Study on Machining Parameters for Thrust Force and Torque in Milling AA7039 Composites Reinforced with Al2O3/B4C/SiC Particles

Sener KARABULUT

doi:https://doi.org/10.19072/ijet.05966

Makale detayları

Study on Machining Parameters for Thrust Force and Torque in Milling AA7039 Composites Reinforced with Al2O3/B4C/SiC Particles

Yazarlar:

Sener KARABULUT

Yayıncı:

İstanbul Gelisim University

Dergi:

International Journal of Engineering Technologies IJET 2016 Vol.2 Issue 2, pp.68-75

Belge Tipi:

Makale

Yayın Tarihi:

6/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000461160

Sıklık:

Aylık

eISSN:

2149-5262

pISSN:

2149-0104

DOI:

https://doi.org/10.19072/ijet.05966

Özet:

 

Metal matrix composites are used in many industrial fields such as automobile, military and aerospace applications due to their superior mechanical properties. In the present study, three aluminum 7039 metal matrix composite (MMCs) samples reinforced with 10 wt.% particulates of aluminum oxide (Al2O3), 10 wt.% boron carbide (B4C), and 10 wt.% silicon carbide (SiC) were successfully fabricated using a powder metallurgy and hot extrusion method. The influences of cutting parameters on the thrust cutting force and torque during milling of the three MMCs were investigated under dry machining conditions. The milling tests were performed based on the Taguchi orthogonal -array design of experiments, for different machining parameters such as cutting speed, feed and depth of cut. The effect of reinforcement contents on cutting force and torque were specified by utilizing analysis of variance (ANOVA). Mathematical models have been generated for the thrust force and torque through regression method. The results indicated that the minimal thrust force and torque were obtained in the machining of the Al2O3 reinforced specimen. The cutting force was directly influenced by the cutting feed and the axial cutting depth was the most effective machining parameter affecting milling torque in the machining of three composite specimens. The experimental results were modeled using regression analysis and artificial neural networks (ANN) to predict the thrust force and torque. The thrust force and torque were predicted with a mean squared error equal to 5.85% and 5.12% respectively using ANN models.

Makale detayları

Study on Machining Parameters for Thrust Force and Torque in Milling AA7039 Composites Reinforced with Al2O3/B4C/SiC Particles

Yazarlar: Sener KARABULUT

Yayıncı: İstanbul Gelisim University

Dergi: International Journal of Engineering Technologies IJET 2016 Vol.2 Issue 2, pp.68-75

Belge Tipi: Makale

Yayın Tarihi: 6/2016

Belge Dili: Türkçe

Document ID (Org No.): 2000461160

Sıklık: Aylık

eISSN: 2149-5262

pISSN: 2149-0104

DOI: https://doi.org/10.19072/ijet.05966

Sayı

Yazarlar:

Sener KARABULUT

Yayıncı:

İstanbul Gelisim University

Dergi:

International Journal of Engineering Technologies IJET 2016 Vol.2 Issue 2, pp.68-75

Belge Tipi:

Makale

Yayın Tarihi:

6/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000461160

Sıklık:

Aylık

eISSN:

2149-5262

pISSN:

2149-0104

DOI:

https://doi.org/10.19072/ijet.05966