The purpose of this paper is to obtain a model that quickly predicts springback in the three-point bending process of steel / PUR / steel sandwich panels. Firstly, based on the finite element simulation, the springback behavior for different punch radius, length between supports, and foam thickness is established. The results obtained by the finite element analysis show a satisfactory agreement with the experimental results. Secondly, three machine learning approaches are applied, including linear regression (LR), artificial neural network (ANN), and support vector machine (SVM) in order to predict the springback of sandwich panels in the three-point bending process. The performance of these approaches is investigated by using some statistical tools like mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The obtained results show that the ANN approach is the best model for predicting the springback of sandwich panels when considering accuracy.

Cold roll forming is a sheet metal forming process in whichthe bending occurs gradually in several forming steps from an undeformed strip to a finishedprofile. Althoughsimple appearance, the process is influenced by several parametersthat complicate the process design and control such as springback.The main purpose in this article is to determine a simple criterion for the springback and to introduce a fast solution to obtain it and therefore artificial neural network was proposed for achiving this goal. Cold roll forming of a channel section in the first station was simulated by a commercial package named “Msc Marc Mentat”. The data obtained from the finite element simulations were used as training and testingsetsfor neural networks. Perfect performance of neural network was proved when the neural network outputs were compared with the testing set that did not exist in the training set.

Spingback is one of the important factors in metal forming process. Study on springback shows that this phenomenon can have great impacts on shape and formation of the part. Therefore, to increase the accuracy and the quality of the produced part, the important factors have to be recognized. In this paper, machining forming for thin part which is a combination of machining and incremental forming is first introduced.Then numerical and experimental results are compared. The effects of forming parameters such as tool diameter, part angle, forming steps, and tool position on springback are presented. The results show that the step depth has a great affect on springback.

Springback is one of the key factors to influence the quality of drawn sheet metal parts in deep drawing process. Previous investigations about the springback have shown that, the amount of work-piece deformation can be affected by this phenomenon in the deep drawing process.Therefore, to optimise this manufacturing process and to increase the dimensional accuracy of the parts, it is essential to find out the effective parameters and bring the deep drawing process under producer control. In this paper, the finite element analysis of springback was applied and the effects of many physical parameters on the springback such as, type of materials, blankholder force, coefficient of friction and tool clearance were studied. Then, it was proposed how to decrease the effect of springback for different materials. For simplicity, two dimensional analyses (plane-strain simulation) were performed and the results were compared with experimental data. A good agreement was found between numerical and experimental results.

The technique of Sheet Stamping by Deformable Forming Tools (SSDFT) has been recognized as a promising alternative to control the springback of sheet blanks. This paper deals with the springback of elastic-plastic circular plates on deformable dies subjected to transverse external forces. Different significant parameters are examined within the framework of the present investigation. For instance, the influence of the friction coefficient between the workpiece and elastomer on the equivalent plastic strain and, therefore, on the springback, for different boundary conditions, are investigated in detail. Moreover, the effects of the thickness of the workpiece on the springback, for both deformable and conventional dies, are discussed.    

The most prominent feature of sheet material forming process is an elastic recovery phenomenon during unloading which leads to springback and side wall curl. Therefore evaluation of springback and side wall curl is mandatory for production of precise products. In this paper, the effects of some parameters such as friction coefficient, sheet thickness, yield strength of sheet and blank-holder force on the springback and side wall curl in U-bending of DP600 steel alloy sheet has been investigated. The investigations have been done by computer simulation. In the simulations the ABAQUS finite element software has been used and the results compared to experimental ones. The finite element results have been validated from experimental results. After validation of FEM simulation via experimental results a powerful, rapid and efficient tool was introduced for investigating some important aspects and parameters of U-bending process such as blank-holder force, sheet thickness, yield strength of sheet and friction coefficient. MINITAB, a statistical software, was used to analyze finite element results. With the use of MINITAB, equations for prediction of springback and side wall curl radius by friction coefficient, sheet thickness, yield strength and blank-holder force were obtained.

Finite Element method (FEM) is becoming an important modeling tool in sheet metal forming industry. The knowledge of the sheet metals" springback after forming is necessary to control the manufacturing process. This paper deals with the springback and side-wall curl in 2-D draw bending. An anisotropy property for material is considered. A general finite element code "ELFEN" has been applied for numerical simulation. The modeling of problem is performed by the explicit method for loading stage and the combination of the implicit and explicit method for unloading stage. Different significant parameters are examined within the framework of the present investigation. For instance, the influences of the blankhoder force and friction coefficient are investigated in detail.

At the bending process, sheet deforms plastically between tool and die to take its final shape. Deviation of final bending angle from intended angle after removing load is the most important defect which occurs in sheet metal forming processes. This phenomenon which is called springback, occurs because of elastic behavior of sheet after unloading. In order to increasing geometrical accuracy of products, the bending parameters should be chosen in such a way that the intended bending angle be obtained after unloading. In the recent years, due to fuel crisis; aerospace and automotive industries trends to use lightweight materials to decrease fuel consumption. Fiber Metal Laminates are attractive materials for industries due to their suitable specifications such as high strength to weight ratio, low cost, high chemical resistance and high acoustic and vibration damping. In the present study, the springback behavior of Fiber metal laminates has been investigated by using theoretical and experimental procedures. The results of this study shows that the developed theoretical model can predict springback with mean error of 17%.

The most prominent feature of sheet material forming process is an elastic recovery phenomenon during unloading which leads to springback. Therefore, evaluation of springback is mandatory for production of precise products. In this paper, the effects of temperature, friction coefficient, blank-holder force and sheet thickness on the springback of AL5083-H111 alloy sheet in warm U-bending conditions were investigated by performing experimental tests and numerical method. ABAQUS FEA software was used for numerical simulation. Finally, comparison of experimental and numerical results showed good agreement.