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Systematic approach for determining optimal processing parameters to produce parts with high density in selective laser melting process

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Abstract

Relying on trial-and-error methods to determine the optimal processing parameters which maximize the density of parts produced using selective laser melting (SLM) technique is costly and time consuming. With a given SLM machine characteristics (e.g., laser power, scanning speed, laser spot size, and laser type), powder material, and powder size distribution, the present study proposes a more systematic strategy to reduce the time and cost in finding optimal parameters for producing high-density components. In the proposed approach, a circle packing design algorithm is employed to identify 48 representative combinations of the laser scanning speed and laser power for a commercial Nd:YAG SLM system. For each parameter combination, finite element heat transfer simulations are performed to calculate the melt pool dimensions and peak temperature for 316L stainless steel powder deposited on a 316L substrate. The simulated results are then used to train the artificial neural networks (ANNs). The trained ANNs are used to predict the melt pool dimensions and peak temperature for 3600 combinations of the laser power and laser speed in the design space. The resulting processing maps are then inspected to determine the particular parameter combinations which produce stable single scan tracks with good adhesion to the substrate and a peak temperature lower than the evaporation point of the SS 316L powder bed. Finally, the surface roughness measurements are employed to confirm the parameter settings which maximize the SLM component density. The experimental results show that the proposed approach results in a maximum component density of 99.97 %, an average component density of 99.89%, and a maximum standard deviation of 0.03%.

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References

  1. Yadroitsev I, Gusarov A, Yadroitsava I, Smurov I (2010) Single track formation in selective laser melting of metal powders. J Mater Process Technol 210(12):1624–1631

    Article  Google Scholar 

  2. Kamath C (2016) Data mining and statistical inference in selective laser melting. Int J Adv Manuf Technol 86(5-8):1659–1677

    Article  Google Scholar 

  3. King WE, Barth HD, Castillo VM, Gallegos GF, Gibbs JW, Hahn DE, Kamath C, Rubenchik AM (2014) Observation of keyhole-mode laser melting in laser powder-bed fusion additive manufacturing. J Mater Process Technol 214(12):2915–2925

    Article  Google Scholar 

  4. Bajaj P, Wright J, Todd I, Jägle EA (2018) Predictive process parameter selection for selective laser melting manufacturing: applications to high thermal conductivity alloys. Addit Manuf 27:246–258

    Article  Google Scholar 

  5. Read N, Wang W, Essa K, Attallah MM (2015) Selective laser melting of AlSi10Mg alloy: process optimisation and mechanical properties development. Mater Des (1980-2015) 65:417–424

    Article  Google Scholar 

  6. Yadroitsev I, Krakhmalev P, Yadroitsava I (2015) Hierarchical design principles of selective laser melting for high quality metallic objects. Addit Manuf 7:45–56

    Article  Google Scholar 

  7. Kamath C, El-dasher B, Gallegos GF, King WE, Sisto A (2014) Density of additively-manufactured, 316L SS parts using laser powder-bed fusion at powers up to 400 W. Int J Adv Manuf Technol 74(1-4):65–78

    Article  Google Scholar 

  8. Verhaeghe F, Craeghs T, Heulens J, Pandelaers L (2009) A pragmatic model for selective laser melting with evaporation. Acta Mater 57(20):6006–6012

    Article  Google Scholar 

  9. Gusarov A, Smurov I (2010) Modeling the interaction of laser radiation with powder bed at selective laser melting. Phys Procedia 5:381–394

    Article  Google Scholar 

  10. Tran H-C, Lo Y-L, Huang M-H (2017) Analysis of scattering and absorption characteristics of metal powder layer for selective laser sintering. IEEE/ASME Trans Mechatron 22(4):1807–1817

    Article  Google Scholar 

  11. Tran H-C, Lo Y-L (2018) Heat transfer simulations of selective laser melting process based on volumetric heat source with powder size consideration. J Mater Process Technol 255:411–425

    Article  Google Scholar 

  12. Moser D, Pannala S, Murthy J (2015) Computation of effective radiative properties of powders for selective laser sintering simulations. JOM 67(5):1194–1202

    Article  Google Scholar 

  13. Boley C, Khairallah S, Rubenchik A (2015) Calculation of laser absorption by metal powders in additive manufacturing. Appl Opt 54(9):2477–2482

    Article  Google Scholar 

  14. Spierings A, Levy G (2009) Comparison of density of stainless steel 316L parts produced with selective laser melting using different powder grades. In: Proceedings of the Annual International Solid Freeform Fabrication Symposium. Austin, TX, pp 342-353

  15. Streek A, Regenfuss P, Exner H (2013) Fundamentals of energy conversion and dissipation in powder layers during laser micro sintering. Phys Procedia 41:858–869

    Article  Google Scholar 

  16. Roberts I, Wang C, Esterlein R, Stanford M, Mynors D (2009) A three-dimensional finite element analysis of the temperature field during laser melting of metal powders in additive layer manufacturing. Int J Mach Tools Manuf 49(12):916–923

    Article  Google Scholar 

  17. Yin J, Zhu H, Ke L, Hu P, He C, Zhang H, Zeng X (2016) A finite element model of thermal evolution in laser micro sintering. Int J Adv Manuf Technol 83(9-12):1847–1859

    Article  Google Scholar 

  18. Foroozmehr A, Badrossamay M, Foroozmehr E (2016) Finite element simulation of selective laser melting process considering optical penetration depth of laser in powder bed. Mater Des 89:255–263

    Article  Google Scholar 

  19. Han L, Phatak K, Liou F (2004) Modeling of laser cladding with powder injection. Metall Mater Trans B 35(6):1139–1150

    Article  Google Scholar 

  20. Khairallah SA, Anderson AT, Rubenchik A, King WE (2016) Laser powder-bed fusion additive manufacturing: Physics of complex melt flow and formation mechanisms of pores, spatter, and denudation zones. Acta Mater 108:36–45

    Article  Google Scholar 

  21. Gusarov A, Yadroitsev I, Bertrand P, Smurov I (2009) Model of radiation and heat transfer in laser-powder interaction zone at selective laser melting. J Heat Transf 131(7):072101

    Article  Google Scholar 

  22. Hodge N, Ferencz R, Solberg J (2014) Implementation of a thermomechanical model for the simulation of selective laser melting. Comput Mech 54(1):33–51

    Article  MathSciNet  Google Scholar 

  23. Kamath C, Fan Y (2017) Regression with small data sets: a case study using code surrogates in additive manufacturing. Knowl Inf Syst 57(2):475–493

    Article  Google Scholar 

  24. Fang K-T, Li R, Sudjianto A (2005) Design and modeling for computer experiments. Chapman and Hall/ CRC Press

  25. Ma M, Wang Z, Gao M, Zeng X (2015) Layer thickness dependence of performance in high-power selective laser melting of 1Cr18Ni9Ti stainless steel. J Mater Process Technol 215:142–150

    Article  Google Scholar 

  26. Di W, Yongqiang Y, Xubin S, Yonghua C (2012) Study on energy input and its influences on single-track, multi-track, and multi-layer in SLM. Int J Adv Manuf Technol 58(9-12):1189–1199

    Article  Google Scholar 

  27. Bean GE, Witkin DB, McLouth TD, Patel DN, Zaldivar RJ (2018) Effect of laser focus shift on surface quality and density of Inconel 718 parts produced via selective laser melting. Addit Manuf 22:207–215

    Article  Google Scholar 

  28. Thijs L, Verhaeghe F, Craeghs T, Van Humbeeck J, Kruth J-P (2010) A study of the microstructural evolution during selective laser melting of Ti–6Al–4V. Acta Mater 58(9):3303–3312

    Article  Google Scholar 

  29. Yasa E, Deckers J, Kruth J-P (2011) The investigation of the influence of laser re-melting on density, surface quality and microstructure of selective laser melting parts. Rapid Prototyp J 17(5):312–327

    Article  Google Scholar 

  30. Gan Z, Lian Y, Lin SE, Jones KK, Liu WK, Wagner GJ (2019) Benchmark study of thermal behavior, surface topography, and dendritic microstructure in selective laser melting of Inconel 625. Integr Mater Manuf Innov:1–16

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Acknowledgments

The authors gratefully acknowledge the financial support provided to this study by the Ministry of Science and Technology of Taiwan under Grant Nos. MOST 105-2218-E-006-015 and MOST 107-2218-E-006-051. Additionally, this research was, in part, supported by the Ministry of Education, Taiwan, Headquarter of University Advancement to the Intelligent Manufacturing Research Center (iMRC), National Cheng Kung University (NCKU).

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  1. Department of Mechanical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan

    Hong-Chuong Tran & Yu-Lung Lo

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  1. Hong-Chuong Tran
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  2. Yu-Lung Lo
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Correspondence to Yu-Lung Lo.

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Tran, HC., Lo, YL. Systematic approach for determining optimal processing parameters to produce parts with high density in selective laser melting process. Int J Adv Manuf Technol 105, 4443–4460 (2019). https://doi.org/10.1007/s00170-019-04517-0

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  • DOI: https://doi.org/10.1007/s00170-019-04517-0

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