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Phenomenological modelling of direct laser metal deposition for single tracks

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Abstract

The direct laser metal deposition (DLMD) is an emerging technology in the additive manufacturing field, which is becoming widely adopted in several industrial applications. The optimal selection of process parameters is critical, given the cost of physical tests and the requirement for high-quality manufacturing. Correct forecasting of process parameters using predictive physical models is a viable alternative to shorten the setup phase and improve the sustainability. In this paper, firstly, several models available so far in the literature are reviewed, and then, a general model is derived to evaluate the best combination of process parameters in single track operations. The proposed phenomenological model allows simple forecasting based on three main process parameters: laser power (P), powder feed rate (F) and translation speed (V). An innovative approach is proposed to generalise the model and overcome the “try and error” method used in numerous works to determine the exponents (α, β, γ). The model was designed considering the physical parameters which best explained the variability of the exponents: the thermal diffusivity of the base material and the density of the powder material. The best ranges of the process parameter exponents are suggested to establish the most suitable combined parameters for the prediction of geometric characteristics of the clad. The potentialities of the model are proven based on an experimental case performed over a commercially available Nickel-based super-alloy powder. New formulations are recommended, which are in good agreement with the behaviours defined in the literature, as shown in the test case.

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Abbreviations

P:

Laser power

V:

Translation speed

F:

Powder feed rate

W:

Clad width

H:

Clad height

p:

Clad penetration depth

A c :

Clad area

A m :

Substrate molten area

Dil:

Dilution

Dt:

Thermal diffusivity

α:

Absorbance of powder

η d :

Laser power dependent deposition efficiency

η i :

Laser power independent deposition efficiency

η melt :

Substrate melting efficiency

ρ (p) :

Powder density

ρ (s) :

Substrate density

C (p) :

Specific heat of powder

T (p) :

Melting temperature of powder

L f(p) :

Latent heat of fusion of powder

C (s) :

Specific heat of substrate

T (s) :

Melting temperature of substrate

L f(s) :

Latent heat of fusion of substrate

References

  1. Tay S, Te Chuan L, Aziati A, Ahmad ANA (2018) An overview of industry 4.0: definition, components, and government initiatives. J Adv Res Dyn Control Syst 10:14

    Google Scholar 

  2. Dilberoglu UM, Gharehpapagh B, Yaman U, Dolen M (2017) The role of additive manufacturing in the era of Industry 4.0. Proc Manuf 11:545–554. https://doi.org/10.1016/j.promfg.2017.07.148

    Article  Google Scholar 

  3. Horst D, Duvoisin C, Vieira R (2018) Additive manufacturing at Industry 4.0: a review. Int J Eng Tech Res 8:3–8

    Google Scholar 

  4. Despeisse M, Ford S (2015) The role of additive manufacturing in improving resource efficiency and sustainability. In: Umeda S, Nakano M, Mizuyama H et al (eds) Advances in production management systems: innovative production management towards sustainable growth. Springer International Publishing, Cham, pp 129–136

    Google Scholar 

  5. Siva Prasad H, Brueckner F, Volpp J, Kaplan AFH (2020) Laser metal deposition of copper on diverse metals using green laser sources. Int J Adv Manuf Technol 107:1559–1568. https://doi.org/10.1007/s00170-020-05117-z

    Article  Google Scholar 

  6. Errico V, Campanelli SL, Angelastro A, Mazzarisi M, Casalino G (2020) On the feasibility of AISI 304 stainless steel laser welding with metal powder. J Manuf Process 56:96–105. https://doi.org/10.1016/j.jmapro.2020.04.065

    Article  Google Scholar 

  7. Srivastava D, Chang ITH, Loretto MH (2000) The optimisation of processing parameters and characterisation of microstructure of direct laser fabricated TiAl alloy components. Mater Des 21:425–433. https://doi.org/10.1016/S0261-3069(99)00091-6

    Article  Google Scholar 

  8. Yang LX, Peng XF, Wang BX (2001) Numerical modeling and experimental investigation on the characteristics of molten pool during laser processing. Int J Heat Mass Transf 44:4465–4473. https://doi.org/10.1016/S0017-9310(01)00086-2

    Article  MATH  Google Scholar 

  9. Guan X, Zhao YF (2020) Modeling of the laser powder–based directed energy deposition process for additive manufacturing: a review. Int J Adv Manuf Technol 107:1959–1982. https://doi.org/10.1007/s00170-020-05027-0

    Article  Google Scholar 

  10. Zhang Z, Ge P, Yao XX, Li T, Liu WW (2020) Numerical studies of residual states and scaling effects in laser-directed energy deposition additive manufacturing. Int J Adv Manuf Technol 108:1233–1247. https://doi.org/10.1007/s00170-020-05300-2

    Article  Google Scholar 

  11. Han L, Phatak KM, Liou FW (2004) Modeling of laser cladding with powder injection. Metall Mater Trans B Process Metall Mater Process Sci 35:1139–1150. https://doi.org/10.1007/s11663-004-0070-0

    Article  Google Scholar 

  12. Kumar A, Roy S (2009) Development of a theoretical process map for laser cladding using a three-dimensional conduction heat transfer model. Numer Heat Transf Part Appl 56:478–496. https://doi.org/10.1080/10407780903266489

    Article  Google Scholar 

  13. Wen S, Shin YC (2010) Modeling of transport phenomena during the coaxial laser direct deposition process. J Appl Phys 108:044908. https://doi.org/10.1063/1.3474655

    Article  Google Scholar 

  14. Pinkerton AJ, Li L (2004) Modelling the geometry of a moving laser melt pool and deposition track via energy and mass balances. J Phys Appl Phys 37:1885–1895. https://doi.org/10.1088/0022-3727/37/14/003

    Article  Google Scholar 

  15. Xi W, Song B, Zhao Y, Yu T, Wang J (2019) Geometry and dilution rate analysis and prediction of laser cladding. Int J Adv Manuf Technol 103:4695–4702. https://doi.org/10.1007/s00170-019-03932-7

    Article  Google Scholar 

  16. Zhu S, Chen W, Ding L, Zhan X, Chen Q (2019) A mathematical model of laser cladding repair. Int J Adv Manuf Technol 103:3265–3278. https://doi.org/10.1007/s00170-019-03588-3

    Article  Google Scholar 

  17. Reddy L, Preston SP, Shipway PH, Davis C, Hussain T (2018) Process parameter optimisation of laser clad iron based alloy: predictive models of deposition efficiency, porosity and dilution. Surf Coat Technol 349:198–207. https://doi.org/10.1016/j.surfcoat.2018.05.054

    Article  Google Scholar 

  18. Alekseev AV, Turichin GA, Klimova-Korsmik OG, Valdaytseva EA, Rashkovets MV, Nikulina AA (2020) Simulation of the Ni3Al intermetallic inclusion growth process during direct laser deposition using Ni-based superalloy powder. Mater Today Proc 30:756–760. https://doi.org/10.1016/j.matpr.2020.01.562

    Article  Google Scholar 

  19. Costa L, Felde I, Réti T, Kálazi Z, Colaço R, Vilar R, Verő B (2003) A simplified semi-empirical method to select the processing parameters for laser clad coatings. Mater Sci Forum 414–415:385–394. https://doi.org/10.4028/www.scientific.net/MSF.414-415.385

    Article  Google Scholar 

  20. de Oliveira U, Ocelík V, De Hosson JTM (2005) Analysis of coaxial laser cladding processing conditions. Surf Coat Technol 197:127–136. https://doi.org/10.1016/j.surfcoat.2004.06.029

    Article  Google Scholar 

  21. Ocelík V, de Oliveira U, de Boer M, de Hosson JTM (2007) Thick Co-based coating on cast iron by side laser cladding: analysis of processing conditions and coating properties. Surf Coat Technol 201:5875–5883. https://doi.org/10.1016/j.surfcoat.2006.10.044

    Article  Google Scholar 

  22. El Cheikh H, Courant B, Hascoët J-Y, Guillén R (2012) Prediction and analytical description of the single laser track geometry in direct laser fabrication from process parameters and energy balance reasoning. J Mater Process Technol 212:1832–1839. https://doi.org/10.1016/j.jmatprotec.2012.03.016

    Article  Google Scholar 

  23. Nenadl O, Kuipers W, Koelewijn N, Ocelík V, de Hosson JTM (2016) A versatile model for the prediction of complex geometry in 3D direct laser deposition. Surf Coat Technol 307:292–300. https://doi.org/10.1016/j.surfcoat.2016.08.090

    Article  Google Scholar 

  24. Barekat M, Shoja Razavi R, Ghasemi A (2016) Nd:YAG laser cladding of Co–Cr–Mo alloy on γ-TiAl substrate. Opt Laser Technol 80:145–152. https://doi.org/10.1016/j.optlastec.2016.01.003

    Article  Google Scholar 

  25. Ansari M, Shoja Razavi R, Barekat M (2016) An empirical-statistical model for coaxial laser cladding of NiCrAlY powder on Inconel 738 superalloy. Opt Laser Technol 86:136–144. https://doi.org/10.1016/j.optlastec.2016.06.014

    Article  Google Scholar 

  26. Erfanmanesh M, Abdollah-Pour H, Mohammadian-Semnani H, Shoja-Razavi R (2017) An empirical-statistical model for laser cladding of WC-12Co powder on AISI 321 stainless steel. Opt Laser Technol 97:180–186. https://doi.org/10.1016/j.optlastec.2017.06.026

    Article  Google Scholar 

  27. Nabhani M, Razavi RS, Barekat M (2018) An empirical-statistical model for laser cladding of Ti-6Al-4V powder on Ti-6Al-4V substrate. Opt Laser Technol 100:265–271. https://doi.org/10.1016/j.optlastec.2017.10.015

    Article  Google Scholar 

  28. Bax B, Rajput R, Kellet R, Reisacher M (2018) Systematic evaluation of process parameter maps for laser cladding and directed energy deposition. Addit Manuf 21:487–494. https://doi.org/10.1016/j.addma.2018.04.002

    Article  Google Scholar 

  29. El Cheikh H, Courant B, Branchu S et al (2012) Analysis and prediction of single laser tracks geometrical characteristics in coaxial laser cladding process. Opt Lasers Eng 50:413–422. https://doi.org/10.1016/j.optlaseng.2011.10.014

    Article  Google Scholar 

  30. Riquelme A, Escalera-Rodriguez MD, Rodrigo P, Rams J (2016) Role of laser cladding parameters in composite coating (Al-SiC) on aluminum alloy. J Therm Spray Technol 25:1177–1191. https://doi.org/10.1007/s11666-016-0431-7

    Article  Google Scholar 

  31. Caiazzo F, Alfieri V, Argenio P, Sergi V (2017) Additive manufacturing by means of laser-aided directed metal deposition of 2024 aluminium powder: investigation and optimization. Adv Mech Eng 9:168781401771498. https://doi.org/10.1177/1687814017714982

    Article  Google Scholar 

  32. Chen Y, Wang X, Zhao Y, Song B, Yu T (2020) Interactive optimization of process parameters and coating analysis of laser cladding JG-3 powder. Int J Adv Manuf Technol 107:2623–2633. https://doi.org/10.1007/s00170-020-05155-7

    Article  Google Scholar 

  33. Peng L, Taiping Y, Sheng L, Dongsheng L, Qianwu H, Weihao X, Xiaoyan Z (2005) Direct laser fabrication of nickel alloy samples. Int J Mach Tools Manuf 45:1288–1294. https://doi.org/10.1016/j.ijmachtools.2005.01.014

    Article  Google Scholar 

  34. Aggarwal K, Urbanic RJ, Saqib SM (2018) Development of predictive models for effective process parameter selection for single and overlapping laser clad bead geometry. Rapid Prototyp J 24:214–228. https://doi.org/10.1108/RPJ-04-2016-0059

    Article  Google Scholar 

  35. Saqib S, Urbanic RJ, Aggarwal K (2014) Analysis of laser cladding bead morphology for developing additive manufacturing travel paths. Proc CIRP 17:824–829. https://doi.org/10.1016/j.procir.2014.01.098

    Article  Google Scholar 

  36. Yu T, Yang L, Zhao Y, Sun J, Li B (2018) Experimental research and multi-response multi-parameter optimization of laser cladding Fe313. Opt Laser Technol 108:321–332. https://doi.org/10.1016/j.optlastec.2018.06.030

    Article  Google Scholar 

  37. Sun Y, Hao M (2012) Statistical analysis and optimization of process parameters in Ti6Al4V laser cladding using Nd:YAG laser. Opt Lasers Eng 50:985–995. https://doi.org/10.1016/j.optlaseng.2012.01.018

    Article  Google Scholar 

  38. Shi Y, Li Y, Liu J, Yuan Z (2018) Investigation on the parameter optimization and performance of laser cladding a gradient composite coating by a mixed powder of Co50 and Ni/WC on 20CrMnTi low carbon alloy steel. Opt Laser Technol 99:256–270. https://doi.org/10.1016/j.optlastec.2017.09.010

    Article  Google Scholar 

  39. Verdi D, Múnez CJ, Garrido MA, Poza P (2017) Process parameter selection for Inconel 625-Cr3C2 laser cladded coatings. Int J Adv Manuf Technol 92:3033–3042. https://doi.org/10.1007/s00170-017-0372-4

    Article  Google Scholar 

  40. Caiazzo F (2018) Laser-aided directed metal deposition of Ni-based superalloy powder. Opt Laser Technol 103:193–198. https://doi.org/10.1016/j.optlastec.2018.01.042

    Article  Google Scholar 

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Correspondence to Marco Mazzarisi.

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Mazzarisi, M., Campanelli, S.L., Angelastro, A. et al. Phenomenological modelling of direct laser metal deposition for single tracks. Int J Adv Manuf Technol 111, 1955–1970 (2020). https://doi.org/10.1007/s00170-020-06204-x

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