Kesme Parametrelerinin Haynes 242 Nikel Bazlı Süper Alaşım Malzemenin Tornalamasında Güç Tüketimi Üzerindeki Etkilerinin RSM ve GA ile İncelenmesi

Year 2022, Volume: 22 Issue: 5, 1204 - 1213, 27.10.2022

Hakan Kazan Engin Ufuk Ergül

https://doi.org/10.35414/akufemubid.1103662

Cited By: 1

Abstract

Talaşlı imalatta yaygın kullanımı nedeniyle tornalama işleminde güç tüketimini azaltmak sürdürülebilir bir üretim süreci için kilit faktörlerden biridir. Nikel bazlı süper alaşımlar, üstün mekanik özelliklerinden nedeniyle endüstride sıklıkla tercih edilirler. Bu çalışmanın amacı işlem parametrelerinin Haynes 242 nikel bazlı süper alaşım malzemenin tornalanmasında güç tüketimi üzerine etkilerinin incelenmesidir. Bu kapsamda, yanıt yüzeyi yöntemi (Response Surface Method-RSM) ile birleştirilen üç seviye Box-Behnken tasarımı ve genetik algoritma (GA) uygulanarak minimum güç tüketiminin tahmin edilmesinde kullanılan optimum parametre değerlerini belirlemek için regresyon modeli oluşturulmuştur. İlk olarak 3 farklı seviyedeki takım uç radüsü (0.4,0.6 ve 0.8 mm), talaş derinliği (0.2,0.4 ve 0.6 mm), ve ilerleme oranı (0.1,0.2 ve 0.3 mm/rev.) dikkate alınarak Box-Behnken deney tasarımı oluşturulmuştur. Ardından, elde edilen deney setlerine göre AdvantEdge™ vasıtasıyla her bir deney setine ait güç tüketimleri ölçülmüştür. Sonrasında, RSM’den elde edilen matematiksel tahmin modelinden yararlanılarak güç tüketimi tahmini için GA kullanılmıştır. Sonuç olarak, bu yöntemlerle bulunan tahmin değerleri karşılaştırılmış ve birbirlerine çok yakın oldukları görülmüştür. Hem istatistiksel hem de simülasyon programı sonuçları, güç tüketimini minimize etmek için düşük ilerleme oranı ve talaş derinliğine ihtiyaç duyulduğunu göstermektedir.

Keywords

Tornalama, Nikel Esaslı Süperalaşım, RSM, Box Behnken, Genetik Algoritma, Güç Tüketimi

Investigation the Effects of Cutting Parameters on Power Consumption in Turning of Haynes 242 Nickel-Based Super Alloy by RSM and GA

Abstract

Due to its widespread use in machining, reducing power consumption in the turning process is one of the key factors for a sustainable production process. Nickel-based superalloys are preferred in variable applications due to their superior mechanical properties. This study aims to investigate the effects of process parameters on power consumption in turning of Haynes 242 nickel-based superalloy. In this context, three levels of Box-Behnken design combined with the Response Surface Method (RSM) and genetic algorithm (GA) were applied to find the optimum parameter values used in the estimation of the minimum power consumption to create the regression model. First, the Box-Behnken experimental design was created based on 3 different levels of tool nose radius (0.4,0.6 and 0.8 mm), depth of cut (0.2,0.4 and 0.6 mm), and feed rate (0.1,0.2 and 0.3 mm/rev.). Then, the power consumption of each test measured by AdvantEdge™ based on the obtained experimental sets. Then, GA was used for power consumption estimation by utilizing the mathematical estimation model obtained from RSM. Finally, the estimated values obtained by both methods were compared. Both statistical and simulation results show that low feed rate and depth of cut are needed to minimize power consumption.

Keywords

Turning, Nickel-Based Superalloy, RSM, Box Behnken, Genetic Algorithm, Power Consumption

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