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Parametric Optimization of Microhardness of Electroless Ni-Zn-Cu-P Coating Using Taguchi Design and Artificial Neural Network

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Abstract

In this investigation, the AZ31 magnesium alloy was coated with a quaternary electroless Ni-Zn-Cu-P coating for less than 600 s, resulting in a coating thickness of 5 µm. To optimize the controllable coating parameters (nickel sulphate, zinc sulphate, and sodium hypophosphite), the Taguchi L27 orthogonal array was employed to maximize the microhardness of the coatings. By using these coating parameters as inputs and the microhardness of the coatings as an output, the applicability of an artificial neural network (ANN) was examined. To predict the microhardness of the coatings, ANNs with feed-forward back-propagation neural networks were trained using the Levenberg–Marquardt algorithm with 1 neuron for the first ANN, 2 neurons for the second, and so on up to ten ANN. The network with seven neurons in the hidden layer (ANN 3-7-1) shows the maximum correlation coefficient (R2), indicating that ANN 3-7-1 accurately predicts microhardness. For ANN 3-7-1, the root mean squared error and R2 were 8.8475 and 0.982, respectively. The surface morphology, composition, and crystallinity of the coatings were investigated and determined by field emission scanning electron microscopy, energy dispersive x-ray spectroscopy, and x-ray diffraction analysis.

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References

  1. F. Goodwin, S. Guruswamy, K.U. Kainer, C. Kammer, W. Knabl, A. Koethe, G. Leichtfried, G. Schlamp, and R. Stickler, H. Warlimont, in Springer Handbook of Condensed Matter and Materials Data. ed. by W. Martienssen, and H. Warlimont (Springer, Berlin, 2005), pp. 161–430.

    Google Scholar 

  2. M.A. Taha, N.A. El-Mahallawy, R.M. Hammouda, and S.I. Nassef, J. Coatings Technol. Res. 7, 793. (2010).

    Google Scholar 

  3. Z.-M. Qiu, F. Zhang, J.-T. Chu, Y.-C. Li, and L. Song, Front. Mater. Sci. 14, 96. (2020).

    Google Scholar 

  4. B. Qingyou, Y. Yu, H. Liu, S. Bi, L. Cao, Q. Bai, and X. Teng, Int. J. Electrochem. Sci. 7, 8337. (2012).

    Google Scholar 

  5. M. Heshmati, D. Seifzadeh, P. Shoghi, and M. Gholizadeh-Gheshlaghi, Surf. Coatings Technol. 328, 20. (2017).

    Google Scholar 

  6. P. Zhou, W. Cai, Y. Yang, X. Li, T. Zhang, and F. Wang, Surf. Coatings Technol. 374, 103. (2019).

    Google Scholar 

  7. J. Liu, X. Wang, Z. Tian, M. Yuan, and X. Ma, Appl. Surf. Sci. 356, 289. (2015).

    Google Scholar 

  8. G. O. Mallory, J. B. Hajdu, American Electroplaters and Surface Finishers Society, in Electroless Plating: Fundamentals and Applications (American Electroplaters and Surface Finishers Society, Orlando, 1990).

  9. J. Sudagar, J. Lian, and W. Sha, J. Alloys Compd. 571, 183. (2013).

    Google Scholar 

  10. W. Riedel, Electroless Nickel Plating (Publisher: ASM International; Finishing Publications, Metals Park, Ohio, Stevenage, England, 1991).

    Google Scholar 

  11. H. Larhzil, M. Cissé, R. Touir, M.E. Touhami, and M. Cherkaoui, Electrochim. Acta 53, 622. (2007).

    Google Scholar 

  12. W.L. Liu, S.H. Hsieh, W.J. Chen, and Y.C. Hsu, Appl. Surf. Sci. 255, 3880. (2009).

    Google Scholar 

  13. M. Oulladj, and D. Saidi, J Mater Sci. 34, 2437. (1999).

    Google Scholar 

  14. R. Wang, W. Ye, C. Ma, and C. Wang, Mater. Charact. 59, 108. (2008).

    Google Scholar 

  15. V. Kumar, B.B. Mandal, and B. Oraon, Mater. Today Proc. 59, 1183. (2022).

    Google Scholar 

  16. J.N. Balaraju, V.E. Selvi, V.K.W. Grips, and K.S. Rajam, Electrochim. Acta. 52, 1064. (2006).

    Google Scholar 

  17. P. Gadhari, and P. Sahoo, Procedia Mater. Sci. 6, 623. (2014).

    Google Scholar 

  18. S. Kundu, K. Das, and P. Sahoo, Mater. Today Proc. 5, 8547. (2018).

    Google Scholar 

  19. S. Sarkar, A. Mukherjee, R.K. Baranwal, J. De, C. Biswas, and G. Majumdar, J. Mech. Behav. Mater. 28, 153. (2019).

    Google Scholar 

  20. S. Sarkar, R.K. Baranwal, A. Mukherjee, I. Koley, C. Biswas, J. Haider, and G. Majumdar, Adv. Mater. Process. Technol. 6, 487. (2020).

    Google Scholar 

  21. I.A. Shozib, A. Ahmad, M.S.A. Rahaman, A.M. Abdul-Rani, M.A. Alam, M. Beheshti, and I. Taufiqurrahman, J. Mater. Res. Technol. 12, 1010. (2021).

    Google Scholar 

  22. ŞT. Güner, M.J. Diamantopoulou, K.P. Poudel, A. Çömez, and R. Özçelik, Comput. Electron. Agric. 192, 106596. (2022).

    Google Scholar 

  23. M. Zaimi and K. Noda, ECS Trans. 45, 3. (2013).

    Google Scholar 

  24. M. Ali Ahmadi, S. Zendehboudi, A. Lohi, A. Elkamel, and I. Chatzis, Geophys. Prospect. 61, 582. (2013).

    Google Scholar 

  25. M.A. Ahmadi, M.R. Ahmadi, S.M. Hosseini, and M. Ebadi, J. Pet. Sci. Eng. 123, 183. (2014).

    Google Scholar 

  26. M.A. Ahmadi and Z. Chen, Petroleum. 5, 271. (2019).

    Google Scholar 

  27. M.A. Ahmadi, A. Bahadori, and S.R. Shadizadeh, Fuel 139, 154. (2015).

    Google Scholar 

  28. M.A. Ahmadi, Math. Probl. Eng. 2015, 706897. (2015).

    Google Scholar 

  29. M.A. Ahmadi, R. Soleimani, M. Lee, T. Kashiwao, and A. Bahadori, Petroleum 1, 118. (2015).

    Google Scholar 

  30. S.R. Moosavi, D.A. Wood, M.A. Ahmadi, and A. Choubineh, Nat. Resour. Res. 28, 1619. (2019).

    Google Scholar 

  31. M. Ahmadi, and Z. Chen, J. Pet. Explor. Prod. Technol. 10, 2873. (2020).

    Google Scholar 

  32. M.H. Ahmadi, M. Alhuyi Nazari, R. Ghasempour, H. Madah, M.B. Shafii, and M.A. Ahmadi, Colloids Surfaces A Physicochem. Eng. Asp. 541, 154. (2018).

    Google Scholar 

  33. M. Ramezanizadeh, M.A. Ahmadi, M.H. Ahmadi, and M. Alhuyi Nazari, J. Therm. Anal. Calorim. 137, 307. (2019).

    Google Scholar 

  34. L.T. Le, H. Nguyen, J. Dou, and J. Zhou, Appl. Sci. 9, 2630. (2019).

    Google Scholar 

  35. J.F. Mas, and J.J. Flores, Int. J. Remote Sens. 29, 617. (2008).

    Google Scholar 

  36. G. Goudarzi, P.K. Hopke, and M. Yazdani, Chemosphere 283, 131285. (2021).

    Google Scholar 

  37. J. Garza-Ulloa, in Applied Biomechatronics Using Mathematical Models (Elsevier, 2018), pp. 373–524.

  38. W. Yating, S. Bin, L. Lei, and H. Wenbin, J. Mater. Process. Technol. 205, 207. (2008).

    Google Scholar 

  39. X.F. Zou, Y.J. Hu, X.B. Long, and L.Y. Huang, Surfaces Interfaces 18, 100443. (2020).

    Google Scholar 

  40. S.Y.M. Vaghefi, and S.M.M. Vaghefi, Neural Comput. Appl. 20, 1055. (2011).

    Google Scholar 

  41. H. Beygi, H. Vafaeenezhad, and S.A. Sajjadi, Appl. Surf. Sci. 258, 7744. (2012).

    Google Scholar 

  42. M. Vijayanand, R. Varahamoorthi, and P. Kumaradhas, Mater. Today Proc. 49, 2239. (2022).

    Google Scholar 

  43. T.H. Priyanto, A. Insani, and R. Muslih, and Bharoto. J. Phys. Conf. Ser. 1436, 012061. (2020).

    Google Scholar 

  44. C. Gu, J. Lian, G. Li, L. Niu, and Z. Jiang, J. Alloys Compd. 391, 104. (2005).

    Google Scholar 

  45. K.G. Keong, W. Sha, and S. Malinov, J. Alloys Compd 334, 192. (2002).

    Google Scholar 

  46. I. Baskaran, T.S.N.S. Narayanan, and A. Stephen, Mater. Chem. Phys. 99, 117. (2006).

    Google Scholar 

  47. M. Cissé, M. Abouchane, T. Anik, K. Himm, R.A. Belakhmima, M. Ebn Touhami, R. Touir, and A. Amiar, Int. J. Corros. 2010, 246908. (2010).

    Google Scholar 

  48. M. Cherkaoui, A. Srhiri, and E. Chassaing, Plating Surf. Finish. 79, 68. (1992).

    Google Scholar 

  49. B. Oraon, G. Majumdar, and B. Ghosh, Mater. Des. 29, 1412. (2008).

    Google Scholar 

  50. M. Yan, H.G. Ying, and T.Y. Ma, Surf. Coatings Technol. 202, 5909. (2008).

    Google Scholar 

  51. B. Chandra Kandpal, J. Kumar, and H. Singh, Mater. Today Proc. 5, 18946. (2018).

    Google Scholar 

  52. L. Zhang, L. Sun, J.G. Han, and Y.H. Guo, J. Mater. Sci. Mater. Electron. 26, 2605. (2015).

    Google Scholar 

  53. D.C. Montgomery, Design and Analysis of Experiments (Wiley, Hoboken, NJ, 2017).

    Google Scholar 

  54. K. Ramesh, P. Baranitharan, and R. Sakthivel, Meas. J. Int. Meas. Confed. 131, 143. (2019).

    Google Scholar 

  55. A.M. Al-Swaidani and W.T. Khwies, Adv. Civ. Eng. 2018, 5207962. (2018).

    Google Scholar 

Download references

Acknowledgements

The first author acknowledges AICTE (All India Council for Technical Education) for providing financial support for doing Ph.D. work under the AICTE-NDF (National Doctoral Fellowship) scheme at Jadavpur University.

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  1. Department of Mechanical Engineering, Jadavpur University, Kolkata, 700032, India

    Chandra Sekhar Rauta, Gautam Majumdar & Sandip Sarkar

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  1. Chandra Sekhar Rauta
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Rauta, C.S., Majumdar, G. & Sarkar, S. Parametric Optimization of Microhardness of Electroless Ni-Zn-Cu-P Coating Using Taguchi Design and Artificial Neural Network. JOM 74, 4564–4574 (2022). https://doi.org/10.1007/s11837-022-05489-5

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