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

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, R2 testing and R2 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.

Görüntülenme
19
06.06.2022 tarihinden bu yana
İndirme
1
06.06.2022 tarihinden bu yana
Son Erişim Tarihi
26 Mart 2024 11:41
Google Kontrol
Tıklayınız
machining process cutting surface offset roughness suitable technique optimization criteria current stochastic minimum realistic namely parameters control different function predicted characteristics maximum response respectively performance indicators practical requirements whether important Optimization reveal calculated values valiadtion
Tam Metin
Tam Metin İndirmek için tıklayın Ön izleme
Detaylı Görünüm
Eser Adı
(dc.title)
Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy
Eser Sahibi
(dc.contributor.author)
ÖMER FARUK BÜYÜKYAVUZ
Yayın Tarihi
(dc.date.issued)
2021
Yayıncı
(dc.publisher)
Journal of Artificial Intelligence and Data Science
Tür
(dc.type)
Makale
Özet
(dc.description.abstract)
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, R2 testing and R2 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.
Kayıt Giriş Tarihi
(dc.date.accessioned)
06.06.2022
Açık Erişim Tarihi
(dc.date.available)
2022-06-06
Yayın Dili
(dc.language.iso)
eng
Konu Başlıkları
(dc.subject)
γ titanium aluminide
Konu Başlıkları
(dc.subject)
Modeling
Konu Başlıkları
(dc.subject)
Optimization
Konu Başlıkları
(dc.subject)
Wire EDM
Atıf için Künye
(dc.identifier.citation)
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, sayı. 1, ss. 89-95, Ağu. 2021
ISSN
(dc.identifier.issn)
2791-8335
Yayının ilk sayfa sayısı
(dc.identifier.startpage)
89
Yayının son sayfa sayısı
(dc.identifier.endpage)
95
Dergi Adı
(dc.relation.journal)
Journal of Artificial Intelligence and Data Science
Dergi Sayısı
(dc.identifier.issue)
1
Dergi Cilt
(dc.identifier.volume)
1
Haklar
(dc.rights)
Open access
Tek Biçim Adres
(dc.identifier.uri)
https://hdl.handle.net/11469/1934
Analizler
Yayın Görüntülenme
Yayın Görüntülenme
Erişilen ülkeler
Erişilen şehirler
6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve çerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.

creativecommons
Bu site altında yer alan tüm kaynaklar Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.
Platforms