Skip to main content

Investigation of surface roughness in the milling of Al7075 and open-cell SiC foam composite and optimization of machining parameters

Abstract

In the present study, aluminum alloy 7075 (Al7075)-based open-cell silicon carbide (SiC) foam composite was fabricated and the machinability of both Al7075 and the open-cell SiC foam Al metal matrix composite was investigated during milling using an uncoated carbide tool. The machining trials were conducted using the Taguchi L27 full-factorial orthogonal array, and the milling parameters were optimized for surface roughness. Analysis of variance was employed to determine the effect of the cutting variables on surface roughness. The experimental results were evaluated by signal-to-noise ratio, 3D surface graphs, artificial neural networks (ANNs) and main effect graphs. The analysis results show that the feed rate was the most significant milling parameter affecting surface roughness of both Al7075 and the open-cell SiC foam composite. Prediction models have been developed for the surface roughness through regression analysis and ANNs. Confirmation experiments were performed to identify the performance of mathematical models, and the surface roughness was predicted with a mean squared error equal to 1.6 and 0.24 % in the milling of Al7075 and open-cell SiC foam composite, respectively. The test result showed that the three-dimensional open-pore SiC foam network reinforcement was restricted the movement of the soft matrix and provided an acceptable surface quality in the milling of MMCs.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

References

  1. Bhushan RK, Kumar S, Das S (2010) Effect of machining parameters on surface roughness and tool wear for 7075 Al alloy SiC composite. Int J Adv Manufact Technol 50:459–469

    Article  Google Scholar 

  2. Zhu X, Jiang D, Tan S (2015) Reaction bonding of open cell SiC–Al2O3 composites. Mater Res Bull 36:2003–2015

    Article  Google Scholar 

  3. Mollicone J, Ansart F, Lenormand P, Duployer B, Tenailleau C, Vicente J (2014) Characterization and functionalization by sol-gel route of SiC foams. J Eur Ceram Soc 34:3479–3487

    Article  Google Scholar 

  4. Liu Y, Edouard D, Nguyen LD, Begin D, Nguyen P, Pham C, Pham-Huu C (2013) High performance structured platelet milli-reactor filled with supported cobalt open cell SiC foam catalyst for the Fischer–Tropsch synthesis. Chem Eng J 222:265–273

    Article  Google Scholar 

  5. Montanaro L, Jorand OY, Fantozzib G, Negroa A (1998) Ceramic foams by powder processing. J Eur Ceram Soc 18:1339–1350

    Article  Google Scholar 

  6. Zhao LZ, Zhao MJ, Yan H, Cao XC, Zhang JS (2009) Mechanical behavior of SiC foam-SiC particles/Al hybrid composites. Trans Nonferrous Metals Soc China 19:547–551

    Article  Google Scholar 

  7. Muthukrishnan N, Davim JP (2009) Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. J Mater Process Technol 209:225–232

    Article  Google Scholar 

  8. Sahoo AK, Pradhan S (2013) Modeling and optimization of Al/SiCp MMC machining using Taguchi approach. Measurement 46:3064–3307

    Article  Google Scholar 

  9. Muñoz-Escalona P, Maropoulos PG (2010) Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351. J Mater Eng Perform 19:185–193

    Article  Google Scholar 

  10. Oktem H, Erzurumlu T, Çöl M (2005) A study of the Taguchi optimization method for surface roughness in finish milling of mold surfaces. Int J Adv Manuf Technol 28:694–700

    Article  Google Scholar 

  11. Kiliçkap E, Çakir O, Aksoy M, Inan A (2005) Study of tool wear and surface roughness in machining of homogenised SiC-p reinforced aluminum metal matrix composite. J Mater Process Technol 164–165:862–867

    Article  Google Scholar 

  12. Manna A, Bhattacharyya B (2004) Investigation for optimal parametric combination for achieving better surface finish during turning of Al/SiC-MMC. Int J Adv Manuf Technol 23:658–665

    Article  Google Scholar 

  13. Davim JP, Antonio CAC (2001) Optimization of cutting conditions in machining of aluminium matrix composites using a numerical and experimental model. J Mater Process Technol 112:78–82

    Article  Google Scholar 

  14. Vakondios D, Kyratsis P, Yaldiz S, Antoniadis A (2012) Influence of milling strategy on the surface roughness in ball end milling of the aluminium alloy Al7075-T6. Measurement 45:1480–1488

    Article  Google Scholar 

  15. Karthikeyan R, Ganesan G, Nagarazan RS (2001) A critical study on machining of Al/SiC composites. Mater Manuf Process 16:47–60

    Article  Google Scholar 

  16. Rao B, Shin YC (2001) Analysis on high-speed face-milling of 7075-T6 aluminum using carbide and diamond cutters. Int J Mach Tools Manuf 41:1763–1781

    Article  Google Scholar 

  17. Benardos PG, Vosniakos GC (2002) Prediction of surface roughness in CNC face milling using neural networks and Taguchi’s design of experiments. Robot Comput Integr Manuf 18:343–354

    Article  Google Scholar 

  18. Vrabel M, Mankova I, Beno J, Tuharsky J (2012) Surface roughness prediction using artificial neural networks when drilling Udimet 720. Procedia Eng 48:693–700

    Article  Google Scholar 

  19. Zain AM, Haron H, Sharif S (2010) Prediction of surface roughness in the end milling machining using Artificial Neural Network. Expert Syst Appl 37:1755–1768

  20. Marimuthu P, Chandrasekaran K (2011) Experimental study on stainless steel for optimal setting of machining parameters using Taguchi and neural network. ARPN J Eng Appl Sci 6:119–127

  21. Zhang JZ, Chen CJ (2009) Surface roughness optimization in a drilling operation using the Taguchi design method. Mater Manuf Process 24:459–467

  22. Krajewski S, Jerzy N, Nowacki J (2015) Structure of AlSi–SiC composite foams surface formed by mechanical and thermal cutting. Appl Surf Sci 327:523–531

  23. Gaitonde VN, Karnik SR, Paulo Davim (2012) Computational methods and optimization in machining of metal matrix composites. In: Machining of metal matrix composites, Springer London, pp 143–162

  24. Mandal N, Doloi B, Mondal B, Das R (2011) Optimization of flank wear using Zirconia Toughened Alumina (ZTA) cutting tool: Taguchi method and regression analysis. Measurement 44:2149–2155

  25. Sözen A, Arcaklioǧlu E (2005) Solar potential in Turkey. Appl Energy 80:35–45

    Article  Google Scholar 

Download references

Acknowledgments

The author wish to thank the Hacettepe University Scientific Research Projects Coordination Unit for the financial support provided to this work through the Scientific Research Projects Grant funding number 1743.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Şener Karabulut.

Ethics declarations

Conflict of interest

There is no potential conflict of interest.

Human and animal rights statement

Human participants and/or animals were not used in the research.

Informed consent

Informed consent is shown in acknowledgement section.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Karabulut, Ş., Karakoç, H. Investigation of surface roughness in the milling of Al7075 and open-cell SiC foam composite and optimization of machining parameters. Neural Comput & Applic 28, 313–327 (2017). https://doi.org/10.1007/s00521-015-2058-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-015-2058-x

Keywords

  • Open-cell SiC foam MMC
  • Al7075
  • Surface roughness
  • Taguchi’s method
  • Artificial neural network