Prediction of TiN coating adhesion strength on aerospace AL7075-T6 alloy using fuzzy rule based system
- 389 Downloads
- 18 Citations
Abstract
In this research work, predicting of titanium nitride (TiN) coating adhesion on AL7075-T6 is presented. First TiN was coated on Al7075-T6 in different conditions and the surfaces adhesion of TiN coated specimens were measured using micro scratch force machine. Second a fuzzy logic model was established to predict the of TiN coating adhesion on AL7075-T6 with respect to changes in input process parameters, DC power, DC bias voltage, and nitrogen flow rate based on the tried data obtained from the scratch force test. Four membership functions are allocated to be connected with each input of the model. Third, new five experimental tests were carried out to verify the predicted results achieved via fuzzy logic model. The result indicated settlement between the fuzzy model and experimental results with the 95.534% accuracy.
Keywords
AL7075-T6 alloy TiN coating PVD magnetron sputtering Adhesion Fuzzy logic modelPreview
Unable to display preview. Download preview PDF.
References
- 1.Sadeler, R., Atasoy, S., Arici, A., and Totik, Y., “The fretting fatigue of commercial hard anodized aluminum alloys,” J. Mat. Eng. Perf., Vol. 18, No. 9, pp. 1280–1284, 2009.CrossRefGoogle Scholar
- 2.Majzoobi, G. H. and Jaleh, M., “Duplex surface treatment on AL7075-T6 alloy against fretting fatigue behavior by application of titanium coating plus nitriding,” Mat. Sci. Eng. A, Vol. 452-453, pp. 673–681, 2007.CrossRefGoogle Scholar
- 3.Wagner, J., Mitterer, C., Penoy, M., Michotte, C., Wallgram, W., and Kathrein, M., “The effect of deposition temperature on microstructure and properties of thermal CVD TiN coatings,” Int. J. Refractory Metals and Hard Materials, Vol. 26, No. 2, pp. 120–126, 2008.CrossRefGoogle Scholar
- 4.Subramanian, B. and Jayachandran, M., “Characterization of reactive magnetron sputtered nanocrystalline titanium nitride (TiN) thin films with brush plated Ni interlayer,” J. Appl. Electrochem., Vol. 37, No. 9, pp. 1069–1075, 2007.CrossRefGoogle Scholar
- 5.Takadoum, J. and Bennani, H. H., “Influence of substrate roughness and coating thickness on adhesion, friction and wear of TiN films,” Surface and Coatings Technology, Vol. 96, No. 2–3, pp. 272–282, 1997.CrossRefGoogle Scholar
- 6.Leung, R. W. K., Lau, H. C. W., and Kwong, C. K., “An expert system to support the optimization of ion plating process: an OLAP-based fuzzy-cum-GA approach,” Expert Sys. Appl., Vol. 25, No. 3, pp. 313–330, 2003.CrossRefGoogle Scholar
- 7.Mohammadzaheri, M., Grainger, S., and Bazghaleh, M., “Fuzzy modeling of a piezoelectric actuator,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 5, pp. 663–670, 2012.CrossRefGoogle Scholar
- 8.Naranbaatar, E., Kim, H.-S., and Lee, B.-R., “Radius measuring algorithm based on machine vision using iterative fuzzy searching method,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 6, pp. 915–926, 2012.CrossRefGoogle Scholar
- 9.Kim, H. M., Park, S. H., Lee, J. M., and Kim, J. S., “A robust control of electro hydrostatic actuator using the adaptive backstepping scheme and fuzzy neural networks,” Int. J. Precis. Eng. Manuf., Vol. 11, No. 2, pp. 227–236, 2010.MathSciNetCrossRefGoogle Scholar
- 10.Oktem, H., Erzurumlu, T., and Erzinchanli, F., “Prediction of minimum surface roughness in end milling mold part using neural network and genetic algorithms,” J. Mat. Design, Vol. 27, pp. 735–744, 2006.CrossRefGoogle Scholar
- 11.Chandrasekaran, M., Muralidhar, M., Murali Krishna, C., and Dixit, U. S., “Application of soft computing techniques in machining performance prediction and optimization: a literature review,” The Int. J. Adv. Manuf. Technol., Vol. 46, No. 5–8, pp. 445–464, 2010.CrossRefGoogle Scholar
- 12.Chunyan, Y., Linhai, T., Yinghui, W., Shebin, W., Tianbao, L., and Bingshe, X., “The effect of substrate bias voltages on impact resistance of CrAlN coatings deposited by modified ion beam enhanced magnetron sputtering,” Surf. Sci., Vol. 255, pp. 4033–4038, 2009.CrossRefGoogle Scholar
- 13.Panich, N., Wangyao, P., Hannongbua, S., Sricharoenchai, P., and Sun, Y., “Effect of argon-nitrogen mixing gas during magnetron sputtering on titanium interlayer deposition with TiB2 coatings on high speed steel,” Rev. Adv. Mat. Sci., Vol. 16, pp. 80–87, 2007.Google Scholar
- 14.Li, J., Zheng, W. T., Jin, Z., Lu, X., Gu, G., Mei, X., and Dong, C., “Influence of substrate dc bias on chemical bonding, adhesion and roughness of carbon nitride films,” Applied Surface Science, Vol. 191, pp. 273–279, 2002.CrossRefGoogle Scholar
- 15.Huang, J. H., Lau, K. W., and Yu, G. P., “Effect of nitrogen flow rate on structure and properties of nanocrystalline TiN thin films produced by unbalanced magnetron sputtering,” Surf. Coat. Technol., Vol. 191, pp. 17–24, 2005.CrossRefGoogle Scholar