Skip to main content
Log in

Determining the Optimum Process Parameters of Selective Laser Melting via Particle Swarm Optimization Based on the Response Surface Method

  • Published:
Metals and Materials International Aims and scope Submit manuscript


Manufacturing high-quality and desired products from additive manufacturing necessitate careful adjustment of the process parameters. Various methods can be utilised to determine optimum process parameters, such as the Taguchi method, Design of Experiments (DoE). Rather than evaluating limited information obtained from statistical analysis of the experiments, optimisation methods can help find the best possible combination for the process parameters. Therefore, an optimisation approach based on Particle Swarm Optimization (PSO) was utilised to find the optimum process parameters. The most important process parameters of Selective Laser Melting (SLM) such as laser power, layer thickness, scan speed, and build orientation were selected as input parameters, and their effects on the tensile properties of the manufactured part were investigated to find out the optimal operating conditions for the SLM process. Since there is not any explicit mathematical expression relating these process parameters to the tensile strength, the Response Surface Method (RSM) was used to obtain a meta-model so that it can be used as an objective function in the optimisation formulation. This approach enabled us to predict the optimum process parameters to maximise the tensile strength without conducting an excessive number of experiments. Moreover, the mathematical model can also predict tensile strength corresponding to the parameter values that are not tested according to the DoE chosen for such studies. Furthermore, it was also shown that the PSO outperforms the Genetic Algorithm (GA), which is widely employed to find out the optimum process parameters, in terms of less number of iteration.

Graphical Abstract

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others


  1. J. Ni, F. Liu, G. Yang, G.-H. Lee, S.-M. Chung, I.-S. Lee, C. Chen, J. Mater. Res. Technol. 14, 2322 (2021)

    Article  CAS  Google Scholar 

  2. H.M. Hamza, K.M. Deen, W. Haider, Mater. Sci. Eng. C 113, 110980 (2020)

    Article  CAS  Google Scholar 

  3. B. Song, S. Dong, H. Liao, C. Coddet, Int. J. Adv. Manuf. Technol. 61, 967 (2012)

    Article  Google Scholar 

  4. A.B. Baldissera, P. Pavez, P.A.P. Wendhausen, C.H. Ahrens, J.M. Mascheroni, IEEE Trans. Magn. 53, 1 (2017)

    Article  Google Scholar 

  5. R. Rashid, S.H. Masood, D. Ruan, S. Palanisamy, R.A.R. Rashid, J. Elambasseril, Addit. Manuf. 22, 426–439 (2018)

    CAS  Google Scholar 

  6. R. Olaf, E. Claus, Wissenschaftliche Gesellschaft fur Lasertechnik. Lasertechnik 3, 227–232 (2005)

    Google Scholar 

  7. H. Gong, K. Rafi, H. Gu, T. Starr, B. Stucker, Addit. Manuf. 1–4, 87 (2014)

    Google Scholar 

  8. A.M. Aboutaleb, M.J. Mahtabi, M.A. Tschopp, L. Bian, J. Manuf. Proc. 38, 432 (2019)

    Article  Google Scholar 

  9. M. Simonelli, Y.Y. Tse, C. Tuck, Mater. Sci. Eng. A 616, 1 (2014)

    Article  CAS  Google Scholar 

  10. J.M. Chacón, M.A. Caminero, E. García-Plaza, P.J. Núñez, Mater. Design 124, 143 (2017)

    Article  Google Scholar 

  11. J. Li, J. Hu, L. Cao, S. Wang, H. Liu, Q. Zhou, J. Manuf. Proc. 68, 198 (2021)

    Article  Google Scholar 

  12. J. Han, J. Yang, H. Yu, J. Yin, M. Gao, Z. Wang, X. Zeng, Rapid Prototyp. J. 23, 217 (2017)

    Article  Google Scholar 

  13. A. Pawlak, P.E. Szymczyk, T. Kurzynowski, E. Chlebus, Rapid Prototyp. J. 26, 249 (2019)

    Article  Google Scholar 

  14. Z. Li, I. Kucukkoc, D.Z. Zhang, F. Liu, RPJ 24, 150 (2018)

    Article  Google Scholar 

  15. F. Ma, H. Zhang, K.K.B. Hon, Q. Gong, J. Clean. Prod. 199, 529 (2018)

    Article  Google Scholar 

  16. Y.M. Arısoy, L.E. Criales, T. Özel, B. Lane, S. Moylan, A. Donmez, Int. J. Adv. Manuf. Technol. 90, 1393 (2017)

    Article  Google Scholar 

  17. D.S. Nguyen, H.S. Park, C.M. Lee, J. Manuf. Proc. 55, 230 (2020)

    Article  Google Scholar 

  18. F.D. Wihartiko, H. Wijayanti, F. Virgantari, IOP Conf. Ser. Mater. Sci. Eng. 332, 12020 (2018)

  19. S.M. Almufti, A.Y. Zebari, H.K. Omer, J. Adv. Comput. Sci. Technol. 8, 40 (2019)

    Article  Google Scholar 

  20. J. Qin, Y. Liu, R. Grosvenor, F. Lacan, Z. Jiang, J. Clean. Prod. 245, 118702 (2020)

    Article  Google Scholar 

  21. S. Negi, S. Dhiman, R.K. Sharma, Arab. J. Sci. Eng. 39, 9161 (2014)

    Article  CAS  Google Scholar 

  22. N. Read, W. Wang, K. Essa, M.M. Attallah, Mater. Design 65, 417 (2015)

    Article  CAS  Google Scholar 

  23. D.C. Montgomery, Design and Analysis of Experiments, 6th Edn. (John Wiley & Sons, New York, 2007)

  24. ASTM E8/E8M-13a, Standard test methods for tension testing of metallic materials (ASTM International, West Conshohocken, 2013)

  25. M.X. Gan, C.H. Wong, J. Mater. Proces. Technol. 238, 474 (2016)

    Article  Google Scholar 

  26. Z. Ye, J. Zhu, Q. Li, B. Mo, B. Lei, Y. Li, C. Wang, C. Huang, Micro Reliab. 88–90, 1151 (2018)

    Article  Google Scholar 

  27. D. Wang, D. Tan, L. Liu, Soft. Comput. 22, 387 (2018)

    Article  Google Scholar 

  28. K. Kalita, I. Shivakoti, R.K. Ghadai, Mater. Manuf. Process. 32, 1101 (2017)

    Article  CAS  Google Scholar 

  29. A.T. Şensoy, I. Kaymaz, Ü. Ertaş, Swarm Evol. Comput. 53, 100645 (2020)

    Article  Google Scholar 

  30. P.-H. Li, W.-G. Guo, W.-D. Huang, Y. Su, X. Lin, K.-B. Yuan, Mater. Sci. Eng. A 647, 34 (2015)

    Article  CAS  Google Scholar 

  31. M. Tang, L. Zhang, N. Zhang, Mater. Sci. Eng. A 814, 141187 (2021)

    Article  CAS  Google Scholar 

  32. J. Sun, Y. Yang, D. Wang, Opt. Laser Technol. 49, 118 (2013)

    Article  CAS  Google Scholar 

  33. B. Yang, Y. Lai, X. Yue, D. Wang, Y. Zhao, Scanning 2020, 9176509 (2020)

  34. B. Fotovvati, M. Balasubramanian, E. Asadi, Coatings 10, 1104 (2020)

    Article  CAS  Google Scholar 

  35. G. Kasperovich, J. Haubrich, J. Gussone, G. Requena, Mater. Design 105, 160 (2016)

    Article  CAS  Google Scholar 

  36. A.K. Singla, M. Banerjee, A. Sharma, J. Singh, A. Bansal, M.K. Gupta, N. Khanna, A.S. Shahi, D.K. Goyal, J. Manuf. Process. 64, 161 (2021)

    Article  Google Scholar 

  37. A. Charles, A. Elkaseer, L. Thijs, S.G. Scholz, Appl. Sci. 10, 7 (2020)

    Article  Google Scholar 

  38. T. Vilaro, C. Colin, J.D. Bartout, Metall. Mater. Trans. A 42, 3190 (2011)

    Article  CAS  Google Scholar 

  39. J.T. Oliveira de Menezes, E.M. Castrodeza, R. Casati, Mater. Sci. Eng. A 766, 138392 (2019)

    Article  CAS  Google Scholar 

  40. Q. Jiang, S. Li, C. Zhou, B. Zhang, Y. Zhang, Opt. Laser Technol. 144, 107391 (2021)

    Article  CAS  Google Scholar 

  41. A.H. Maamoun, Y.F. Xue, M.A. Elbestawi, S.C. Veldhuis, Materials 12, 12 (2019)

    Article  CAS  Google Scholar 

  42. S. Pal, N. Gubeljak, R. Hudak, G. Lojen, V. Rajtukova, J. Predan, V. Kokol, I. Drstvensek, Mater. Sci. Eng. A 743, 637 (2019)

    Article  CAS  Google Scholar 

  43. C. Qiu, C. Panwisawas, M. Ward, H.C. Basoalto, J.W. Brooks, M.M. Attallah, Acta Mater. 96, 72 (2015)

    Article  CAS  Google Scholar 

  44. L. van Belle, J.-C. Boyer, G. Vansteenkiste, Key Eng. Mater. 554-557, 1828 (2013)

  45. S. Leuders, M. Thöne, A. Riemer, T. Niendorf, T. Tröster, H.A. Richard, H.J. Maier, Int. J. Fatigue 48, 300 (2013)

    Article  CAS  Google Scholar 

Download references


This study is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under the project code 218M425. We would like to thank TÜBİTAK for their contributions.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Fahri Murat.

Ethics declarations

Conflict of interest

The authors declared no potential conficts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Murat, F., Kaymaz, İ., Şensoy, A.T. et al. Determining the Optimum Process Parameters of Selective Laser Melting via Particle Swarm Optimization Based on the Response Surface Method. Met. Mater. Int. 29, 59–70 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: