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Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy

Yıl 2021, Cilt: 1 Sayı: 1, 89 - 95, 30.08.2021

Öz

Wire electrical discharge machining (WEDM) of γ titanium aluminide is the subject of the current research. Due to the large number of process variables and sophisticated stochastic process mechanisms, selecting the best machining parameter combinations for increased cutting efficiency and accuracy is a difficult task in WEDM. In general, there is no perfect combination that can produce the fastest cutting speed and the finest surface finish quality at the same time. For this purpose, the data were selected from a literature study. This study describes an attempt to devise a suitable machining technique for achieving the highest possible process criteria yield. To model the machining process, a stochastic optimization method, differential evolution, has been performed. Cutting speed, surface roughness, and wire offset are the three most important criteria that have been used as indicators of process performance. The response characteristics can be predicted as a function of six different control parameters, namely pulse on time, pulse off time, peak current, wire tension, dielectric flow rate, and servo reference voltage. The limitations of the candidate models are checked after the R^2_training, R^2_testing and R^2_valiadtion values are calculated to reveal whether the model is realistic. Optimization results are 3.02 mm/min, 2.36 μm, and 0.13 mm for the maximum cutting speed, the minimum surface roughness, and minimum wire offset, respectively. It is shown that the machining model is suitable and that the optimization technique meets practical requirements.

Kaynakça

  • [1] K. H. Ho, and S. T.Newman, “State of the art electrical discharge machining (EDM),” International Journal of MachineTools& Manufacture, vol. 43, pp. 1287–1300, 2003.
  • [2] D. Scott, S. Boyina, and K. P. Rajurkar, “Analysis and optimization of parameter combinations in wire electrical discharge machining,” Int J Prod Res, vol. 29, pp. 2189–2207, 1991.
  • [3] Y. S. Liao, J. T. Huang, and H. C. Su, “A study on the machining – parameters optimisation of wire electrical discharge machining,” J Mater Process Technol, vol. 71 pp. 487–493, 1997.
  • [4] R. Karthikkeyan et al., “Mathematical modeling for electric discharge machining of aluminum -silicon carbide particulate composites,” J Mater Process Technol, vol. 87, pp. 59–63, 1999.
  • [5] J. T. Huang, Y. S. Liao, and W. J Hsue, “Determination of finish-cutting operation number and machining parameters setting in wire electrical discharge machining,” J Mater Process Technol, vol. 87, pp. 69–81, 1999.
  • [6] S. Sarkar, S. Mitra, and B. Bhattacharyya, “Parametric optimisation of wire electrical discharge machining of γ titanium aluminide alloy through an artificial neural network model,” Int J Adv Manuf Technol, vol. 27, pp. 501–508, 2006. https://doi.org/10.1007/s00170-0
  • [7] L. Aydin, and H. S. Artem, “Comparison of stochastic search optimization algorithms for the laminated composites under mechanical and hygrothermal loadings,” Journal of Reinforced Plastics and Composites, vol. 30, no. 14, pp. 1197–1212, 2011. https://doi.org/10.1177/
  • [8] S. Ozturk, L. Aydin, and E. Celik, “A comprehensive study on slicing processes optimization of silicon ingot for photovoltaic applications,” Solar Energy, vol. 161, pp. 109–24, 2018. doi:10.1016/j.solener. 2017.12.040.
  • [9] M. Savran, and L. Aydin, “Stochastic optimization of graphite-flax/epoxy hybrid laminated composite for maximum fundamental frequency and minimum cost,” Engineering Structures, vol. 174, pp. 675–87, 2018. doi:10.1016/j.engstruct.2018.07.043.
  • [10] M. Akcair, M. Savran, L. Aydın, O. Ayakdas, S. Ozturk, and N. Kucukdogan, “Optimum design of anti-buckling behaviour of graphite/epoxy laminated composites by differential evolution and simulated annealing method,” Research on Engineering Structures and Materials, vol. 5, pp. 175–88, 2019.
  • [11] M. L. A. Savran, “Optimum design of hybrid graphite-flax/epoxy laminated composites for minimum cost, minimum weight and maximum frequency using modified simulated annealing method,” Dokuz Eylul University Faculty of Engineering Journal of Science and Engineering, no. 21, pp.833–44, 2019.
Yıl 2021, Cilt: 1 Sayı: 1, 89 - 95, 30.08.2021

Öz

Kaynakça

  • [1] K. H. Ho, and S. T.Newman, “State of the art electrical discharge machining (EDM),” International Journal of MachineTools& Manufacture, vol. 43, pp. 1287–1300, 2003.
  • [2] D. Scott, S. Boyina, and K. P. Rajurkar, “Analysis and optimization of parameter combinations in wire electrical discharge machining,” Int J Prod Res, vol. 29, pp. 2189–2207, 1991.
  • [3] Y. S. Liao, J. T. Huang, and H. C. Su, “A study on the machining – parameters optimisation of wire electrical discharge machining,” J Mater Process Technol, vol. 71 pp. 487–493, 1997.
  • [4] R. Karthikkeyan et al., “Mathematical modeling for electric discharge machining of aluminum -silicon carbide particulate composites,” J Mater Process Technol, vol. 87, pp. 59–63, 1999.
  • [5] J. T. Huang, Y. S. Liao, and W. J Hsue, “Determination of finish-cutting operation number and machining parameters setting in wire electrical discharge machining,” J Mater Process Technol, vol. 87, pp. 69–81, 1999.
  • [6] S. Sarkar, S. Mitra, and B. Bhattacharyya, “Parametric optimisation of wire electrical discharge machining of γ titanium aluminide alloy through an artificial neural network model,” Int J Adv Manuf Technol, vol. 27, pp. 501–508, 2006. https://doi.org/10.1007/s00170-0
  • [7] L. Aydin, and H. S. Artem, “Comparison of stochastic search optimization algorithms for the laminated composites under mechanical and hygrothermal loadings,” Journal of Reinforced Plastics and Composites, vol. 30, no. 14, pp. 1197–1212, 2011. https://doi.org/10.1177/
  • [8] S. Ozturk, L. Aydin, and E. Celik, “A comprehensive study on slicing processes optimization of silicon ingot for photovoltaic applications,” Solar Energy, vol. 161, pp. 109–24, 2018. doi:10.1016/j.solener. 2017.12.040.
  • [9] M. Savran, and L. Aydin, “Stochastic optimization of graphite-flax/epoxy hybrid laminated composite for maximum fundamental frequency and minimum cost,” Engineering Structures, vol. 174, pp. 675–87, 2018. doi:10.1016/j.engstruct.2018.07.043.
  • [10] M. Akcair, M. Savran, L. Aydın, O. Ayakdas, S. Ozturk, and N. Kucukdogan, “Optimum design of anti-buckling behaviour of graphite/epoxy laminated composites by differential evolution and simulated annealing method,” Research on Engineering Structures and Materials, vol. 5, pp. 175–88, 2019.
  • [11] M. L. A. Savran, “Optimum design of hybrid graphite-flax/epoxy laminated composites for minimum cost, minimum weight and maximum frequency using modified simulated annealing method,” Dokuz Eylul University Faculty of Engineering Journal of Science and Engineering, no. 21, pp.833–44, 2019.
Toplam 11 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka
Bölüm Research Articles
Yazarlar

Ömer Faruk Büyükyavuz Bu kişi benim

Yayımlanma Tarihi 30 Ağustos 2021
Gönderilme Tarihi 24 Temmuz 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 1 Sayı: 1

Kaynak Göster

IEEE Ö. F. Büyükyavuz, “Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy”, Journal of Artificial Intelligence and Data Science, c. 1, sy. 1, ss. 89–95, 2021.

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