Parametric evaluation of part distortion in additive manufacturing processes

Abstract

Additive manufacturing is the more and more considered in industry, however efficient simulation tools able to perform accurate predictions are still quite limited. The main difficulties for an efficient simulation are related to the multiple scales, the multiple and complex physics involved, as well as the strong dependency on the process trajectory. This paper aims at proposing a simplified parametric modeling and its subsequent parametric solution for evaluating parametrically the manufactured part distortion. The involved parameter are the ones parametrizing the process trajectories, the thermal shrinkage intensity and anisotropy (the former depending on several material and process parameters and the last directly depending on the process trajectory) and the deposited layers. The resulting simulation tool allows evaluating in real-time the impact of the parameters just referred on the part distortion, and proceed to the required geometrical compensation.

This is a preview of subscription content, log in to check access.

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

References

  1. 1.

    Aguado JV, Bognet B, Canales D, Desmaison O, Boitout F, Chinesta F (2017) A reduced order modeling approach for fast thermo-mechanics simulation of additive layer manufacturing. ECCOMAS Conference on Simulation for Additive Manufacturing, Munich, Germany

  2. 2.

    Bur N, Joyot P, Ghnatios C et al (2016) . Adv Model Simul Eng Sci 3:4. https://doi.org/10.1186/s40323-016-0056-x

    Article  Google Scholar 

  3. 3.

    Chen T, Zhang Y, Yuwen (2004) Numerical simulation of two-dimensional melting and resolidification of a two-component metal powder layer in selective laser sintering process. Numerical Heat Transfer, Part A: Applications 46(7):633–649

    Article  Google Scholar 

  4. 4.

    Chinesta F, Ladeveze P, Cueto E (2011) A short review in model order reduction based on proper generalized decomposition. Arch Comput Methods Eng 18:395–404

    Article  Google Scholar 

  5. 5.

    Chinesta F, Leygue A, Bordeu F, Aguado JV, Cueto E, Gonzalez D, Alfaro I, Ammar A, Huerta A (2013) PGD-based computational vademecum for efficient design, optimization and control. Arch Comput Methods Eng 20:31–59

    MathSciNet  Article  Google Scholar 

  6. 6.

    Chinesta F, Keunings R, Leygue A (2014) The proper generalized decomposition for advanced numerical simulations. A primer. Springerbriefs, Springer

  7. 7.

    Chinesta F, Ladeveze P (eds) (2014) Separated Representations and PGD Based Model Reduction: Fundamentals and Applications. CISM-Springer, Berlin

  8. 8.

    Chinesta F, Leygue A, Bognet B, Ghnatios C, Poulhaon F, Bordeu F, Barasinski A, Poitou A, Chatel S, Maison-Le-Poec S (2014) First steps towards an advanced simulation of composites manufacturing by automated tape placement. Int J Mater Form 7:81–92

    Article  Google Scholar 

  9. 9.

    Chinesta F, Huerta A, Rozza G, Willcox K (2015). In: Stein E, de Borst R, Hughes T (eds) Model order reduction. Chapter in the encyclopedia of computational mechanics, 2nd edn. Wiley, New York

  10. 10.

    Chiumenti M, Cervera M, Salmi A, Agelet de Saracibar C, Dialami N, Matsui K (2010) Finite element modeling of multi-pass welding and shaped metal deposition processes. Comput Methods Appl Mech Eng 199(37):2343–2359

    Article  Google Scholar 

  11. 11.

    Chiumenti M, Lin X, Cervera M, Lei W, Zheng Y, Huang W (2017) Numerical simulation and experimental calibration of Additive Manufacturing by blown powder technology. Part I: thermal analysis. Rapid Prototyping Journal. (In press)

  12. 12.

    Dai D, Gu D (2014) Thermal behavior and densification mechanism during selective laser melting of copper matrix composites: Simulation and experiments. Mater Des 55:482– 491

    Article  Google Scholar 

  13. 13.

    Ding J, Colegrove P, Mehnen J, Sequeira Almeida PM, Wang F, Williams S (2011) Thermomechanical analysis of wire and arc additive layer manufacturing process on large multi-layer parts. Comput Mater Sci 50:3315–3322

    Article  Google Scholar 

  14. 14.

    Dong L, Makradi A, Ahzi S, Remond Y (2009) Three-dimensional transient finite element analysis of the selective laser sintering process. J Mater Process Technol 209(2):700– 706

    Article  Google Scholar 

  15. 15.

    Foteinopoulos P, Papacharalampopoulos A, Stavropoulos P (2018) On thermal modeling of additive manufacturing processes. CIRP J Manuf Sci Technol 20:66–83

    Article  Google Scholar 

  16. 16.

    Heigel JC, Michaleris P, Reutzel EW (2015) Thermo-mechanical model development and validation of directed energy deposition additive manufacturing of Ti-6Al-4V. Addit Manuf 5:9– 19

    Article  Google Scholar 

  17. 17.

    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 

  18. 18.

    Korner C, Attar E, Heinl P (2011) Mesoscopic simulation of selective beam melting processes. J Mater Process Technol 211(6):978–987

    Article  Google Scholar 

  19. 19.

    Korner C, Bauereis A, Attar E (2013) Fundamental consolidation mechanisms during selective beam melting of powders. Model Simul Mater Sci Eng 21(8):085011

    Article  Google Scholar 

  20. 20.

    Kolossov S, Boillat E, Glardon R, Fischer P, Locher M (2004) 3D FE simulation for temperature evolution in the selective laser sintering process. Int J Mach Tools Manuf 44(2):117– 123

    Article  Google Scholar 

  21. 21.

    Kovaleva I, Kovalev O, Smurov I (2014) Model of heat and mass transfer in random packing layer of powder particles in selective laser melting. Phys Procedia 56:400–410

    Article  Google Scholar 

  22. 22.

    Labudovic M, Hu D, Kovacevic R (2003) A three dimensional model for direct laser metal powder deposition and rapid prototyping. J Mater Sci 38:35–49

    Article  Google Scholar 

  23. 23.

    Loh L, Chua C, Yeong W, Song J, Mapar M, Sing S, Liu Z, Zhang D (2015) Numerical investigation and an effective modelling on the selective laser melting (SLM) process with aluminium alloy 6061. Int J Heat Mass Transfer 80:288–300

    Article  Google Scholar 

  24. 24.

    Li Y, Gu D (2014) Parametric analysis of thermal behavior during selective laser melting additive manufacturing of aluminum alloy powder. Mater Des 63:856–867

    Article  Google Scholar 

  25. 25.

    Marimuthu S, Clark D, Allen J, Kamara AM, Mativenga P, Li L, Scudamore R (2013) Finite element modelling of substrate thermal distortion in direct laser additive manufacture of an aero-engine component. Proc Inst Mech Eng C J Mech Eng Sci 227(9):1987–1999

    Article  Google Scholar 

  26. 26.

    Zekovic S, Dwivedi R, Kovacevic R (2005) Thermo-structural finite element analysis of direct laser metal deposited thin-walled structures. In: 16th Solid Freeform Fabrication Symposium, SFF 2005, pp 338–355

  27. 27.

    Zeng K, Pal D, Patil N, Stucker BE (2013) A new dynamic mesh method applied to the simulation of selective laser melting. Proceedings of the Solid Freeform Fabrication Symposium, Austin, TX Aug. 12-14, pp 549–559

Download references

Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 675919. Authors also thank the partners of the SOFIA projet.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Francisco Chinesta.

Ethics declarations

Conflict of interests

The authors declare that they have no conflict of interest.

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

Verify currency and authenticity via CrossMark

Cite this article

Quaranta, G., Haug, E., Duval, J.L. et al. Parametric evaluation of part distortion in additive manufacturing processes. Int J Mater Form 13, 29–41 (2020). https://doi.org/10.1007/s12289-018-01462-3

Download citation

Keywords

  • Vademecum
  • Additive manufacturing
  • PGD
  • MOR
  • Thermal shrinkage
  • Part distortions
  • Geometry compensation