Polyamid Malzemelerde Yüzey Pürüzlüğünün Belirlenmesi İçin Yapay Zeka Destekli Bir Uygulama Tasarımı
Abstract
Mühendislik
işlemlerinde, yüzey kalitesi malzemelerin kalite göstergelerinden birisidir.
Talaşlı imalat işlemlerinde elde edilmek istenen yüzey kalitesi, yüzey
pürüzlülüğü ölçümüyle kontrol edilir. Yüzey pürüzlülüğü oluşumunu etkileyen
birçok faktör bulunmaktadır. Kullanılan kesici takım cinsi, malzeme türü, kesme
şartları gibi faktörler yüzey pürüzlüğü değişimini etkiler. Bu çalışmada,
deneysel olarak bulunan ortalama yüzey pürüzlüğü değerleri geliştirilen uzman
sistem bilgisayar programının bilgi tabanına dinamik olarak yüklenmektedir.
Genel talaşlı imalat kesme şartlarına ait bilgilerde sisteme karar verme
aşamasında destek olmaktadır. Bu sayede, belirlenen kesme durumlarında oluşması
beklenen ortalama yüzey pürüzlüğü değeri, uzman sistemin sağladığı avantajla
çok hızlı ve doğru şekilde belirlenebilmektedir.
Keywords
References
- [1] T. Özel ve Y. Karpat, "Predictive Modeling Of Surface Roughness And Tool Wear In Hard Turning Using Regression And Neural Networks", International Journal of Machine Tools & Manufacture, vol.45, pp. 467-479, 2005.
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- [5] J. P. Davim, L. R. Silva, A. Festas and A. M. Abrao, “Machinability Study On Precision Turning Of PA66 Polyamide With And Without Glass Fiber Reinforcing", Materials and Design, vol.30, pp.228-234, 2009.
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- [10] CZ Liu, J.Q. Wu, J.Q. Li, L.Q. Ren, J. Tong and R.O. Arneli, "Tribological Behaviors Of PA/UHMWPE Blend Under Dry And Lubricated Condition", Wear, vol. 260, pp.109-115, 2006.
- [11] F. Mata, P. Reis and J.P. Oavim, "Physical Cutting Model Of Polyamide Composites (PA66 GF30)", Materials Science Forum, vol. 514, pp. 643-647, 2006.
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- [13] M. Bozdemir, “Prediction Of Surface Roughness Considering Cutting Parameters And Humidity Condition İn End Milling Of Polyamide Materials”, Computational Intelligence and Neuroscience, 2018.
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- [15] O. Poyrazoğlu, M. Gülesin ve Y. Kayır, “Uzman sistem tekniklerine dayalı alışılmamış imalat yöntemlerinin tespiti”, Makine Tasarım ve İmalat Yön. Konferansı, Ankara, Türkiye, 1997, ss.80-89.
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- [17] M. Bozdemir and F. Mendi, "The Knowledge Management System Architecture For Artificial Intelligent Aided Systematic Design", Journal of The Faculty of Engineering and Architecture of Gazi University, vol. 20, no. 2, pp.267-274, 2005.
The Application Design Of Artificial Intelligent Assisted For The Detection Of Surface Roughness In Polyamide Materials
Abstract
In the process of engineering the surface quality is one of the indicators of the quality of materials. Surface quality which is aimed to attain in metal cutting processes is controlled by the measurement of surface roughness. There are many factors that affect the formation of surface roughness. Factors such as the type of cutting tool that is used, the type of material, cutting conditions influence the formation of surface roughness. In this study, polyamide materials surface roughness values which are detected experimentally are dynamically loaded on the database of expert system computer program that is developed. Information about general metal cutting conditions is also supportive in the process of detection of system. In this way polyamide material average surface roughness values that is expected to occur in the detected cutting conditions can be estimated fast and correctly with the help of the expert system.
Keywords
References
- [1] T. Özel ve Y. Karpat, "Predictive Modeling Of Surface Roughness And Tool Wear In Hard Turning Using Regression And Neural Networks", International Journal of Machine Tools & Manufacture, vol.45, pp. 467-479, 2005.
- [2] H. K. Tonshoff, C. Arendt, and A.R. Ben, "Cutting Of Hardened Steel", An.of CIRP, vol.49, no.2, pp 547-566, 2000.
- [3] A. Acır, "Talaş kaldırma işlemlerinde yüzey pürüzlülüğüne etki eden faktörlerin incelenmesi", II. Makine Tasarım ve imalat Kongresi, Konya, Türkiye, 2003, ss. 209-216.
- [4] M. Y. Wang and H. Y. Chang, "Experimental Study Of Surface Roughness In Slot End Milling", International Journal of Machine Tools & Manufacture, vol. 44, pp. 51-57, 2004.
- [5] J. P. Davim, L. R. Silva, A. Festas and A. M. Abrao, “Machinability Study On Precision Turning Of PA66 Polyamide With And Without Glass Fiber Reinforcing", Materials and Design, vol.30, pp.228-234, 2009.
- [6] N. Adams, "Friction And Deformation Of Nylons", Journal of Applied Polymer Science, vol.7, pp. 2075-2103, 1963.
- [7] P. Samyna, P. Baets, G. Schoukens, and I. Van Driessche, "Friction, Wear And Transfer Of Pure And Internally Lubricated Cast Polyamides at Various Testing Scales", Wear, vol. 262, pp.14331449, 2007.
- [8] M. Palabiyik and S. Bahadur, ‘’Mechanical And Tribological Properties Of Polyamide 6 And High Density Polyethylene Polyblends With And Without Compatibilizer,’’ Wear, vol. 246, pp.149158, 2000.
- [9] P. Samyn and T. M. Tuzolana, "Effect Of Test Scale On The Friction Properties Of Pure And Internal-Lubricated East Polyamides At Running-In", Polymer Testing, vol. 26, pp.660-675, 2007.
- [10] CZ Liu, J.Q. Wu, J.Q. Li, L.Q. Ren, J. Tong and R.O. Arneli, "Tribological Behaviors Of PA/UHMWPE Blend Under Dry And Lubricated Condition", Wear, vol. 260, pp.109-115, 2006.
- [11] F. Mata, P. Reis and J.P. Oavim, "Physical Cutting Model Of Polyamide Composites (PA66 GF30)", Materials Science Forum, vol. 514, pp. 643-647, 2006.
- [12] M. Bozdemir, “The Effects Of Humidity On Cast PA6G During Turning And Milling Machining”, Advances in Materials Science and Engineering, 2017.
- [13] M. Bozdemir, “Prediction Of Surface Roughness Considering Cutting Parameters And Humidity Condition İn End Milling Of Polyamide Materials”, Computational Intelligence and Neuroscience, 2018.
- [14] N. Allahverdi, Uzman Sistemler, İstanbul, Türkiye: Atlas Yayınları, 2002, ss 1-60.
- [15] O. Poyrazoğlu, M. Gülesin ve Y. Kayır, “Uzman sistem tekniklerine dayalı alışılmamış imalat yöntemlerinin tespiti”, Makine Tasarım ve İmalat Yön. Konferansı, Ankara, Türkiye, 1997, ss.80-89.
- [16] E. Turban, Decision support and expert systems, N.York, USA: Macmillan Publushing Company, 1990, ss 20-60.
- [17] M. Bozdemir and F. Mendi, "The Knowledge Management System Architecture For Artificial Intelligent Aided Systematic Design", Journal of The Faculty of Engineering and Architecture of Gazi University, vol. 20, no. 2, pp.267-274, 2005.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | March 30, 2019 |
| Published in Issue | Year 2019 Cilt:7 Sayı:2 (2019) (Özel Sayı) |
