Advertisement

Surface topography investigations on nickel alloy 625 fabricated via laser powder bed fusion

  • Tuğrul Özel
  • Ayça Altay
  • Alkan Donmez
  • Richard Leach
ORIGINAL ARTICLE
  • 121 Downloads

Abstract

Laser powder bed fusion as an additive manufacturing process produces complex surface topography at multiple scales through rapid heating, melting, directional cooling, and solidification that are often governed by laser path and layer-to-layer scanning strategies and influenced by process parameters such as power, scan velocity, hatch distance, and resultant energy density. Investigations on manufactured surfaces, as-built and after applying electropolishing, are performed using stylus profilometry, digital optical microscopy, and scanning electron microscopy techniques to reveal the complex surface texture of the nickel alloy 625 test cubes that are produced by following an experimental design. Surface texture is further explored using image processing together with machine learning-based algorithms. Measurement uncertainty is also discussed briefly. The results reveal a complex nature of laser powder bed fusion created surface topography and textures as exposed with electropolishing that may further lead to a quantitative understanding of such textures and their formations influenced by different scanning strategies and process parameters.

Keywords

Powder bed fusion Surface topography Surface texture Nickel alloy 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

Funding

The support by the NIST under the financial assistance number 70NANB14H227 and assistances are gratefully acknowledged.

References

  1. 1.
    Amato KN, Gaytan SM, Murr LE, Martinez E, Shindo PW, Hernandez J, Collins S, Medina F (2012) Microstructures and mechanical behavior of Inconel 718 fabricated by selective laser melting. Acta Mater 60:2229–2239CrossRefGoogle Scholar
  2. 2.
    Arisoy YM, Criales LE, Özel T, Lane B, Moylan S, Donmez A (2016) Influence of scan strategy and process parameters on microstructure and its optimization in additively manufactured nickel alloy 625 via laser powder bed fusion. Int J Adv Manuf Technol.  https://doi.org/10.1007/s00170-016-9429-z
  3. 3.
    Bourell DL, Leu MC, Chakravarthy K, Guo N, Alayavalli K (2011) Graphite-based indirect laser sintered fuel cell bipolar plates containing carbon fiber additions. CIRP Ann Manuf Technol 60(1):275–278CrossRefGoogle Scholar
  4. 4.
    Brinksmeier E, Levy G, Meyer D, Spierings AB (2010) Surface integrity of selective-laser-melted components. CIRP Ann Manuf Technol 59(1):601–606CrossRefGoogle Scholar
  5. 5.
    Childs THC, Hauser C, Badrossamay M (2004) Mapping and modelling single scan track formation in direct metal selective laser melting. CIRP Ann Manuf Technol 53(1):191–194CrossRefGoogle Scholar
  6. 6.
    Criales LE, Arisoy YM, Lane B, Moylan S, Donmez A, Özel T (2017a) Predictive modeling and optimization of multi-track processing for laser powder bed fusion of nickel alloy 625. Additive Manufacturing 13:14–36CrossRefGoogle Scholar
  7. 7.
    Criales LE, Arisoy YM, Lane B, Moylan S, Donmez A, Özel T (2017b) Laser powder bed fusion of nickel alloy 625: experimental investigations of effects of process parameters on melt pool size and shape with spatter analysis. Int J Mach Tools Manuf in press Google Scholar
  8. 8.
    Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning data mining, inference, and prediction. Springer-Verlag, BerlinMATHGoogle Scholar
  9. 9.
    Kim SJ, Koh K, Boyd S, Gorinevsky D (2009) l 1 trend filtering. SIAM Rev 51(2):339–360MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Kruth J-P, Levy G, Klocke F, Childs THC (2007) Consolidation phenomena in laser and powder-bed based layered manufacturing. CIRP Ann-Manuf Technol 56(2):730–759CrossRefGoogle Scholar
  11. 11.
    NIST e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, section 5.3.3.6.2. Dec. 23, 2016
  12. 12.
    Selvin S, Ajay SG, Gowri BG, Sowmya V, Somon KP (2016) l 1 trend filter for image denoising. Proc Comput Sci 93:495–502CrossRefGoogle Scholar
  13. 13.
    Simonelli M, Tuck C, Aboulkhair NT, Maskery I, Ashcroft I, Wildman RD, Hague R (2015) A study on the laser spatter and the oxidation reactions during selective laser melting of 316L stainless steel, Al-Si10-Mg, and Ti-6Al-4V. Metall Mater Trans A 46A:3842–3851CrossRefGoogle Scholar
  14. 14.
    Taylor BN, Kuyatt CE (1994) Guidelines for evaluating and expressing the uncertainty of nist measurement results. NIST Technical Note 1297. http://www.nist.gov/pml/pubs/tn1297/ Jan. 5, 2017)
  15. 15.
    Thompson A, Senin N, Giusca C, Leach R (2017) Topography of selectively laser melted surfaces: a comparison of different measurement methods. CIRP Annals- Manufacturing. Technology 66:543–546Google Scholar
  16. 16.
    Townsend A, Senin N, Blunt L, Leach RK, Taylor JS (2016) Surface texture metrology for metal additive manufacturing: a review. Precis Manuf 46:34–47CrossRefGoogle Scholar
  17. 17.
    Yasa E, Kruth J-P, Deckers J (2011) Manufacturing by combining selective laser melting and selective laser erosion/laser re-melting. CIRP Annals- Manufacturing. Technology 60(1):263–266Google Scholar
  18. 18.
    Zaeh MF, Ott M (2011) Investigations on heat regulation of additive manufacturing processes for metal structures. CIRP Ann-Manuf Technol 60(1):259–262CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  • Tuğrul Özel
    • 1
  • Ayça Altay
    • 1
  • Alkan Donmez
    • 2
  • Richard Leach
    • 3
  1. 1.Industrial and Systems Engineering, Manufacturing and Automation Research LaboratoryRutgers UniversityPiscatawayUSA
  2. 2.National Institute of Standards and Technology, Engineering LaboratoryGaithersburgUSA
  3. 3.Manufacturing Metrology Team, Faculty of EngineeringUniversity of NottinghamNottinghamUK

Personalised recommendations