Fuzzy Logic Modeling for Higher Adhesion Strength of Cr/Cr-N Multilayer Thin Film Coating on Aerospace AL7075-T6 Alloy for Higher Fretting Fatigue Life

  • Erfan Zalnezhad
  • Ahmed Aly Diaa Mohammed Sarhan
Conference paper


Adhesion strength of coating is one of the most imperative factors in magnetron sputtering technique. Therefore; exploring the effect of coating parameters on enhancing adhesion strength of coating to substrate is extremely important. In this study, an experimental assessment was carried out to discover the fretting fatigue life of Cr/CrN coated AL7075-T6 alloy with higher adhesion strength to substrate by application of PVD magnetron sputtering technique. A fuzzy logic method was utilized to examine how to achieve higher adhesion of coating regarding to changes in input process parameters including DC power, nitrogen flow rate and temperature for fretting fatigue life Improvement.


Adhesion AL7075-T6 Cr-CrN coating Fretting fatigue Fuzzy logic Magnetron sputters technique 



This research was funded by the UMRG grant with number: RP021C-13AET from the University of Malaya, Malaysia.


  1. 1.
    K. Genel, The effect of pitting on the bending fatigue performance of high-strength aluminum alloy. Scripta Mater. 57, 297–300 (2007)CrossRefGoogle Scholar
  2. 2.
    P.S. Pao, S.J. Gill, C.R. Feng, On fatigue crack initiation from corrosion pits in 7075-T7351 aluminum alloy. Scripta Mater. 43, 391–396 (2000)CrossRefGoogle Scholar
  3. 3.
    H. Lee, S. Mall, Fretting behavior of shot peened Ti-6Al-4 V under slip controlled mode. Wear 260, 642–651 (2006)CrossRefGoogle Scholar
  4. 4.
    G.H. Majzoobi, J. Nemati, A.J. NovinRooz, G.H. Farrahi, Modification of fretting fatigue behavior of AL7075-T6 alloy by the application of titanium coating using IBED technique and shot peening. Tribol. Int. 42, 121–129 (2009)CrossRefGoogle Scholar
  5. 5.
    E. Zalnezhad, A.D.A. Sarhan, M. Hamdi, Investigating the fretting fatigue life of thin film titanium nitride coated aerospace Al7075-T6 alloy, 559, 436–446 (2013)Google Scholar
  6. 6.
    L.C. Lietch, H. Lee, S. Mall, Fretting fatigue behavior of Ti-6Al-4 V, under seawater environment. Mater. Sci. Eng., A 403, 281–289 (2005)CrossRefGoogle Scholar
  7. 7.
    G.H. Majzoobi, M. Jaleh, Duplex surface treatments on AL7075-T6 alloy against fretting fatigue behavior by application of titanium coating plus nitriding. Mater. Sci. Eng. A 452453, 673–681 (2007)Google Scholar
  8. 8.
    S. Ortmann, A. Savan, Y. Gerbig, H. Haefke, In-process structuring of CrN coatings and its influence on friction in dry and lubricated sliding. Wear 254, 1099–1105 (2003)CrossRefGoogle Scholar
  9. 9.
    B. Sresomroeng, V. Premanond, P. Kaewtatip, A. Khantachawana, A. Kurosawa, N. Koga, Performance of CrN radical nitrided tools on deep drawing of advanced high strength steel. Surf. Coat. Technol. 205, 4198–4204 (2011)Google Scholar
  10. 10.
    R. Rebole, A. Martinez, R. Rodriguez, G.G. Fuentes, E. Spain, N. Watson, J.C.A. Batista, J. Housden, F. Montala, L.J. Carreras, T.J. Tate, Microstructural and tribological investigations of CrN coated, wet-stripped and recoated functional substrates used for cutting and forming tools. Thin Solid Films 469–470, 466–471 (2004)CrossRefGoogle Scholar
  11. 11.
    G. Bertrand, H. Mahdjoub, C.A. Meunier, Study of the corrosion behavior and protective quality of sputtered chromium nitride coatings. Surf. Coat. Technol. 126, 199–209 (2000)CrossRefGoogle Scholar
  12. 12.
    E. Ufuah, T.H. Tashok, Behavior of stiffened steel plates subjected to accidental loadings. Eng. Lett. 21(2), 95–100 (2013)Google Scholar
  13. 13.
    E. Zalnezhad, A.D.A. Sarhan, M. Hamdi, Adhesion strength predicting of Cr/CrN coated AL7075 using fuzzy logic system for fretting fatigue life enhancement, in Lecture Notes in Engineering and Computer Science: Proceedings of the World Congress on Engineering and Computer Science 2013, WCECS 2013, pp. 589–595, San Francisco, USA, 23–25 Oct 2013Google Scholar
  14. 14.
    C. K. On, J. Teo, Artificial neural controller synthesis in autonomous mobile cognition. IAENG Int. J. Comput. Sci. 36(4), 240–252 (IJCS_36_4_01) (2009) Google Scholar
  15. 15.
    A. Soleimani, Z. Kobti, Event-driven fuzzy paradigm for emotion generation dynamics, in Lecture Notes in Engineering and Computer Science: Proceedings of the World Congress on Engineering and Computer Science 2013, WCECS 2013, pp.168–173, San Francisco, USA, 23–25 Oct 2013Google Scholar
  16. 16.
    ISO Standard, Metallic materials—rotating bar bending fatigue testing, ISO International (2010)Google Scholar
  17. 17.
    C.I. Nkeki, C.R. Nwozo, Optimal investment under inflation protection and optimal portfolios with stochastic cash flows strategy. IAENG Int. J. Appl. Math. 43(2), 54–63 (2013)MathSciNetGoogle Scholar
  18. 18.
    B. Latha, V.S. Senthilkumar, Modeling and analysis of surface roughness parameters in drilling GFRP composites using fuzzy logic. Mater. Manuf. Processes 25, 817–827 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Erfan Zalnezhad
    • 1
  • Ahmed Aly Diaa Mohammed Sarhan
    • 1
  1. 1.Center of Advanced Manufacturing and Material Processing, Department of Mechanical Engineering, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia

Personalised recommendations