Ayer, Onder2024-06-122024-06-1220171330-36511848-6339https://doi.org/10.17559/TV-20160130154750https://hdl.handle.net/20.500.14551/18763Forming of disc samples composed from aluminium and copper in performed study was examined with upsetting procedure. An approach for prediction deformation load of upsetting processes is developed. This study combines the finite element method model, neural network model and upper bound method to simulate and predict the deformation load in upsetting of bimetallic materials. The Finite Element Method (FEM) results were obtained from DEFORM-3D software and they were compared and validated with experiments by taking forming load into consideration. Also, Artificial Neural Network (ANN) model was used to analyze and predict the forming load for different process parameters. The Upper Bound (UB) model was also proposed to estimate the forming load and the results were compared with experiments. It was understood that calculated results were in concordance with experimental results in upsetting of bimetallic hollow discs. Thus, proposed ANN, FEM and UB models provide a valuable insight into the parameters affecting forming load and can be named as useful tools to predict the forming load without the need of any experiments.en10.17559/TV-20160130154750info:eu-repo/semantics/openAccessArtificial Neural Network (ANN)Bimetallic MaterialsDEFORM-3DFinite Element Method (FEM)Load AnalysisUpper Bound Method (UB)UpsettingRing Compression TestUpper-Bound MethodNeural-NetworkElement-AnalysisTaguchi MethodExtrusionBilletsFemOptimizationWorkabilityArticle24616791688Q4WOS:0004171217000062-s2.0-85036668674Q3