Skip to main content

Advertisement

SpringerLink
Log in

Multiresponse Optimization of Laser Cladding Steel + VC Using Grey Relational Analysis in the Taguchi Method

  • Published:
JOM Aims and scope Submit manuscript

Abstract

Laser cladding of metal matrix composite coatings (MMCs) has become an effective and economic method to improve the wear resistance of mechanical components. The clad quality characteristics such as clad height, carbide fraction, carbide dissolution, and matrix hardness in MMCs determine the wear resistance of the coatings. These clad quality characteristics are influenced greatly by the laser cladding processing parameters. In this study, American Iron and Steel Institute (AISI) 420 + 20% vanadium carbide (VC) was deposited on mild steel with a high powder direct diode laser. The Taguchi-based Grey relational method was used to optimize the laser cladding processing parameters (laser power, scanning speed, and powder feed rate) with the consideration of multiple clad characteristics related to wear resistance (clad height, carbide volume fraction, and Fe-matrix hardness). A Taguchi L9 orthogonal array was designed to study the effects of processing parameters on each response. The contribution and significance of each processing parameter on each clad characteristic were investigated by the analysis of variance (ANOVA). The Grey relational grade acquired from Grey relational analysis was used as the performance characteristic to obtain the optimal combination of processing parameters. Based on the optimal processing parameters, the phases and microstructure of the laser-cladded coating were characterized by using x-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS).

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Y. Xi, D. Liu, and D. Han, Surf. Coat. Technol. 202, 2577 (2008).

    Article  Google Scholar 

  2. C.E. Pinedo and W.A. Monteiro, Surf. Coat. Technol. 179, 119 (2004).

    Article  Google Scholar 

  3. M. Zhong and W. Liu, Proc. Inst. Mech. Eng., Part C 224, 1041 (2010).

  4. S. Liu, P. Farahmand, and R. Kovacevic, Opt. Laser Technol. 64, 363 (2014).

    Article  Google Scholar 

  5. P. Farahmand, S. Liu, Z. Zhang, and R. Kovacevic, Ceram. Int. 40, 15421 (2014).

    Article  Google Scholar 

  6. J.J. Candel, V. Amigó, J.A. Ramos, and D. Busquets, Surf. Coat. Technol. 204, 3161 (2010).

    Article  Google Scholar 

  7. H. Yan, J. Zhang, P. Zhang, Z. Yu, C. Li, P. Xu, and Y. Lu, Surf. Coat. Technol. 232, 362 (2013).

    Article  Google Scholar 

  8. N. Altinkök, JOM 66, 909 (2014).

    Article  Google Scholar 

  9. H.F. El-Labban, E.R.I. Mahmoud, and H. Al-Wadai, J. Manuf. Process. 20, 190 (2015).

    Article  Google Scholar 

  10. X.H. Wang, M. Zhang, L. Cheng, S.Y. Qu, and B.S. Du, Tribol. Lett. 34, 177 (2009).

    Article  Google Scholar 

  11. J. Nurminen, J. Näkki, and P. Vuoristo, Int. J. Refract. Met. Hard Mater. 27, 472 (2009).

    Article  Google Scholar 

  12. Q. Wu, W. Li, N. Zhong, G. Wu, and H. Wang, Mater. Des. 49, 10 (2013).

    Article  Google Scholar 

  13. X.H. Wang, L. Cheng, M. Zhang, S.Y. Qu, B.S. Du, and Z.D. Zou, Surf. Eng. 25, 211 (2009).

    Article  Google Scholar 

  14. S. Ilo, C. Just, and F. Xhiku, Mater. Des. 33, 459 (2012).

    Article  Google Scholar 

  15. Y. Dongxia, L. Xiaoyan, H. Dingyong, N. Zuoren, and H. Hui, Opt. Laser Technol. 44, 2020 (2012).

    Article  Google Scholar 

  16. A.N. Haq, P. Marimuthu, and R. Jeyapaul, Int. J. Adv. Manuf. Tech. 37, 250 (2008).

    Article  Google Scholar 

  17. J.L. Lin and C.L. Lin, Int. J. Mach. Tool. Manuf. 42, 237 (2002).

    Article  Google Scholar 

  18. Y.S. Tarng, S.C. Juang, and C.H. Chang, J. Mater. Process. Technol. 128, 1 (2002).

    Article  Google Scholar 

  19. R.S. Pawade and S.S. Joshi, Int. J. Adv. Manuf. Technol. 56, 46 (2011).

    Article  Google Scholar 

  20. X. Cao, M. Xiao, M. Jahazi, J. Fournier, and M. Alain, Mater. Manuf. Process. 23, 413 (2008).

    Article  Google Scholar 

  21. I. Smurov, M. Doubenskaia, and A. Zaitsev, Surf. Coat. Technol. 220, 112 (2013).

    Article  Google Scholar 

  22. S. Zanzarin, S. Bengtsson, and A. Molinari, J. Laser Appl. 27, S29209 (2015).

    Article  Google Scholar 

  23. L. John and J.K. Damian, Welding Metallurgy and Weldability of Stainless Steels, 1st ed. (Hoboken, NJ: Wiley, 2005), pp. 63–67.

    Google Scholar 

Download references

Acknowledgements

This work was financially support by the National Science Foundation (Grant IIP-1034652). The authors also would like to thank the research engineer, Andrew Socha, for his help in the execution of experiments.

Author information

Authors and Affiliations

  1. Lyle School of Engineering, Center for Laser-aided Manufacturing, Southern Methodist University, Dallas, TX, 75206, USA

    Zhe Zhang & Radovan Kovacevic

Authors
  1. Zhe Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Radovan Kovacevic
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Radovan Kovacevic.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Kovacevic, R. Multiresponse Optimization of Laser Cladding Steel + VC Using Grey Relational Analysis in the Taguchi Method. JOM 68, 1762–1773 (2016). https://doi.org/10.1007/s11837-016-1942-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11837-016-1942-x

Keywords

Search

Navigation