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Published in: Neural Computing and Applications 2/2017

07-09-2015 | Original Article

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

Authors: Şener Karabulut, Halil Karakoç

Published in: Neural Computing and Applications | Issue 2/2017

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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.

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Literature
1.
go back to reference 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 50:459–469CrossRef 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 50:459–469CrossRef
2.
go back to reference Zhu X, Jiang D, Tan S (2015) Reaction bonding of open cell SiC–Al2O3 composites. Mater Res Bull 36:2003–2015CrossRef Zhu X, Jiang D, Tan S (2015) Reaction bonding of open cell SiC–Al2O3 composites. Mater Res Bull 36:2003–2015CrossRef
3.
go back to reference 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 34:3479–3487CrossRef 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 34:3479–3487CrossRef
4.
go back to reference 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 222:265–273CrossRef 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 222:265–273CrossRef
5.
go back to reference Montanaro L, Jorand OY, Fantozzib G, Negroa A (1998) Ceramic foams by powder processing. J Eur Ceram Soc 18:1339–1350CrossRef Montanaro L, Jorand OY, Fantozzib G, Negroa A (1998) Ceramic foams by powder processing. J Eur Ceram Soc 18:1339–1350CrossRef
6.
go back to reference 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 19:547–551CrossRef 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 19:547–551CrossRef
7.
go back to reference Muthukrishnan N, Davim JP (2009) Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. J Mater Process Technol 209:225–232CrossRef Muthukrishnan N, Davim JP (2009) Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. J Mater Process Technol 209:225–232CrossRef
8.
go back to reference Sahoo AK, Pradhan S (2013) Modeling and optimization of Al/SiCp MMC machining using Taguchi approach. Measurement 46:3064–3307CrossRef Sahoo AK, Pradhan S (2013) Modeling and optimization of Al/SiCp MMC machining using Taguchi approach. Measurement 46:3064–3307CrossRef
9.
go back to reference Muñoz-Escalona P, Maropoulos PG (2010) Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351. J Mater Eng Perform 19:185–193CrossRef Muñoz-Escalona P, Maropoulos PG (2010) Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351. J Mater Eng Perform 19:185–193CrossRef
10.
go back to reference 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 28:694–700CrossRef 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 28:694–700CrossRef
11.
go back to reference 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 164–165:862–867CrossRef 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 164–165:862–867CrossRef
12.
go back to reference 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 23:658–665CrossRef 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 23:658–665CrossRef
13.
go back to reference 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 112:78–82CrossRef 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 112:78–82CrossRef
14.
go back to reference 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 45:1480–1488CrossRef 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 45:1480–1488CrossRef
15.
go back to reference Karthikeyan R, Ganesan G, Nagarazan RS (2001) A critical study on machining of Al/SiC composites. Mater Manuf Process 16:47–60CrossRef Karthikeyan R, Ganesan G, Nagarazan RS (2001) A critical study on machining of Al/SiC composites. Mater Manuf Process 16:47–60CrossRef
16.
go back to reference 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 41:1763–1781CrossRef 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 41:1763–1781CrossRef
17.
go back to reference 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 18:343–354CrossRef 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 18:343–354CrossRef
18.
go back to reference Vrabel M, Mankova I, Beno J, Tuharsky J (2012) Surface roughness prediction using artificial neural networks when drilling Udimet 720. Procedia Eng 48:693–700CrossRef Vrabel M, Mankova I, Beno J, Tuharsky J (2012) Surface roughness prediction using artificial neural networks when drilling Udimet 720. Procedia Eng 48:693–700CrossRef
19.
go back to reference 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 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.
go back to reference 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 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.
go back to reference Zhang JZ, Chen CJ (2009) Surface roughness optimization in a drilling operation using the Taguchi design method. Mater Manuf Process 24:459–467 Zhang JZ, Chen CJ (2009) Surface roughness optimization in a drilling operation using the Taguchi design method. Mater Manuf Process 24:459–467
22.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference Sözen A, Arcaklioǧlu E (2005) Solar potential in Turkey. Appl Energy 80:35–45CrossRef Sözen A, Arcaklioǧlu E (2005) Solar potential in Turkey. Appl Energy 80:35–45CrossRef
Metadata
Title
Investigation of surface roughness in the milling of Al7075 and open-cell SiC foam composite and optimization of machining parameters
Authors
Şener Karabulut
Halil Karakoç
Publication date
07-09-2015
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 2/2017
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-2058-x

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