Dergiler / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2018 / Cilt: 36 - Sayı: 4

PREDICTION OF SURFACE HARDNESS IN A BURNISHING PROCESS USING TAGUCHI METHOD, FUZZY LOGIC MODEL AND REGRESSION ANALYSIS

Sayfa
1283–1295
Yayın Tarihi
2018-12-01
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:The available work is aimed for comparison and estimation of surface hardness in ball burnishing process of aluminum alloy based upon the Taguchi technique, Fuzzy logic and regression models.
📊
Temel Bulgular & Veri:The ball burnishing parameters like burnishing speed, force, feed rate and number of passes were designed using Taguchi L25 orthogonal design matrix.
💡
Sonuç & Katkı:With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Ball burnishing · surface hardness · Taguchi method

Abstract

The available work is aimed for comparison and estimation of surface hardness in ball burnishing process of aluminum alloy based upon the Taguchi technique, Fuzzy logic and regression models. The ball burnishing parameters like burnishing speed, force, feed rate and number of passes were designed using Taguchi L25 orthogonal design matrix. Taguchi’s signal to noise ratio was used to optimize the surface hardness. The effect of burnishing parameters on surface hardness was established by analysis of variance. Fuzzy logic was conducted using Matlab Toolbox. Taguchi technique, second order regression model and variance analysis were developed using MINITAB 17. The predicted hardness values of performance parameters were operated to compare the distinct models. The results of predicted models indicated that the consistent predictive model is the fuzzy logic model. With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.

🔖

Bu Makaleye Atıf Yap

BAŞAR, G., KAHRAMAN, F. (2018). PREDICTION OF SURFACE HARDNESS IN A BURNISHING PROCESS USING TAGUCHI METHOD, FUZZY LOGIC MODEL AND REGRESSION ANALYSIS. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 36 - Sayı: 4, 1283–1295. https://ajindex.com/articles/419011

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (12)

  1. El-Tayeb, N. S. M., Low, K. O., Brevern, P. V., (2007) Influence of roller burnishing contact width and burnishing orientation on surface quality and tribological behaviour of Aluminium 6061, Journal of materials processing technology,186(1-3), 272-278
  2. Esme, U., (2010) Use of Grey based Taguchi method in ball burnishing process for the optimization of surface roughness and microhardness of AA 7075 aluminum alloy, Materiali in Tehnologije, 44(3), 129-135
  3. Bounouara, A., Hamadache, H., Amirat, A., (2018) Investigation on the effect of ball burnishing on fracture toughness in spiral API X70 pipeline steel, The International Journal of Advanced Manufacturing Technology, 94(9-12), 4543-4551
  4. Basak, H., Goktas, H. H., (2009) Burnishing process on al-alloy and optimization of surface roughness and surface hardness by fuzzy logic, Materials & Design, 30(4), 1275-1281
  5. Esme, U., Sagbas, A., Kahraman, F., Kulekci, M.K., (2008) Use of artificial neural networks in ball burnishing process for the prediction of surface roughness of AA 7075 aluminum alloy, Materiali in tehnologije, 42(5), 215-219
  6. Kahraman, F., (2015) Application of the response surface methodology in the ball burnishing process for the prediction and analysis of surface hardness of the aluminum alloy AA 7075, Materials Testing, 57(4), 311-315
  7. Hassan, A. M., Al-Dhifi, S. Z., (1999) Improvement in the wear resistance of brass components by the ball burnishing process, Journal of Materials Processing Technology, 96(1-3), 73-80
  8. Klocke, F., Bäcker, V., Wegner, H., Zimmermann, M., (2011) Finite element analysis of the roller burnishing process for fatigue resistance increase of engine components, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 225(1), 2-11
  9. Pałka, K., Weroński, A., Zalewski, K., (2006) Mechanical properties and corrosion resistance of burnished X5CrNi18-9 stainless steel, Journal of Achievements in Materials and Manufacturing Engineering, 16(1-2), 57-62
  10. Yen, Y. C., Sartkulvanich, P., Altan, T., (2005) Finite element modeling of roller burnishing process, CIRP Annals-Manufacturing Technology, 54(1), 237-240
  11. Sagbas, A., (2011) Analysis and optimization of surface roughness in the ball burnishing process using response surface methodology and desirabilty function, Advances in Engineering Software, 42(11), 992-998
  12. El-Taweel, T. A., El-Axir, M. H., (2009) Analysis and optimization of the b