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    Extrusion load prediction of gear-like profile for different die geometries using ANN and FEM with experimental verification
    (Springer London Ltd, 2015) Bingol, Sedat; Ayer, Onder; Altinbalik, Tahir
    This paper deals with the extrusion of gear-like profiles and uses of finite element method (FEM) and artificial neural network (ANN) to predict the extrusion load. In the study, gear-like components has been manufactured by forward extrusion for the AA1070 aluminum alloy and the process was simulated by using a DEFORM-3D software package to establish a database in order to provide the data for ANN modeling. Serious experiments were performed for only one die set and four teeth gear profile to obtain data for comparing with DEFORM-3D results. After verifying a highly appropriate FEM simulation with the experiment at the same conditions, Results were enhanced for different die lengths, extrusion ratios, and two extra teeth number as three and six using FEM simulations. Subsequently, the data from the performed FEM simulations were submitted for the best obtained ANN model. Finally, a good agreement between FE-simulated and ANN-predicted results was obtained. The proposed ANN model is found to be useful in predicting the forming load of the different die set variations based on the reliable test data.
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    Fatigue life modeling of gear like products using ANN
    (Natl Inst Science Communication-Niscair, 2016) Ayer, Onder; Bingol, Sedat; Altinbalik, Tahir; Kilicgedik, Hidir Yanki
    The expected life of a gear is important parameter especially for the gears to secure of the mechanics of it. Related to this importance, fatigue failure is one of the most seen failures occurred on gears working under cyclic loads. It is not possible to eliminate fatigue failure effects but it is possible to reduce by appropriate materials selection and design criteria. Due to demand for gears with higher load-carrying capacity and increased fatigue life, it is important to determine the fatigue strengths of the gears. hi this study, forward extrusion method with cosine and tapered profile dies is carried out to obtain gear-like products. The products are then tested under cyclic loads to determine the fatigue life. The results obtained from the experiments are used as inputs in developing the ANN models. Different ANN models are developed for cosine curved and straight tapered profiles to obtain the best models. A comparative analysis is performed in order to evaluate the accuracy of the developed models, in terms of statistical measurements (R-2, MSE, MAE). Results revealed that proposed ANN models for both cosine curved and tapered profiles are able to predict the fatigue life of the gear-like profiles.