• Transactions of Materials Processing
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• v.21 no.8
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• pp.479-484
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• 2012

The objective of this study is to compensate the elastic recovery in the flexible forming process using the predictive models. The target shape was limited to two-dimensional shape having only one curvature radius in the longitudinal-direction. In order to predict the shape error the regression and neural network models were established based on the finite element (FE) simulations. A series of simulations were conducted considering input variables such as the elastic pad thickness, the thickness of plate, and the objective curvature radius. Then, at sampling points in the longitudinal-direction, the shape errors between formed and objective shapes could be calculated from the FE simulations as an output variable. These shape errors were expressed to a representative error value by the root mean square error (RMSE). To obtain the correct objective shape the die shape was adjusted by the closed-loop using the neural network model since the neural network model shows a higher capability of estimating the shape error than the regression model. Finally the experimental result shows that the formed shape almost agreed with the objective shape.

• Transactions of Materials Processing
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• v.17 no.4
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• pp.272-277
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• 2008

A constitutive equation of the electrical steel strip used for a raw material of transformer is proposed. The stress-strain behavior of electrical steel strip is quite different from that of common carbon steel and/or alloy steel. A series of tensile tests were performed with the specimens made from cold rolled strip. Several thicknesses of the strip were produced by a two-high (with upper and lower rolls) cold rolling pilot mill as reduction ratio increases from 10% to 90%. Its initial thickness of the strip was 2.5mm. Tensile specimens are cut out from the cold rolled strips. Mechanical properties of the steel are examined through rolling direction. Ramberg-Osgood model and the proposed equation are combined to describe the total behavior of stress-strain including instability region. The stress-strain curves calculated from the present constitutive equation are compared with those from experimentally obtained at each test condition of reduction ratios of specimen. Results show that the predicted stress-strain curves are in overall in a good agreement with measured ones.

• Transactions of Materials Processing
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• v.17 no.4
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• pp.249-256
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• 2008

Combined phase transformation and heat transfer was considered on the simulation of hot press forming process, using material properties modeler, $JMatPro^{(R)}$ and a finite element package, $DEFORM^{TM}$-HT. In order to obtain high temperature mechanical properties and flow curves for different phases, a material properties modeler, $JMatPro^{(R)}$ was used, avoiding expensive and extensive high temperature materials tests. The results successfully show that the strength of hot press forming parts may exhibit different strength in the same parts, depending on the contact of blank with tooling. It was also shown effectively that the strength of the parts can be controlled by designing appropriate cooling paths and coolants. This was shown in terms of different heat convection coefficient in the calculation. Overall, current combination of software was shown to be an effective tool for the tool and process design of hot forming process, although the material modeler needs to be additionally verified by an appropriate set of high temperature materials test.

• Transactions of Materials Processing
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• v.26 no.6
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• pp.341-347
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• 2017

Flexibly-reconfigurable roll forming (FRRF) is a novel sheet metal forming technology conducive to produce multi-curvature surfaces by controlling strain distribution along longitudinal direction. Reconfigurable rollers could be arranged to implement a kind of punch die set. By utilizing these reconfigurable rollers, desired curved surface can be formed. In FRRF process, three-dimensional surface is formed from two-dimensional curve. Thus, it is difficult to predict the forming result. In this study, a regression analysis was suggested to construct a predictive model for a longitudinal curvature of FRRF process. To facilitate investigation, input parameters affecting the longitudinal curvature of FRRF were determined as maximum compression value, curvature radius in the transverse direction, and initial blank width. Three-factor three-level full factorial experimental design was utilized and 27 experiments using FRRF apparatus were performed to obtain sample data of the regression model. Regression analysis was carried out using experimental results as sample data. The model used for regression analysis was a quadratic nonlinear regression model. Determination factor and root mean square root error were calculated to confirm the conformity of this model. Through goodness of fit test, this regression predictive model was verified.

• Transactions of Materials Processing
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• v.29 no.5
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• pp.272-281
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• 2020

As the thickness of mobile communication devices is getting thinner, the size of the internal parts is also getting smaller. Among them, the battery case requires a high-level deep drawing technique because it has a rectangular shape with a large aspect ratio. In this study, the initial blank shape was optimized to minimize earing in a multi-stage deep drawing process using an artificial neural network(ANN). There has been no reported case of applying artificial neural network technology to the initial blank optimal design for a square case with large aspect ratio. The training data for ANN were obtained though simulation, and the model reliability was verified by performing comparative study with regression model using random sample test and goodness-of-fit test. Finally, the optimal design of the initial blank shape was performed through the verified ANN model.

• Transactions of Materials Processing
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• v.29 no.5
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• pp.282-289
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• 2020

Flexible roll forming is an advanced sheet-metal-forming process that allows the production of parts with various cross-sections. During the flexible process, material is subjected to three-dimensional deformation such as transverse bending, inhomogeneous elongations, or contraction. Because of the effects of process variables on the quality of the roll-formed products, the approaches used to investigate the roll-forming process have been largely dependent on experience and trial- and-error methods. Web-warping is one of the major shape defects encountered in flexible roll forming. In this study, an SVR model was developed to predict the web-warping during the flexible roll forming process. In the development of the SVR model, three process parameters, namely the forming-roll speed condition, leveling-roll height, and bend angle were considered as the model inputs, and the web-warping height was used as the response variable for three blank shapes; rectangular, concave, and convex shape. MATLAB software was used to train the SVR model and optimize three hyperparameters (λ, ε, and γ). To evaluate the SVR model performance, the statistical analysis was carried out based on the three indicators: the root-mean-square error, mean absolute error, and relative root-mean-square error.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.381-383
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• 2005

This paper is concerned with the prediction of micro structural changes of Al alloys during cryogenic rolling using an Eulerian finite element analysis. The main objective of cryogenic rolling is to obtain ultra-fine grains by severe plastic deformation at the extremely low temperature. Thereby, this simulation focuses on micro structural developments - the texture development and the changes in the size and shape of grains. The former one may be modeled using a crystal plasticity theory while the other can be predicted by a streamline technique. Applications to three pass rolling are given.

• Transactions of Materials Processing
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• v.19 no.4
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• pp.224-229
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• 2010

During the multi-pass wire drawing process, wires suffer a great amount of plastic deformation that is through the cross-section. This generates tensile residual stress at surface of drawn wires. The generated residual stress on surface is one of the problems for quality of wires so that prediction and reduction of residual stresses is important to avoid unexpected fracture. Therefore, in this study, the effect of process variables such as semi-die angle, bearing length and reduction ratio on the residual stress was evaluated through Finite Element Analysis. Based on the results of the Analysis, a prediction model was established for predicting residual stress on the surface of high carbon steel(AISI1072, AISI1082). To identify the effectiveness of the proposed model, X-ray diffraction is used to measure the residual stresses on the surface. As the result of the comparison between calculated residual stresses and measured residual stresses, the model could be used to predict residual stresses in cold drawn wire.

• Transactions of Materials Processing
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• v.16 no.4 s.94
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• pp.250-253
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them.

• Transactions of Materials Processing
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• v.26 no.5
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• pp.286-292
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• 2017

Magnesium alloy shows strong anisotropy and asymmetric behavior in tension and compression curve, especially at room temperature. These characteristics limit the application of finite element method (FEM) which is based on conventional continuum mechanics. To accurately predict the material behavior of magnesium alloy at microstructural level, a methodology of fully coupled multiscale simulation is presented and a crystal plasticity model as a constitutive equation in the simulation of metal forming process is introduced in this study. The existing constitutive equation for rigid plastic FEM is modified to accommodate deviatoric stress component and its derivatives with respect to strain rate components. Viscoplastic self-consistent (VPSC) polycrystal model was selected as a constitutive model because it was regarded as the most robust model compared to Taylor model or Sachs model. Stiffness matrix and load vector were derived based on the new approach and implemented into $DEFORM^{TM}-3D$ via a user subroutine handling stiffness matrix at an elemental level. The application to extrusion and rolling process of pure magnesium is presented in this study to assess the validity of the proposed multiscale process.