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Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network

Yıl 2012, Cilt: 25 Sayı: 1, 1 - 18, 30.06.2012

Öz



In this study, it is
attempted to model and optimize the wire electrical discharge machining (WEDM)
process using Taguchi design of experiment and artificial neural network. A
neural network with back propagation algorithm was developed to predict the
performance characteristic, namely surface roughness. An approach to determine
optimal machining parameters setting was proposed based on the Taguchi design
method. In addition, analysis of variance (ANOVA) was performed to identify the
significant parameter affecting the surface roughness. Experimental
confirmations were carried out to indicate the effectiveness of this proposed
optimization method and a good improvement was obtained. The performance of
artificial neural network (ANN) was measured with the mean square error and it
was observed that the developed ANN model could predict effectively.




Kaynakça

  • [1] A. Manna, B. Bhattacharyya, “Taguchi and Gauss elimination method: A dual response approach for parametric optimization of CNC wire cut EDM of PRAl SiCMMC”, International Journal of Advance Manufacturing Technology, Vol. 28, No.3, pp.67–75, 2006.
  • [2] H.C. Chen, J.C. Lin, Y.K. Yang, C.H.Tsai “Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach”, Expert Systems with Applications, Vol.37, No.1, pp.7147–7153, 2010.
  • [3] A. Mohammadi, A.F. Tehrani, E.Emanian, D.Karimi, “A new approach to surface roughness and roundness improvement in wire electrical discharge turning based on statistical analyses”, International Journal of Advance Manufacturing Technology, Vol.39, No.5, pp. 64–73, 2008.
  • [4] S. Sarkar, K. Ghosh, S. Mitra1 and B. Bhattacharyya, “An integrated approach to optimization of WEDM combining single-pass and multipass cutting operation”, Materials and Manufacturing Processes, Vol. 25, No.4, pp. 99–807, 2010.
  • [5] R. Ramakrishnan, L. Karunamoorthy, “Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process”, Journal of Materials Processing Technology, Vol. 207, No.2, pp. 343-349, 2008.
  • [6] R. Ramakrishnan, L. Karunamoorth, “Multi response optimization of wire EDM operations using robust design of experiment”, International Journal of Advance Manufacturing Technology, Vol.29, No.2, pp.105–112, 2006.
  • [7] J.T. Huang, Y.S. Liao, W.J. Hsue,“Determination of finish cutting operation number and machining parameters setting in wire electrical discharge machining”, Journal of Materials Processing Technology, Vol.87, No. 7, pp.69-81,1999.
  • [8] N. Tosun, C. Cogun, G. Tosun, “A study on kerf and material removal rate in wire electrical discharge machining based on Taguchi method”, Journal of Materials Processing Technology, Vol. 152, No. 1, pp. 316-322, 2004.
  • [9] A.Mohammadi, A.F.Tehrani, E.Emanian, D.Karimi “Statistical analysis of wire electrical turning on material removal rate”, Journal of Materials Processing Technology, Vol.205, No. 3, pp. 283-290, 2008.
  • [10] Y.C.Lin, C.H.Cheng, B.L.Su, L.R.Wang, “Machining chararacteristics and optimization of machining parameters of SKH 57 high-speed using electrical discharge machining based on Taguchi method”, Materials and Manufacturing Process, Vol.21, No.9, pp. 922-929, 2006.
  • [11] N.Tosun, C.Cogun. “An investigation on wire in WEDM”, Journal of Materials Processing Geri Beslemeli Yapay Sinir Ağları Ve Taguchi Metodu Kullanilarak Tel Erozyon Ġle Kesme Süreci Optimizasyonu 17 Technology, Vol. 134, No. 2, pp. 273-278, 2003.
  • [12] Y.S Tarng, S.C.Ma, L.K.Chung, “Determination of optimal cutting parameters in wire electrical discharge machining”, International Journal of Machine Tools & Manufacture, Vol. 35, No. 4, pp. 1693–1701, 1995.
  • [13] D.Scott, S.Boyina, K.P.Rajurkar, “Analysis and optimization of parameter combination in wire electrical discharge machining”, International Journal of Production Research, Vol.11, No. 1, pp. 2189–2207, 1991.
  • [14] T.A.Spedding, Z.Q.Wang, “Parametric optimization and surface characterization of wire electrical discharge machining process”, Precision Eng., Vol.20, No. 9, pp.5–15, 1997.
  • [15] J.Yuan, K.Wang, T.Yu, M.Fang. “Reliable multi-objective optimization of high speed WEDM process based on Gaussian process regression”, International Journal of Machine Tools & Manufacture, Vol. 60, No. 1, pp. 48-47, 2008.
  • [16] K.Y. Kuang, K.T. Chıang, “Modeling and analysis of machinability evaluation in the wire electrical discharge machining (WEDM) process of aluminum oxide-based ceramic”, Materials and Manufacturing Process, Vol.23, No. 3, pp. 241-250, 2008.
  • [17] N.Tosun, C.Cogun, A.Inan, “The effect of cutting parameters on workpiece surface roughness in wire EDM”, Machining Science Technology, Vol.4, No. 4, pp.209-219, 2003.
  • [18] S.Mahapatra, A.Patnaik, “Parametric optimization of wire electrical discharge machining (WEDM) process using Taguchi method”, Journal of Braz. Soc. of Mech.Sci.& Eng., Vol. XXVIII, No. 3, pp. 422-429, 2006.
  • [19] A.B. Puri, B.Bhattacharyya, “An analysis and optimisation of the geometrical inaccuracy due to wire lag phenomenon in WEDM”, International Journal of Machine Tools & Manufacture, Vol.43, No. 2, pp. 151–159, 2003.
  • [20] T.A. Spedding, Z.Q.Wang, “Study on modeling of EDM process”, Journal of Materials Processing Technology, Vol. 67, No. 4, pp.18-28, 1997.
  • [21] Y.S. Liao, J.T.Huang, H.C. Su, “A study on the machining parameters optimization of wire electrical discharge machining”, Journal of Materials Processing Technology, Vol. 71, No.3, pp.487-493, 1997.
  • [22] K.P. Rajurkar, W.M. Wang, “Thermal modeling and on-line monitoring of wire-EDM”, Journal of Materials Processing Technology, Vol.38, No.1, pp. 417-430, 1993.
  • [23] M.I. Gökler, A.M. Ozangozu, “Experimental investigation of effects of cutting parameters on surface roughness in the WEDM process”, International Journal of Machine Tools & Manufacture, Vol. 40, No. 3, pp.1831–1848, 2000.
  • [24] A. Hascalik, U. Caydas, “Experimental study of wire electrical discharge machining of AISI D5 tool steel”, Journal of Materials Processing Technology, Vol.148, No.2, pp.362-367, 2004.
  • [25] F. Han, J. Jiang, D.Yu. “Influence of discharge current on machined surfaces by thermo-analysis in finish cut of WEDM”, International Journal of Machine Tools & Manufacture, Vol. 47, No. 4, pp.1187–1196, 2007.
  • [26] K.H.Ho, S.T. Newman, S. Rahimifard, R.D. Allen. “State of the art in wire electrical discharge machining (WEDM)”, International Journal of Machine Tools & Manufacture, Vol. 44, No. 4, pp. 1247–1259, 2004.
  • [27] P.M. Escalona and P.G. Maropoulos. “Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351”, Journal of Materials Engineering and Performance, Vol. 19, No.3, pp.185–193, 2010.
  • [28] D. Karayel. “Prediction and control of surface roughness in CNC lathe using artificial neural network”, Journal of Materials Processing Technology., Vol. 209, No.2, pp. 3125–3137, 2009.
  • [29] M.D. Jean, C.D, Liub. J.T. Wang. “Design and development of artificial neural networks for depositing powders in coating treatment”, Applied Surface Science, Vol. 245, No. 3, pp. 290–303, 2005.
  • [30] U.Esme, A.Ozbek, F.Kahraman, A.Sagbas, I. Keles. “Tel erozyonda yüzey kalitesine etki eden parametrelerin Taguchi metoduyla optimizasyonu”, Çankaya Üniversitesi 1. Mühendislik ve Teknoloji Sempozyumu, 24-25 Nisan 2008, Ankara, Bildiri kitabı, ss.394-404.

Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network

Yıl 2012, Cilt: 25 Sayı: 1, 1 - 18, 30.06.2012

Öz



In this study, it is attempted to model and optimize the wire electrical discharge machining (WEDM) process using Taguchi design of experiment and artificial neural network. A neural network with back propagation algorithm was developed to predict the performance characteristic, namely surface roughness. An approach to determine optimal machining parameters setting was proposed based on the Taguchi design method. In addition, analysis of variance (ANOVA) was performed to identify the significant parameter affecting the surface roughness. Experimental confirmations were carried out to indicate the effectiveness of this proposed optimization method and a good improvement was obtained. The performance of artificial neural network (ANN) was measured with the mean square error and it was observed that the developed ANN model could predict effectively.



Kaynakça

  • [1] A. Manna, B. Bhattacharyya, “Taguchi and Gauss elimination method: A dual response approach for parametric optimization of CNC wire cut EDM of PRAl SiCMMC”, International Journal of Advance Manufacturing Technology, Vol. 28, No.3, pp.67–75, 2006.
  • [2] H.C. Chen, J.C. Lin, Y.K. Yang, C.H.Tsai “Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach”, Expert Systems with Applications, Vol.37, No.1, pp.7147–7153, 2010.
  • [3] A. Mohammadi, A.F. Tehrani, E.Emanian, D.Karimi, “A new approach to surface roughness and roundness improvement in wire electrical discharge turning based on statistical analyses”, International Journal of Advance Manufacturing Technology, Vol.39, No.5, pp. 64–73, 2008.
  • [4] S. Sarkar, K. Ghosh, S. Mitra1 and B. Bhattacharyya, “An integrated approach to optimization of WEDM combining single-pass and multipass cutting operation”, Materials and Manufacturing Processes, Vol. 25, No.4, pp. 99–807, 2010.
  • [5] R. Ramakrishnan, L. Karunamoorthy, “Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process”, Journal of Materials Processing Technology, Vol. 207, No.2, pp. 343-349, 2008.
  • [6] R. Ramakrishnan, L. Karunamoorth, “Multi response optimization of wire EDM operations using robust design of experiment”, International Journal of Advance Manufacturing Technology, Vol.29, No.2, pp.105–112, 2006.
  • [7] J.T. Huang, Y.S. Liao, W.J. Hsue,“Determination of finish cutting operation number and machining parameters setting in wire electrical discharge machining”, Journal of Materials Processing Technology, Vol.87, No. 7, pp.69-81,1999.
  • [8] N. Tosun, C. Cogun, G. Tosun, “A study on kerf and material removal rate in wire electrical discharge machining based on Taguchi method”, Journal of Materials Processing Technology, Vol. 152, No. 1, pp. 316-322, 2004.
  • [9] A.Mohammadi, A.F.Tehrani, E.Emanian, D.Karimi “Statistical analysis of wire electrical turning on material removal rate”, Journal of Materials Processing Technology, Vol.205, No. 3, pp. 283-290, 2008.
  • [10] Y.C.Lin, C.H.Cheng, B.L.Su, L.R.Wang, “Machining chararacteristics and optimization of machining parameters of SKH 57 high-speed using electrical discharge machining based on Taguchi method”, Materials and Manufacturing Process, Vol.21, No.9, pp. 922-929, 2006.
  • [11] N.Tosun, C.Cogun. “An investigation on wire in WEDM”, Journal of Materials Processing Geri Beslemeli Yapay Sinir Ağları Ve Taguchi Metodu Kullanilarak Tel Erozyon Ġle Kesme Süreci Optimizasyonu 17 Technology, Vol. 134, No. 2, pp. 273-278, 2003.
  • [12] Y.S Tarng, S.C.Ma, L.K.Chung, “Determination of optimal cutting parameters in wire electrical discharge machining”, International Journal of Machine Tools & Manufacture, Vol. 35, No. 4, pp. 1693–1701, 1995.
  • [13] D.Scott, S.Boyina, K.P.Rajurkar, “Analysis and optimization of parameter combination in wire electrical discharge machining”, International Journal of Production Research, Vol.11, No. 1, pp. 2189–2207, 1991.
  • [14] T.A.Spedding, Z.Q.Wang, “Parametric optimization and surface characterization of wire electrical discharge machining process”, Precision Eng., Vol.20, No. 9, pp.5–15, 1997.
  • [15] J.Yuan, K.Wang, T.Yu, M.Fang. “Reliable multi-objective optimization of high speed WEDM process based on Gaussian process regression”, International Journal of Machine Tools & Manufacture, Vol. 60, No. 1, pp. 48-47, 2008.
  • [16] K.Y. Kuang, K.T. Chıang, “Modeling and analysis of machinability evaluation in the wire electrical discharge machining (WEDM) process of aluminum oxide-based ceramic”, Materials and Manufacturing Process, Vol.23, No. 3, pp. 241-250, 2008.
  • [17] N.Tosun, C.Cogun, A.Inan, “The effect of cutting parameters on workpiece surface roughness in wire EDM”, Machining Science Technology, Vol.4, No. 4, pp.209-219, 2003.
  • [18] S.Mahapatra, A.Patnaik, “Parametric optimization of wire electrical discharge machining (WEDM) process using Taguchi method”, Journal of Braz. Soc. of Mech.Sci.& Eng., Vol. XXVIII, No. 3, pp. 422-429, 2006.
  • [19] A.B. Puri, B.Bhattacharyya, “An analysis and optimisation of the geometrical inaccuracy due to wire lag phenomenon in WEDM”, International Journal of Machine Tools & Manufacture, Vol.43, No. 2, pp. 151–159, 2003.
  • [20] T.A. Spedding, Z.Q.Wang, “Study on modeling of EDM process”, Journal of Materials Processing Technology, Vol. 67, No. 4, pp.18-28, 1997.
  • [21] Y.S. Liao, J.T.Huang, H.C. Su, “A study on the machining parameters optimization of wire electrical discharge machining”, Journal of Materials Processing Technology, Vol. 71, No.3, pp.487-493, 1997.
  • [22] K.P. Rajurkar, W.M. Wang, “Thermal modeling and on-line monitoring of wire-EDM”, Journal of Materials Processing Technology, Vol.38, No.1, pp. 417-430, 1993.
  • [23] M.I. Gökler, A.M. Ozangozu, “Experimental investigation of effects of cutting parameters on surface roughness in the WEDM process”, International Journal of Machine Tools & Manufacture, Vol. 40, No. 3, pp.1831–1848, 2000.
  • [24] A. Hascalik, U. Caydas, “Experimental study of wire electrical discharge machining of AISI D5 tool steel”, Journal of Materials Processing Technology, Vol.148, No.2, pp.362-367, 2004.
  • [25] F. Han, J. Jiang, D.Yu. “Influence of discharge current on machined surfaces by thermo-analysis in finish cut of WEDM”, International Journal of Machine Tools & Manufacture, Vol. 47, No. 4, pp.1187–1196, 2007.
  • [26] K.H.Ho, S.T. Newman, S. Rahimifard, R.D. Allen. “State of the art in wire electrical discharge machining (WEDM)”, International Journal of Machine Tools & Manufacture, Vol. 44, No. 4, pp. 1247–1259, 2004.
  • [27] P.M. Escalona and P.G. Maropoulos. “Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351”, Journal of Materials Engineering and Performance, Vol. 19, No.3, pp.185–193, 2010.
  • [28] D. Karayel. “Prediction and control of surface roughness in CNC lathe using artificial neural network”, Journal of Materials Processing Technology., Vol. 209, No.2, pp. 3125–3137, 2009.
  • [29] M.D. Jean, C.D, Liub. J.T. Wang. “Design and development of artificial neural networks for depositing powders in coating treatment”, Applied Surface Science, Vol. 245, No. 3, pp. 290–303, 2005.
  • [30] U.Esme, A.Ozbek, F.Kahraman, A.Sagbas, I. Keles. “Tel erozyonda yüzey kalitesine etki eden parametrelerin Taguchi metoduyla optimizasyonu”, Çankaya Üniversitesi 1. Mühendislik ve Teknoloji Sempozyumu, 24-25 Nisan 2008, Ankara, Bildiri kitabı, ss.394-404.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Konular Endüstri Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Aysun Sağbaş

Funda Kahraman

Uğur Esme Bu kişi benim

Yayımlanma Tarihi 30 Haziran 2012
Kabul Tarihi 24 Ağustos 2012
Yayımlandığı Sayı Yıl 2012 Cilt: 25 Sayı: 1

Kaynak Göster

APA Sağbaş, A., Kahraman, F., & Esme, U. (2012). Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 25(1), 1-18.
AMA Sağbaş A, Kahraman F, Esme U. Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network. ESOGÜ Müh Mim Fak Derg. Haziran 2012;25(1):1-18.
Chicago Sağbaş, Aysun, Funda Kahraman, ve Uğur Esme. “Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi 25, sy. 1 (Haziran 2012): 1-18.
EndNote Sağbaş A, Kahraman F, Esme U (01 Haziran 2012) Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 25 1 1–18.
IEEE A. Sağbaş, F. Kahraman, ve U. Esme, “Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network”, ESOGÜ Müh Mim Fak Derg, c. 25, sy. 1, ss. 1–18, 2012.
ISNAD Sağbaş, Aysun vd. “Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network”. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 25/1 (Haziran 2012), 1-18.
JAMA Sağbaş A, Kahraman F, Esme U. Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network. ESOGÜ Müh Mim Fak Derg. 2012;25:1–18.
MLA Sağbaş, Aysun vd. “Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, c. 25, sy. 1, 2012, ss. 1-18.
Vancouver Sağbaş A, Kahraman F, Esme U. Optimization of Wire Electrical Discharge Machining Process Using Taguchi Method and Back Propagation Neural Network. ESOGÜ Müh Mim Fak Derg. 2012;25(1):1-18.

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