Abstract
In the present study, aluminium 7039-based 10% weight fraction of SiC and 10% \(\hbox {B}_{4}\hbox {C}_{\mathrm{p}}\) metal matrix composites (MMCs) were produced by powder metallurgy and investigated the influential machining parameters on surface quality using an uncoated carbide tool under dry cutting environment. The experiments were performed based on Taguchi’s \({L}_{18}\) (\(2^{1}\,\times \,3^{2})\) with a mixed orthogonal array. The optimal cutting parameters for better surface finish were defined using signal-to-noise (S / N) ratio, central composite desirability function and regression analysis. Experimental results showed that the finished surface was significantly affected by the interfacial bonding effect of reinforcement particles and built-up edge formation. Better surface roughness was obtained in the milling of AA7039/\(\hbox {B}_{4}\hbox {C}\)-MMCs. The analysis findings indicated that the most significant cutting parameters on the finished surface were the cutting speed and feed rate. The cutting depth was not shown to have a meaningful correlation with surface quality in the milling of both MMCs. Artificial neural network was produced a low prediction error as compared to the regression modelling.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Karabulut, Ş.; Uğur, G.; Henifi, Ç.: Study on the mechanical and drilling properties of AA7039 composites reinforced with \(\text{ Al }_{2}\text{ O }_{3}/\text{ B }_{4}\text{ C }\)/SiC particles. Compos. Part B 93, 43–55 (2016)
Karabulut, Ş.; Henifi, Ç.; Halil, K.: Experimental investigation and optimization of cutting force and tool wear in milling Al7075 and open-cell SiC foam composite. Arab. J. Sci. Eng. 41, 1797–1812 (2016)
Davim, J.P.: Machining of Metal Matrix Composites. Springer, London (2012)
Manna, A.; Bhattacharayya, B.: A study on machinability of Al/SiC-MMC. J. Mater. Process. Technol. 140, 711–716 (2003)
Karabulut, Ş.; Halil, K.; Ramazan, Ç.: Influence of \(\text{ B }_{4}\text{ C }\) particle reinforcement on mechanical and machining properties of Al6061/\(\text{ B }_{4}\text{ C }\) composites. Compos. Part B 101, 87–98 (2016)
Soy, U.; Ficici, F.; Demir, A.: Evaluation of the Taguchi method for wear behavior of Al/SiC/B4C composites. J. Compos. Mater. 46, 851–859 (2011)
El-Gallab, M.; Sklad, M.: Machining of Al/SiC particulate metal-matrix composites. Part I?: Tool performance. J. Mater. Process. Technol. 83, 151–158 (1998)
Baharvandi, H.R.; Hadian, A.M.; Alizadeh, A.: Processing and mechanical properties of boron carbide-titanium diboride ceramic matrix composites. Appl. Compos. Mater. 13, 191–198 (2006)
Sahoo, A.K.; Pradhan, S.: Modeling and optimization of Al/SiCp MMC machining using Taguchi approach. Measurement 46, 306–307 (2013)
Barnes, S.; Pashby, I.R.: Machining of aluminium based metal matrix composites. Appl. Compos. Mater. 2, 31–42 (1995)
Karabulut, Ş.: Optimization of surface roughness and cutting force during AA7039/\(\text{ Al }_{2}\text{ O }_{3}\) metal matrix composites milling using neural networks and Taguchi method. Measurement. 66, 139–149 (2015)
Kumar, R.; Chauhan, S.: Study on surface roughness measurement for turning of Al7075/10/SiCp and Al7075 hybrid composites by using response surface methodology (RSM) and artificial neural networking. Measurement 65, 166–180 (2015)
Venkatesan, K.; Ramanujam, R.; Joel, J.; Jeyapandiarajan, P.; Vignesh, M.; Tolia, D.J.; Krishna, R.V.: Study of cutting force and surface roughness in machining of al alloy hybrid composite and optimized using response surface methodology. Proced. Eng. 97, 677–686 (2014)
Muthukrishnan, N.; Davim, J.P.: Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. J. Mater. Process. Technol. 209, 225–232 (2009)
Kılıçkap, E.; Çakır, O.; Aksoy, M.; İnan, A.: Study of tool wear and surface roughness in machining of homogenised SiCp reinforced aluminium metal matrix composite. J. Mater. Process. Technol. 164–165, 862–867 (2005)
Ozben, T.; Kilickap, E.; Çakır, O.: Investigation of mechanical and machinability properties of SiC particle reinforced Al-MMC. J. Mater. Process. Technol. 198, 220–225 (2008)
Tool Life Testing in Milling. Part 1: Face Milling. ISO 8688-1, International ISO Standard (1989)
ISO-4287. Geometrical Product Specifications (GPS), Surface Texture: Profile Method, Terms, Definitions and Surface Texture Parameters. International Organization for Standardization, ISO-4287 (1997)
Mia, M.; Nikhil, R.D.: Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method. Int. J. Adv. Manuf. Technol. 88, 739–753 (2017)
Sarıkaya, M.; Güllü, A.: Taguchi design and response surface methodology based analysis of machining parameters in CNC turning under MQL. J. Clean. Prod. 65, 604–616 (2014)
Bayraktar, Ö.; Uzun, G.; Çakiroğlu, R.; Guldas, A.: Experimental study on the 3D-printed plastic parts and predicting the mechanical properties using artificial neural networks. Polym. Adv. Technol. (2016). doi:10.1002/pat.3960
Sarıkaya, M.; Yılmaz, V.; Güllü, A.: Analysis of cutting parameters and cooling/lubrication methods for sustainable machining in turning of Haynes 25 superalloy. J. Clean. Prod. 133, 172–181 (2016)
Yıldırım, Ç.V.; Kıvak, T.; Sarıkaya, M.; Erzincanlı, F.: Determination of MQL parameters contributing to sustainable machining in the milling of nickel-base superalloy waspaloy. Arab. J. Sci. Eng. (2017). doi:10.1007/s13369-017-2594-z
Mia, M.; Khan, M.A.; Dhar, N.R.: Study of surface roughness and cutting forces using ANN, RSM, and ANOVA in turning of Ti–6Al–4V under cryogenic jets applied at flank and rake faces of coated WC tool. Int. J. Adv. Manuf. Technol. (2017). doi:10.1007/s00170-017-0566-9
Mia, M.; Dhar, N.R.: Response surface and neural network based predictive models of cutting temperature in hard turning. J. Adv. Res. 7(6), 1035–1044 (2016)
Acknowledgements
The authors wish to thank Hacettepe University Scientific Research Projects Coordination Unit for the financial support. This work was supported by Research Fund of the Hacettepe University. Project ID #636
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Karabulut, Ş., Gökmen, U. & Çinici, H. Optimization of Machining Conditions for Surface Quality in Milling AA7039-Based Metal Matrix Composites. Arab J Sci Eng 43, 1071–1082 (2018). https://doi.org/10.1007/s13369-017-2691-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-017-2691-z