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Parametric evaluation of part distortion in additive manufacturing processes

  • Giacomo Quaranta
  • Eberhard Haug
  • Jean Louis Duval
  • Francisco ChinestaEmail author
Original Research
  • 70 Downloads

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.

Keywords

Vademecum Additive manufacturing PGD MOR Thermal shrinkage Part distortions Geometry compensation 

Notes

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.

Compliance with Ethical Standards

Conflict of interests

The authors declare that they have no conflict of interest.

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, GermanyGoogle Scholar
  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 CrossRefGoogle 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):633–649CrossRefGoogle 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 18:395–404CrossRefGoogle 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 20:31–59MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Chinesta F, Keunings R, Leygue A (2014) The proper generalized decomposition for advanced numerical simulations. A primer. Springerbriefs, SpringerGoogle Scholar
  7. 7.
    Chinesta F, Ladeveze P (eds) (2014) Separated Representations and PGD Based Model Reduction: Fundamentals and Applications. CISM-Springer, BerlinGoogle Scholar
  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 7:81–92CrossRefGoogle 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 YorkGoogle Scholar
  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):2343–2359CrossRefzbMATHGoogle 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)Google Scholar
  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– 491CrossRefGoogle 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 50:3315–3322CrossRefGoogle 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– 706CrossRefGoogle Scholar
  15. 15.
    Foteinopoulos P, Papacharalampopoulos A, Stavropoulos P (2018) On thermal modeling of additive manufacturing processes. CIRP J Manuf Sci Technol 20:66–83CrossRefGoogle 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– 19CrossRefGoogle 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– 45CrossRefGoogle Scholar
  18. 18.
    Korner C, Attar E, Heinl P (2011) Mesoscopic simulation of selective beam melting processes. J Mater Process Technol 211(6):978–987CrossRefGoogle 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):085011CrossRefGoogle 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– 123CrossRefGoogle 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 56:400–410CrossRefGoogle 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 38:35–49CrossRefGoogle 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 80:288–300CrossRefGoogle 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 63:856–867CrossRefGoogle 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):1987–1999CrossRefGoogle 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 338–355Google Scholar
  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 549–559Google Scholar

Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  1. 1.ESI GroupParc IcadeRungis CedexFrance
  2. 2.PIMM, ENSAM ParisTechESI GROUP Chair on Advanced Modeling and Simulation of Manufacturing ProcessesParisFrance

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