TY - JOUR T1 - Investigation of material models on deep drawing and ironing processes TT - Derin çekme ve ütüleme proseslerinde malzeme modellerinin incelenmesi AU - Kaplan, Cihangir AU - Güleç, Cem AU - Arıkoğlu, Mesut AU - Toros, Serkan AU - Korkmaz, Habip Gökay PY - 2022 DA - April Y2 - 2022 DO - 10.28948/ngumuh.1034351 JF - Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi JO - NÖHÜ Müh. Bilim. Derg. PB - Nigde Omer Halisdemir University WT - DergiPark SN - 2564-6605 SP - 387 EP - 392 VL - 11 IS - 2 LA - en AB - Within the scope of this study, the effects of yield and hardening criteria used in forming simulations on part geometric dimensions were investigated. As material 0.8 mm thick DC04 material is used. In the study, the results were compared using the Hill-48 and Barlat-91 yield criteria and experimental flow curve, Hockett-Sherby, Ludwig and Hollomon flow curve models. The studies were carried out in Simufact Sheet Metal Form software. Although all the models studied because of dimensional evaluations estimated within tolerance values, the model in which the experimental data were used with Hill-48 gave the closest results to the nominal dimensions. KW - Sheet Metal Forming KW - Yield Criteria KW - Deep Drawing KW - Ironing N2 - Bu çalışma kapsamında, şekillendirme simülasyonlarında kullanılan akma ve pekleşme kriterlerinin parça geometrik boyutlarına etkisi incelenmiştir. Malzeme olarak 0.8 mm kalınlığındaki DC04 malzemesi kullanılmıştır. Çalışmada Hill-48 ve Barlat-91 akma kriterleri ile deneysel akma eğrisi, Hockett-Sherby, Ludwig ve Hollomon akma eğrisi modelleri kullanılarak sonuçlar karşılaştırılmıştır. Çalışmalar Simufact Sheet Metal Form yazılımda gerçekleştirilmiştir. Boyutsal değerlendirmeler neticesinde çalışılan bütün modeller her ne kadar tolerans değerleri içerisinde tahmin etmiş olsa da deneysel verilerinin Hill-48 ile kullanıldığı model nominal boyutlara en yakın sonuçları vermiştir. CR - V. L. Hattalli and S. R. Srivatsa, Sheet metal forming processes–recent technological advances, Materials Today: Proceedings, 5, 2564-2574, 2018. https://doi.org/10.1016/j.matpr.2017.11.040 CR - Y. Jia, Y. Qiao, H. Pan, E. Chu, and Y. Bai, A Comprehensive plasticity and fracture model for metal sheets under multi-axial stress and non-linear strain path, SAE International Journal of Engines, 10, 266-273, 2017. https://doi:10.4271/2017-01-0315 CR - H. Zeng, Z. Huang, T. Wang, H. Sun, and L. Wang, Optimal design and forming analysis of the stamping process for front wall of automobile considering springback compensation technology, SAE Technical Paper, 0148-7191, 2021. https://doi.org/10.4271/2021-01-0269 CR - Z. Wang, T. Hakoyama, Y. Endo, and K. Osakada, Application of flow model in metal cutting to cold forging of tubular products, CIRP Annals, 68, 273-276, 2019. https://doi.org/10.1016/j.cirp.2019.04.033 CR - K. Zhao, L. Wang, Y. Chang, and J. Yan, Identification of post-necking stress–strain curve for sheet metals by inverse method, Mechanics of Materials, 92, 107-118, 2016. https://doi.org/10.1016/j.mechmat.2015.09.004 CR - I. Mirandola, G. A. Berti, R. Caracciolo, S. Lee, N. Kim, and L. Quagliato, Machine learning-based models for the estimation of the energy consumption in metal forming processes, Metals, 11, 833, 2021. https://doi.org/10.3390/met11050833 CR - Q.-F. Zhang, Z.-Y. Cai, Y. Zhang, and M.-Z. Li, Springback compensation method for doubly curved plate in multi-point forming, Materials & Design, 47, 377-385, 2013. https://doi.org/10.1016/j.matdes.2012. 12.005 CR - J. Abu Qudeiri, A. Ziout, M. Alsayyed, A. Alzarooni, F. Safieh, A. Al Hatti, et al., Simulation study of deep drawing process, in Materials Science Forum, 2020, 139-147. https://doi.org/10.4028/www.scientific.net/ MSF.977.139 CR - S. Tatipala, J. Pilthammar, M. Sigvant, J. Wall, and C. M. Johansson, Introductory study of sheet metal forming simulations to evaluate process robustness, in IOP Conference Series: Materials Science and Engineering, 2018, 012111. https://doi:10.1088/1757-899X/418/1/012111 CR - A. Zabala, E. S. de Argandoña, D. Cañizares, I. Llavori, N. Otegi, and J. Mendiguren, Numerical study of advanced friction modelling for sheet metal forming: Influence of the die local roughness, Tribology International, 165, 107259, 2022. https://doi.org/10.1016/j.triboint.2021.107259 CR - M. Ramezani and Z. Ripin, Introduction to sheet metal forming processes, Rubber-Pad Forming Processes—Technology and Applications, Elsevier, Amsterdam, 1-22, 2012. CR - Y. Qin, W. A. W. Nawang, and J. Zhao, Forming of micro sheet-metal components, in Micromanufacturing Engineering and Technology, ed, 2015, 299-322. https://doi.org/10.1016/B978-0-323-31149-6.00013-X CR - O. Çavuşoğlu, S. Toros, H. Gürün, and A. Güral, Warm deformation and fracture behaviour of DP1000 advanced high strength steel, Ironmaking & Steelmaking, 45, 618-625, 2018. https://doi.org/10. 1080/03019233.2017.1309168 CR - J. Lian, F. Shen, X. Jia, D.-C. Ahn, D.-C. Chae, S. Münstermann, et al., An evolving non-associated Hill48 plasticity model accounting for anisotropic hardening and r-value evolution and its application to forming limit prediction, International Journal of Solids and Structures, 151, 20-44, 2018. https://doi.org/10.1016/j.ijsolstr.2017.04.007 CR - D. Banabic, Sheet metal forming processes: constitutive modelling and numerical simulation: Springer Science & Business Media, 2010. CR - B. Şener, T. A. Akşen, and M. Fırat, On the effect of through-thickness integration for the blank thickness and ear formation in cup drawing FE analysis, European Mechanical Science, 5, 51-55, 2021. https://doi.org/10.26701/ems.781175 UR - https://doi.org/10.28948/ngumuh.1034351 L1 - https://dergipark.org.tr/en/download/article-file/2122669 ER -