Skip to main content

Effect of Build Orientation on Cross-Sectional Areas of Sliced Layers and Geometrical Accuracy in Selective Laser Melting

  • Conference paper
  • First Online:
Recent Advances in Intelligent Manufacturing and Service Systems

Abstract

Additive manufacturing is a manufacturing process that allows the production of complex parts and has many advantages over conventional production methods. However, the pre-processing stage is still time-consuming and open to failure. Build orientation is one of the pre-processing stages, which have a crucial effect on support requirement, build cost, and accuracy of the produced part. In recent years, a number of research have been made to optimize build orientation for surface roughness, the requirement of support structures, build time, and cost. For metallic additive manufacturing, a limited number of research has been carried out. Selective laser melting is one of the powder bed fusion technologies that allows the production of high-performance metallic parts. In the selective laser melting process, some defects may occur due to residual stresses resulting from solidification during the process. Build orientation is important in selective laser melting to ensure proper heat flow throughout to entire structure during the process. After the build orientation is selected, the part slices into layers. Each layer builds on the previous layer, and production carries out. The cross-sectional areas of these sliced layers depend on the build orientation. This study investigates the effect of cross-sectional areas on the geometric accuracy of the part. The numerical evaluation shows that the distribution of layers has a significant impact on geometrical accuracy. First, the effect of the mean cross-sectional area on the thermal distortion was investigated. It is observed that the geometric accuracy of the part decreases for the build orientation, which has a higher mean cross-sectional area. In addition, it is revealed that the increase and sudden change of the cross-sectional area in the build direction negatively affect the geometric accuracy.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bourell DL (2016) Perspectives on additive manufacturing. Annu Rev Mater Res 46(1):1–18. https://doi.org/10.1146/annurev-matsci-070115-031606

    Article  Google Scholar 

  2. Wodziak JR, Fadel GM, Kirschman C (1994) A genetic algorithm for optimizing multiple part placement to reduce build time. In: Proc Fifth Int Conf Rapid Prototyping, no. May, pp 201–210

    Google Scholar 

  3. Alexander P, Allen S, Dutta D (1998) Part orientation and build cost determination in layered manufacturing. CAD Comput Aided Des 30(5):343–356. https://doi.org/10.1016/S0010-4485(97)00083-3

    Article  Google Scholar 

  4. Thrimurthulu K, Pandey PM, Reddy NV (2004) Optimum part deposition orientation in fused deposition modeling. Int J Mach Tools Manuf 44(6):585–594. https://doi.org/10.1016/j.ijmachtools.2003.12.004

    Article  Google Scholar 

  5. Byun HS, Lee KH (2006) Determination of optimal build direction in rapid prototyping with variable slicing. Int J Adv Manuf Technol 28(3–4):307–313. https://doi.org/10.1007/s00170-004-2355-5

    Article  Google Scholar 

  6. Canellidis V, Giannatsis J, Dedoussis V (2009) Genetic-algorithm-based multi-objective optimization of the build orientation in stereolithography. Int J Adv Manuf Technol 45(7–8):714–730. https://doi.org/10.1007/s00170-009-2006-y

    Article  Google Scholar 

  7. Li A, Zhang Z, Wang D, Yang J (2010) Optimization method to fabrication orientation of parts in fused deposition modeling rapid prototyping. Int Conf Mech Autom Control Eng MACE2010 pp 416–419. https://doi.org/10.1109/MACE.2010.5535335

  8. Luo Z, Yang F, Dong G, Tang Y, Zhao YF (2018) Orientation optimization in layer-based additive manufacturing process. Proc ASME Des Eng Tech Conf 1A–2016(January):2016. https://doi.org/10.1115/DETC2016-59969

    Article  Google Scholar 

  9. Rocha AMAC, Pereira AI, Vaz AIF (2018) Build orientation optimization problem in additive manufacturing, vol 10961, LNCS, no. February 2019. Springer International Publishing

    Google Scholar 

  10. Ga B, Gardan N, Wahu G (2018) Methodology for part building orientation in additive manufacturing. Comput Aided Des Appl 16(1):113–128. https://doi.org/10.14733/cadaps.2019.113-128

    Article  Google Scholar 

  11. Matos MA, Rocha AMAC, Pereira AI (2019) On optimizing the build orientation problem using genetic algorithm. In: AIP Conference Proceedings, vol 2116, p. 220006. https://doi.org/10.1063/1.5114224

  12. Di Angelo L, Di Stefano P, Dolatnezhadsomarin A, Guardiani E, Khorram E (2020) A reliable build orientation optimization method in additive manufacturing: the application to FDM technology. Int J Adv Manuf Technol 108(1–2):263–276. https://doi.org/10.1007/s00170-020-05359-x

    Article  Google Scholar 

  13. Matos MA, Rocha AMAC, Costa LA (2021) Many-objective optimization of build part orientation in additive manufacturing. Int J Adv Manuf Technol 112(3–4):747–762. https://doi.org/10.1007/s00170-020-06369-5

    Article  Google Scholar 

  14. Phatak AM, Pande SS (2012) Optimum part orientation in rapid prototyping using genetic algorithm. J Manuf Syst 31(4):395–402. https://doi.org/10.1016/j.jmsy.2012.07.001

    Article  Google Scholar 

  15. Zhang Y, Bernard A (2013) Using AM feature and multi-attribute decision making to orientate part in additive manufacturing. In: High value manufacturing: advanced research in virtual and rapid prototyping, CRC Press, pp 411–416

    Google Scholar 

  16. Zhang Y, De Backer W, Harik R, Bernard A (2016) Build orientation determination for multi-material deposition additive manufacturing with continuous fibers. Procedia CIRP 50:414–419. https://doi.org/10.1016/j.procir.2016.04.119

    Article  Google Scholar 

  17. Zhang Y, Bernard A, Gupta RK, Harik R (2016) Feature based building orientation optimization for additive manufacturing. Rapid Prototyp J 22(2):358–376. https://doi.org/10.1108/RPJ-03-2014-0037

    Article  Google Scholar 

  18. Ransikarbum K, Ha S, Ma J, Kim N (2017) Multi-objective optimization analysis for part-to-Printer assignment in a network of 3D fused deposition modeling. J Manuf Syst 43:35–46. https://doi.org/10.1016/j.jmsy.2017.02.012

    Article  Google Scholar 

  19. Jaiswal P, Patel J, Rai R (2018) Build orientation optimization for additive manufacturing of functionally graded material objects. Int J Adv Manuf Technol 96(1–4):223–235. https://doi.org/10.1007/s00170-018-1586-9

    Article  Google Scholar 

  20. Calignano F (2014) Design optimization of supports for overhanging structures in aluminum and titanium alloys by selective laser melting. Mater Des 64:203–213. https://doi.org/10.1016/j.matdes.2014.07.043

    Article  Google Scholar 

  21. Das P, Chandran R, Samant R, Anand S (2015) Optimum part build orientation in additive manufacturing for minimizing part errors and support structures. Procedia Manuf 1:343–354. https://doi.org/10.1016/j.promfg.2015.09.041

    Article  Google Scholar 

  22. Morgan HD, Cherry JA, Jonnalagadda S, Ewing D, Sienz J (2016) Part orientation optimisation for the additive layer manufacture of metal components. Int J Adv Manuf Technol 86(5–8):1679–1687. https://doi.org/10.1007/s00170-015-8151-6

    Article  Google Scholar 

  23. Brika S, Zhao YF, Brochu M, Mezetta J (2017) Multi-Objective build orientation optimization for powder bed fusion by laser. Ind Eng Manag 6(4). https://doi.org/10.4172/2169-0316.1000236

  24. Cheng L, To A (2019) Part-scale build orientation optimization for minimizing residual stress and support volume for metal additive manufacturing: theory and experimental validation. CAD Comput Aided Des 113:1–23. https://doi.org/10.1016/j.cad.2019.03.004

    Article  Google Scholar 

  25. Griffiths V, Scanlan JP, Eres MH, Martinez-Sykora A, Chinchapatnam P (2019) Cost-driven build orientation and bin packing of parts in Selective Laser Melting (SLM). Eur J Oper Res 273(1):334–352. https://doi.org/10.1016/j.ejor.2018.07.053

    Article  Google Scholar 

  26. Qin Y, Qi Q, Shi P, Scott PJ, Jiang X (2020) Automatic determination of part build orientation for laser powder bed fusion. Virtual Phys Prototyp. https://doi.org/10.1080/17452759.2020.1832793

    Article  Google Scholar 

  27. Qin Y, Qi Q, Shi P, Scott PJ, Jiang X (2020) Automatic generation of alternative build orientations for laser powder bed fusion based on facet clustering. Virtual Phys Prototyp 15(3):307–324. https://doi.org/10.1080/17452759.2020.1756086

  28. Fang ZC, Wu ZL, Huang CG, Wu CW (2020) Review on residual stress in selective laser melting additive manufacturing of alloy parts. Opt Laser Technol 129(15):106283. https://doi.org/10.1016/j.optlastec.2020.106283

    Article  Google Scholar 

  29. Ning J, Sievers DE, Garmestani H, Liang SY (2019) Analytical modeling of in-process temperature in powder bed additive manufacturing considering laser power absorption, latent heat, scanning strategy, and powder packing. Mater (Basel) 12(5):1–16. https://doi.org/10.3390/MA12050808

    Article  Google Scholar 

  30. Ning J, Wang W, Zamorano B, Liang SY (2019) Analytical modeling of lack-of-fusion porosity in metal additive manufacturing. Appl Phys A Mater Sci Process 125(11):1–11. https://doi.org/10.1007/s00339-019-3092-9

    Article  Google Scholar 

  31. Ning J, Sievers DE, Garmestani H, Liang SY (2020) Analytical modeling of in-process temperature in powder feed metal additive manufacturing considering heat transfer boundary condition. Int J Precis Eng Manuf-Green Technol 7(3):585–593. https://doi.org/10.1007/s40684-019-00164-8

    Article  Google Scholar 

  32. Xing W, Ouyang D, Li N, Liu L (2018) Estimation of residual stress in selective laser melting of a Zr-based amorphous alloy. Mater (Basel) 11(8). https://doi.org/10.3390/MA11081480

  33. Li C, Liu JF, Guo YB (2016) Prediction of residual stress and part distortion in selective laser melting. Proc CIRP 45:171–174. https://doi.org/10.1016/j.procir.2016.02.058

    Article  Google Scholar 

  34. Ning J, Praniewicz M, Wang W, Dobbs JR, Liang SY (2020) Analytical modeling of part distortion in metal additive manufacturing. Int J Adv Manuf Technol 107(1–2):49–57. https://doi.org/10.1007/s00170-020-05065-8

    Article  Google Scholar 

  35. Park HS, Ansari MJ (2020) Estimation of residual stress and deformation in selective laser melting of Ti6Al4V alloy. Proc CIRP 93:44–49. https://doi.org/10.1016/j.procir.2020.03.091

    Article  Google Scholar 

Download references

Acknowledgements

The corresponding author thanks the Scientific and Technological Research Council of Turkey (TÜBİTAK) for their support under 2244 - Industrial PhD Fellowship Program, Grant No: 118C100.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmet Can Günaydın .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Günaydın, A., Kaya, N., Yıldız, A. (2022). Effect of Build Orientation on Cross-Sectional Areas of Sliced Layers and Geometrical Accuracy in Selective Laser Melting. In: Sen, Z., Oztemel, E., Erden, C. (eds) Recent Advances in Intelligent Manufacturing and Service Systems. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-7164-7_2

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-7164-7_2

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7163-0

  • Online ISBN: 978-981-16-7164-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics