AISI P20 Plastik Kalıp Çeliğinin Dik İşleme Tezgahında Baralanmasında İşleme Parametrelerinin Kesme Torkuna Etkisi
Öz
Anahtar Kelimeler
Destekleyen Kurum
Proje Numarası
Etik Beyan
Teşekkür
Kaynakça
- Kayır Y. and Süzgünol M., Optimization of cutting parameters for drilling AISI P20 die mold alloy steel with Taguchi and GRA methods. Gazi University Journal of Science, 31(3): (2018) 898-910.
- [2] Stoić A., Kopač J., and Cukor G., Testing of machinability of mould steel 40CrMnMo7 using genetic algorithm. Journal of materials processing technology, 164: (2005) 1624-1630.
- [3] Zeilmann R.P., Nicola G.L., Vacaro T., Teixeira C.R., and Heiler R., Implications of the reduction of cutting fluid in drilling AISI P20 steel with carbide tools. The International Journal of Advanced Manufacturing Technology, 58: (2012) 431-441.
- [4] Slamani M., Mayer R., Balazinski M., and Engin S., Identification and compensation of dynamic scale mismatches in high-speed end mill boring trajectory on CNC machines. J. Manuf. Sci. Eng., 132(034501): (2010)
- [5] Lazoglu I., Atabey F., and Altintas Y., Dynamics of boring processes: Part III-time domain modeling. International journal of machine tools and manufacture, 42(14): (2002) 1567-1576.
- [6] Lacerda H.B. and Siqueira I.L., Blade geometry effects on the boring of valve seats of internal combustion engines. The International Journal of Advanced Manufacturing Technology, 63: (2012) 269-280.
- [7] Del Taglia A. and Tani G., A method for measuring cutting forces in boring operations. International Journal of Machine Tool Design and Research, 22(1): (1982) 23-30.
- [8] Arsuaga M., de Lacalle L.L., Lobato R., Urbikain G., and Campa F. Effect of centrifugal forces on dimensional error of bored shapes. in AIP Conference Proceedings. 2012. American Institute of Physics
Ayrıntılar
Birincil Dil
Türkçe
Konular
İmalat Süreçleri ve Teknolojileri
Bölüm
Araştırma Makalesi
Yazarlar
Aslan Akdulum
*
0000-0003-2030-3167
Türkiye
Mehmet Süzgünol
0009-0004-9320-6848
Türkiye
Yunus Kayır
0000-0001-6793-7103
Türkiye
Erken Görünüm Tarihi
24 Şubat 2025
Yayımlanma Tarihi
24 Mart 2025
Gönderilme Tarihi
16 Eylül 2024
Kabul Tarihi
31 Ocak 2025
Yayımlandığı Sayı
Yıl 2025 Cilt: 13 Sayı: 1
Cited By
Improving the Prediction Accuracy of Surface Roughness in the Boring Process using Integrated Machine Learning Methods
International Journal of Precision Engineering and Manufacturing
https://doi.org/10.1007/s12541-025-01338-y
