Monel 400 Nikel Esaslı Süper Alaşımın Tornalanmasında Oluşan Kesme Kuvveti Bileşenlerinin Değerlendirilmesi ve Yapay Sinir Ağları ile Modellenmesi

Year 2023, , 252 - 265, 31.12.2023

Barış Özlü , Levent Uğur

https://doi.org/10.54365/adyumbd.1340057

Cited By: 1

Abstract

Yapılan çalışma iki bölümden oluşmaktadır. Birinci Bölüm, Monel 400 alaşımının farklı kesme parametrelerinde tornalanması sonucu kesme parametrelerinin kesme kuvveti bileşenlerine ve esas kesme kuvvetine etkileri değerlendirilmiştir. İkinci bölüm ise farklı kesme parametrelerinde yapılan tornalama deneylerinde ölçülen kesme kuvveti bileşenlerinin Yapay Sinir Ağları (YSA) yöntemiyle tahmininden oluşmaktadır. Çalışmada kesme parametresi olarak üç farklı kesme hızı (60-85-110 m/dak), üç farklı ilerleme miktarı (0,05-0,07-0,09 mm/dev) ve üç farklı kesme derinliği (0,4-0,8-1,2 mm) seçilmiştir. Kesme kuvveti bileşenlerinin (Fz, Fx ve Fy) ölçümü A KISTLER 9257 B tipi piezoelektrik dinamometre ile gerçekleştirilmiştir. Kesme kuvveti bileşenlerinin tahmininde YSA yöntemi kullanılmıştır. Sonuç olarak, Monel 400 alaşımının tornalanmasında en düşük kesme kuvveti bileşenleri 0,4 mm kesme derinliğinde, 110 m/dak kesme hızında ve 0,05 mm/dev ilerleme miktarında Fz:227,48 N, Fy:154 N ve Fx:99,16 N ölçülmüştür. YSA yöntemini ile tahmin edilen kesme kuvveti bileşenleri ile deneysel sonuçlar incelendiğinde YSA yöntemini ile yapılan tahminlerin yüksek doğruluk içerdiği görülmüştür.

Keywords

Tornalama, Monel 400 Alaşımı, Kesme Kuvveti Bileşenleri, Yapay Sinir Ağı.

Evaluation of Cutting Force Components in Turning of Monel 400 Nickel Based Superalloy and Modeling with Artificial Neural Networks

Abstract

The study consists of two parts. The first part evaluates the effects of cutting parameters on the cutting force components and the actual cutting force as a result of turning Monel 400 alloy at different cutting parameters. The second part consists of the prediction of the cutting force components measured in turning tests at different cutting parameters by Artificial Neural Networks (ANN) method. Three different cutting speeds (60-85-110 m/min), three different feed rates (0.05-0.07-0.09 mm/rev) and three different depths of cut (0.4-0.8-1.2 mm) were selected as cutting parameters. The measurement of the cutting force components (Fz, Fx and Fy) was carried out with a KISTLER 9257 type B piezoelectric dynamometer. ANN method was used to predict the shear force components. As a result, the lowest cutting force components Fz:227.48 N, Fy:154 N and Fx:99.16 N were measured at 0.4 mm depth of cut, 110 m/min cutting speed and 0.05 mm/rev feed rate for turning Monel 400 alloy. When the cutting force components predicted by ANN method and experimental results are analyzed, it is seen that the predictions made by ANN method have high accuracy.

Keywords

Turning, Monel 400 Alloy, Cutting Force Components, Artificial Neural Network

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