material flow during laser assisted multi-layer additive manufacturing”, Journal of Applied Physics, Vol.116, Pages 124905, 2014.
• 6. Yang, Y.P., Jamshidinia, M., Boulware, P., Kelly, S.M., “Prediction of microstructure, residual stress, and deformation in laser powder bed fusion process”, Computational Mechanics, Vol.61, Pages 599–615, 2018.
• 7. Ning Y., Fuh J. Y. H., Wong Y. S., Loh H. T., “An intelligent parameter selection system for the direct metal laser sintering process”. Int. J. Prod. Res, Cilt 42, Sayı 1, Sayfa 183–199, 2004.
• 8. Yang C., Hao L., Hussein A., Young P., Huang J., Zhu W., “Microstructure and mechanical properties of aluminum alloy cellular lattice structures manufactured by direct metal laser sintering”. Mater. Sci. Eng. A, Vol.628, Pages 238-246, 2015.
• 9. Poyraz, Ö., Kuşhan, M. C. “Investigation of the effect of different process parameters for laser additive manufacturing of metals.” Journal of the Faculty of Engineering and Architecture of Gazi University, Vol. 33, Issue 2, Pages 729-742, 2018.
• 10. Li, Y., Zhou, K., Tan, P., Tor, S. B., Chua, C. K., Leong, K. F., “Modeling temperature and residual stress fields in selective laser melting”, International Journal of Mechanical Sciences, Vol.136, Pages 24-35, 2018.
• 11. Park, H. S., Tran, N. H., Nguyen, D. S., “Development of a predictive system for SLM product quality”. In IOP Conference Series: Materials Science and Engineering, Vol.227, Issue 1, Pages 012090, 2018.
• 12. Mukherjee, T., Manvatkar, V., De, A., &DebRoy, T., “Mitigation of thermal distortion during additive manufacturing”, Scriptamaterialia, Vol.127, Pages 79-83, 2017.
• 13. Yan Z, Liu W, Tang Z, Liu X, Zhang N, Li M, Zhang H., “Review on thermal analysis in laser-based additive manufacturing”, Optics and Laser Technology, Vol.106, Pages 427-441, 2018. 14. Li, C., Fu, C.H., Guo Y.B., Fang, F.Z., “A multiscale modeling approach for fast prediction of part distortion in selective laser melting”, Journal of Materials Processing Technology, Vol.229, Pages 703-712, 2016.
• 15. EOS GMBH, “Material data sheet – Flexline EOS Titanium Ti64”, EOS GmbH – Electro Optical Systems, 2018.
• 16. Stout, R., Billings, P.D., “Accuracy and time resolution in thermal transient finite element analysis”, Semiconductor P. E. O. N. ANSYS™ users conference, 2002.
• 17. Olleak, A., Xi, Z., “Finite Element Modeling of the Selective Laser Melting Process for Ti-6Al-4V”, Solid Freeform Fabrication 2018: Proceedings of the 29th Annual International, Pages 1710-1720, 2018.
• 18. Yakout, M., Elbestawi, M. A., Veldhuis, S. C., & Nangle-Smith, S.,“Influence of thermal properties on residual stresses in SLM of aerospace alloys”, Rapid Prototyping Journal, Vol.26, Issue 1, 2019.
• 19. Chen, Y., “The origin of the distinction between microscopic formulas for stress and Cauchy stress”, Europhysics Letters, Vol.116, Issue 3, Pages 34003, 2016.
• 20. Cauchy stress tensors, https://wikipedia.org/wiki/Cauchy_stress_tensoren, Nov 15, 2019