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Hossein Ghorbani-Menghari,Parviz Kahhal,Jaebong Jung,Majid Mohammadhosseinzadeh,Young Hoon Moon,Ji Hoon Kim 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.6
Achieving sharp corners without defects such as thinning and fractures is a primary objective in the manufacturing of double-stepped tubes. Therefore, selecting the optimal tube hydroforming (THF) process is crucial for improving the formability when manufacturing complex components. In this study, experimental and numerical study was conducted to analyze the radius of the corner and the thickness of the sample in the hydroforming process for double-stepped tubes. The pressure, axial feed, and friction coefficient were considered as input parameters, while the thinning ratio and corner filling were considered as output responses. The optimal hydroforming parameter combination for the corner filling ratio and the minimum thinning ratio was determined based on artificial neural networks. The values of the process parameters obtained from the finite element (FE) simulation and the artificial neural network (ANN) have a good correlation. The proposed method combining FE model and ANN is a precious tool for designing the THF process. Based on the results, it was confirmed that the feed rate has significant influence on the thinning ratio and corner filling.