Araştırma Makalesi

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

Cilt: 1 Sayı: 1 30 Ağustos 2021
  • Ömer Faruk Büyükyavuz *
PDF İndir

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

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.

Anahtar Kelimeler

Kaynakça

  1. [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. [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. [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. [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. [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. [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. [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. [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.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapay Zeka

Bölüm

Araştırma Makalesi

Yazarlar

Ömer Faruk Büyükyavuz * Bu kişi benim
Türkiye

Yayımlanma Tarihi

30 Ağustos 2021

Gönderilme Tarihi

24 Temmuz 2021

Kabul Tarihi

25 Ağustos 2021

Yayımlandığı Sayı

Yıl 2021 Cilt: 1 Sayı: 1

Kaynak Göster

APA
Büyükyavuz, Ö. F. (2021). Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy. Journal of Artificial Intelligence and Data Science, 1(1), 89-95. https://izlik.org/JA47AM38SY
AMA
1.Büyükyavuz ÖF. Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy. Journal of Artificial Intelligence and Data Science. 2021;1(1):89-95. https://izlik.org/JA47AM38SY
Chicago
Büyükyavuz, Ömer Faruk. 2021. “Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy”. Journal of Artificial Intelligence and Data Science 1 (1): 89-95. https://izlik.org/JA47AM38SY.
EndNote
Büyükyavuz ÖF (01 Ağustos 2021) Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy. Journal of Artificial Intelligence and Data Science 1 1 89–95.
IEEE
[1]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, Ağu. 2021, [çevrimiçi]. Erişim adresi: https://izlik.org/JA47AM38SY
ISNAD
Büyükyavuz, Ömer Faruk. “Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy”. Journal of Artificial Intelligence and Data Science 1/1 (01 Ağustos 2021): 89-95. https://izlik.org/JA47AM38SY.
JAMA
1.Büyükyavuz ÖF. Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy. Journal of Artificial Intelligence and Data Science. 2021;1:89–95.
MLA
Büyükyavuz, Ömer Faruk. “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, Ağustos 2021, ss. 89-95, https://izlik.org/JA47AM38SY.
Vancouver
1.Ömer Faruk Büyükyavuz. Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy. Journal of Artificial Intelligence and Data Science [Internet]. 01 Ağustos 2021;1(1):89-95. Erişim adresi: https://izlik.org/JA47AM38SY