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Inconel 625 Alaşımının Frezelenmesinde Takım Aşınmasının Sonlu Elemanlar Yöntemiyle Modellenmesi ve Optimizasyonu

Bu çalışma, PVD AlTiN ve CVD TiCN/Al2O3/TiN kaplı karbür uçlar kullanılarak Inconel 625 süper alaşımının frezelenmesinde kesme parametrelerinin optimizasyonuna ve yanak aşınmasının sayısal analizine odaklanmaktadır. Frezeleme deneyleri Taguchi L18 dikey dizinine göre CNC dikey işleme merkezinde gerçekleştirildi.Takım aşınmasının sonlu eleman yöntemiyle modellemesi Deform 3D yazılımı kullanılarak yapıldı. Takım aşınması üzerinde frezeleme şartlarının etkilerini tanımlamak için varyans analizi kullanılmıştır. Varyans analiz sonuçları, ilerleme miktarının (%41.5 katkı oranı ile) Vb'yi etkileyen en önemli parametre olduğunu göstermiştir. Test sonuçlarını tahmin etmek için lineer ve kuadratik regresyon analizleri kullanıldı. Regresyon analizi sonuçları, kuadratik regresyon modeli ile elde edilen tahmini Vb değerlerinin lineer regresyon modeline göre daha etkili olduğunu göstermektedir. İstatistiksel sonuçlar, Taguchi yönteminin Inconel 625 alaşımının frezelenmesinde optimum kesme parametrelerinin belirlenmesinde başarılı olduğunu göstermektedir.

Optimization and finite element modelling of tool wear in milling of Inconel 625 superalloy

This study focuses on optimization of cutting conditions and numerical analysis of flank wear in milling of Inconel 625 superalloyusing PVD AlTiN and CVD TiCN/Al2O3/TiN-coated carbide inserts. The milling experiments have been performed in CNCvertical machining centre according to Taguchi L18 orthogonal array. Finite element modelling of tool wear was performed usingDeform 3D software. Analysis of variance was utilized to define the influences of the milling conditions on Vb. The results showedthat the feed rate (with 41.5% contribution rate) is the most important parameter affecting Vb. The linear and quadratic regressionanalyses were used to estimate the results of the test. The regression analysis results showed that the estimated Vb values achievedby the quadratic regression model were more effective compared to the linear regression model. Statistical results revealed that theTaguchi method was successful to define optimum cutting parameters in the milling of Inconel 625.

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