Accurate Springback Prediction Research Articles

Analytical Model for Springback Prediction of CuZn20 Foil Considering Size Effects: Weakening versus Strengthening.

The prediction of springback angle for ultra-thin metallic sheets becomes extremely difficult with the existence of size effects. In this study, size effects on the springback behavior of CuZn20 foils are investigated by experiments and analytical methods. The experimental results reveal that the springback angle first decreases gradually and then increases markedly with the decrease of foil thickness, which cannot be analyzed by current theoretical models. Then, an analytical model based on the Taylor-based nonlocal theory of plasticity is developed, in which the drastic increases of both the proportion of surface grains and the strain gradient are taken into account. Moreover, the influence of strain gradient is modified by the grain-boundary blocking factor. The calculation results show that the springback angle of foils is determined by the intrinsic competition between the decrement angle caused by surface grains and the increment angle caused by the strain gradient. Besides, the relative error of predicted springback angle by the model is less than 15%, which means that the developed model is very useful for improving the quality of micro sheet parts with high accuracy of springback prediction.

Comparative Investigation on Aluminum Material Modeling with applications to Springback Prediction

A comparative investigation on springback prediction of aluminum stampings has been completed using an industry-type “shotgun” die as the benchmark case. 5xxx aluminum alloy at a thickness of 1.5 mm was used for the shotgun die tryout. After stamping tryout, the formed panel was scanned to capture its sprung geometry. The studied aluminum alloy was characterized by means of uniaxial tensile test and hydraulic bulge test to determine the material isotropic hardening behavior and planar anisotropy. In order to determine the material kinematic hardening behavior, the exclusive Yoshida model fitting test was conducted in tension-compression (T-C) and compression-tension (C-T) loading modes with the one-cycle and three-cycle loading schemes. The shotgun benchmark case was simulated using FEA software LS-DYNA®. By comparing the simulation results with the tryout measurements, the accuracy of springback prediction was examined to evaluate the influence of material modeling, loading mode and loading cycle in the Yoshida model fitting test. Based on the current benchmark study, the best practice in springback prediction and compensation of aluminum stampings and in conducting the Yoshida model fitting test of aluminum alloys were summarized for industrial applications.

Experimental and numerical prediction and comprehensive compensation of springback in cold roll forming of UHSS

Ultra-high-strength steels (UHSS), for instance, dual phase (DP) and martensitic steels, get growing challenges in strip metal forming processes of car industry manufacturing to achieve lightweight and improve passenger security. Predict and compensate for springback is still a major problems to be solved in cold roll forming (CRF) for complex section materials. In this study, the springback performance UHSS in cold roll forming is discussed by simulation and experimental methods. At the same time, one 3D FEA model was established to analyze the CRF process by COPPA RF and MSC MARC, in which planar swift’s model, anisotropic Hill’s 48 model, and Yid2000-2d model in the company with Yoshida-Uemori kinematic hardening pattern were investigated. Automobile threshold section CRF experiment and springback evaluation carried out through the comparison of numerical results. Considering Yoshida-Uemori kinematic hardening, the anisotropic Yid2000-2d model improves the springback prediction accuracy in CRF car threshold section in comparison with other models. The improved model is used to compensate the springback of product. A new method is proposed, which takes into account angle overbending compensation (AOC), small radius compensation (SRC), and revere-bending compensation (RBC) based on roll shape design. The method, which we call “USTB-Durable Integration of Springback Control (UDI),” is general for it considers the fact radius and angle would occur during springback. Compared with the AOC, SRC, and RBC method, the new method has higher precision especially for the springback compensation of ultra-high-strength complex section in CRF. The researchers are expected to conduct design engineer to calculate and compensate the springback trend before applying roller design to actual production.

Utilization of Advanced Computational Methods to Predict Spring-back of Aluminium Alloys in Automotive Industry

The automotive industry is one of the most dynamically developing segments of the industrial production worldwide. The introduction of still increasingly stringent emission limits for newly developed cars forces car producers to still reduce the fuel consumption of cars. One option is to use hybrid drive units in combination with a redesign of the automobile body while maintaining the highest possible level of vehicle safety. For these reasons, the automotive industry has been increasingly demanding to apply and process low density (lightweight) alloys, including aluminium-based alloys. These materials are subject to high demands both in terms of mechanical properties and technological workability in the mass production process. The utilization of mathematical modelling (numerical simulations) of production processes is now one of the standards in all phases of design and production the car-body and allows the implementation of variable designs in a relatively short time scale and the detection of potential production problems as well. In this paper, the influence of the kinematic hardening model on the accuracy of spring-back prediction is shown in comparison with the commonly used isotropic hardening model. For deformation analysis, a simple workpiece having ?U-shape? of EN AW 6111 material was used. Such aluminium alloys is used for production car-body panels in the automotive industry. Achieved accuracy of numerical simulation results is evaluated by the comparison shape obtained by numerical simulations and shape of experimentally bended workpiece.

Dependency of the Young's modulus to plastic strain in DP steels: A consequence of heterogeneity?

The accurate springback prediction of dual phase (DP) steels has been reported as a major challenge. It was demonstrated that this was due to the lack of understanding of their nonlinear unloading behavior and especially the dependency of their unloading moduli on the plastic prestrain. An improved compartmentalized finite element model was developed. In this model, each element was assigned a unique linear elastic J2 plastic behavior without hardening. The model's novelty lied in the fact that:(i)a statistical distribution was discretized in a deterministic way and used to assign yield stresses to structures called compartments,(ii)those compartments were randomly associated with the elements through a random compartment element mapping (CEM).Multiple CEM were simulated in parallel to investigate the intrinsic randomness of the model. The model was confronted with experimental data extracted from the literature and it was demonstrated that the model was able to reproduce the dependence of the apparent moduli on the tensile prestrain. It was also observed that the evolution of the apparent moduli was predicted even if it was not an explicit input of the experimental dataset used to identify the input parameters of the model. It was then deduced that the shape of the hardening and the dependency of moduli on the prestrain were two manifestations of a single cause: the heterogeneous yield stress in DP steels.

A method of constitutive experiment for accurate description of tube performance under rotary-draw bending

Establishing accurate constitutive relations is an important prerequisite for improving the springback prediction accuracy of rotary-draw bending of tubes. In this paper, the stress loading paths are studied for rectangular tube and composite circular tube in rotary-draw bending processes. It is found that there is reverse loading with tangential/circumferential stress for both the rectangular tube and the base/covered tube of composite circular tube. And the reverse loading is in the plastic deformation range. Two constitutive experimental schemes are designed according to the above research results: (1) The constitutive experiment is designed according to the variation of stress peak points of the tube with the bending process and the yield state of the material. The calculation method of the loading force F is given, too. (2) The displacement of the beam of the tensile tester is determined according to the corresponding strain during stress fluctuations, and an example is given to illustrate how the displacement of the beam is calculated according to the strain corresponding to each trajectory point. The calculation formula of the beam displacement during repeated loading, unloading and reverse loading is developed, too.

In-line Springback Measurement for Tube Bending Using a Laser System

Tube bending process is extensively used for many industrial fields such as the automotive, shipbuilding, and aircraft manufacturing industries. However, one limitation of the tube bending process is that it is not easy to control the springback related to elastic recovery after unloading. Since springback is affected by many influential parameters such as bending angle, radius, speed, and material properties, accurate prediction of springback can be complicated. To compensate springback, it is essential to accurately measure the released springback angle. The proposed method herein is to use a laser system to measure the springback angle in-line, without moving the workpiece from the bend die or machine. This in-line laser measurement concept can help save measurement time while potentially improving measurement accuracy. The system can be used to either instantaneously correct springback or to collect data to adjust machine settings between batches. In detail, the laser source can be installed and fixed into the tube, using the laser beam as the reference position to measure the bending angle. After releasing the clamp, the bent tube is recovered and the embedded laser system indicates the position shift on a datum board. The distance from the center of the unloaded tube to the board is set and the recovered distance is easily measured. The released springback angle can be calculated with those two parameters. In addition, the resolution of the measurement can be improved by properly adjusting the distance. In this paper, the capability of the measuring technique is demonstrated in a rotary draw bending machine using AA6xxx aluminum alloy profiles bent at different angles.

Improvement of springback prediction accuracy for Z-section profiles in four-roll bending process considering neutral layer shift

Aluminum alloy profiles are widely used as major structural components in the aerospace industry. Owing to the diverse section structures and dimensions required, roll bending for profiles with specified cross-sections has become an attractive manufacturing technology. In the present work an expanded study is carried out for springback prediction of profiles in four-roll bending process. An improved theoretical prediction model considering neutral layer shift is developed, with the aim of improving the prediction accuracy for springback of Z-section profiles. The proposed model considers the material properties, geometric characteristics and forming radii. The springback displacements of Z-section profiles for 7075-O and 7475-O aluminum alloy with different thicknesses are predicted using the model. The maximum springback prediction error of the proposed model compared with experimental results is 3.764 %, which is less than the prediction error of the empirical model (11.626 %). The springback prediction for Z-section profiles considering neutral layer shift thus provides a significant improvement in accuracy.

Various elastic moduli of AA6016 and their application on accurate prediction of springback

ABSTRACTFirst of all, the elastic modulus variation of 6016-T4 aluminum alloy has been investigated by uniaxial tensile experiments. Secondly, a new model to describe the change of elastic modulus has been proposed based on our experimental data. Then Finite Element (FE) simulations with various elastic moduli have been conducted to predict the springback of V bending. The results are shown as follows: the elastic modulus decreases, obviously, with increase of equivalent plastic strain; the proposed model is more suitable to explain our experimental data than the other models considered; and the springback prediction of V bending with various elastic moduli is more precise than with constant modulus.

Experimental Characterization and Finite Element Prediction of Large Strain Spring-Back Behavior of Poly(Methyl Methacrylate)

Abstract Spring-back of poly(methyl methacrylate) (PMMA) at large strains, various embossing temperatures, and release temperatures below glass transition is quantified through modified unconfined recovery tests. Cooling, as well as large strains, is shown to reduce the amount of spring-back. Despite reducing the amount of spring-back, these experiments show that there is still a substantial amount present that needs to be accounted for in hot embossing processes. Spring-back is predicted using finite element simulations utilizing a constitutive model for the large strain stress relaxation behavior of PMMA. The model's temperature dependence is modified to account for cooling and focuses on the glass transition temperature region. Spring-back is predicted with this model, capturing the temperature and held strain dependence. Temperature assignment of the sample is found to have the largest effect on simulation accuracy. Interestingly, despite large thermal gradients in the PMMA, a uniform temperature approximation still yields reasonably accurate spring-back predictions. These experiments and simulations fill a substantial gap in knowledge of large strain recovery of PMMA under conditions normally found in hot embossing.

Effect of constitutive model on springback prediction of MP980 and AA6022-T4

Springback simulation of stamped sheet metal components using finite element method depends on the accuracy of appropriate material models and consideration of appropriate experimental strategies. In this work, tension-compression tests with different strategies, e.g. tension-compression, compression-tension up to various strain levels and multicycle compression-tension tests were conducted to determine parameters of the Yoshida-Uemori (Y-U) nonlinear dynamic hardening model using optimization analysis software LS-OPT. Finite element simulations with LS-DYNA were performed to predict springback behavior of both the advanced high strength steel MP980 (a 980 MPa grade multiphase steel) and aluminum alloy 6022-T4, which was then compared to measurements of stamped U-channel specimens. Results suggest that although the various tension-compression testing strategies can significantly affect the determined values of Yoshida-Uemori model parameters, springback prediction accuracy with this model does not depend on the associated variation of model parameters, at least for the two-dimensional sidewall curl of a U-channel shape. For materials (e.g. MP980) exhibiting a clear Bauschinger effect but insignificant texture anisotropy, the selection of suitable yield criteria (e.g. Hill48), the consideration of elastic modulus degradation combined with the Y-U model can obviously increase the accuracy of springback prediction. In contrast, materials (e.g. AA6022-T4) that exhibit little Bauschinger effect but have significant texture anisotropy, the use of a yield criterion that accounts for anisotropy (e.g. YLD2000-2D) is more important for improving the accuracy of springback prediction.

Springback Prediction Using Finite Element Simulation Incorporated With Hardening Data Acquired From Cyclic Loading Tool

The aims of this article are to present the accuracy of springback prediction in U-bending sheet metal forming processes using finite element (FE) simulation incorporated with kinematics or mixed hardening parameters that are derived from cyclic data provided by the developed cyclic loading tool. The FE simulation results in the form of springback angles are compared with the experimental results for validation. It was found that the mixed hardening model provides better simulation results in predicting springback. This is due to the capability of the isotropic hardening part of this model to describe cyclic transient and the kinematic hardening part to improve description of the Bauschinger effect. Kinematic hardening however, on its own is capable of providing relatively good springback simulation illustrated by errors of less than 8 percent. Overall, the data provided by cyclic loading from the newly developed bending-unbending tool is considered valuable for simulating springback prediction.

Effect of coining on springback behaviour

Especially due to utilization of high strength steels in automotive parts, accurate prediction and reduction of springback have gained more importance in the recent years. One of the widely used approaches to reduce the springback in deep drawn parts especially in and around the bent regions is coining (restrike operation). In this method, the sheet material in the springback-relevant regions is compressed between two rigid tools having clearences less than the sheet thickness. By this way, compressive stresses and strains are superimposed and therefore the bending effects are reduced. During coining, plastic deformation occurs in the thickness direction. In order to predict this behavior in process planning numerical simulations should be capable of considering the effects of through-thickness compression. In order to analyze this effect, axisymmetrical deep drawing tests were performed. In a further step, the bottom surface or the radius region of the geometry was compressed between the punch and additional tools. To analyze the springback behaviour, drawn geometries were cut along the rolling direction, so that the residual stresses are released. The same procedure was also simulated with shell elements having enhanced formulation to account for through-thickness deformation. Experimental springback results show that the coining process influences the springback and this can be captured by the enhancements in the shell formulation.

Accurate prediction of springback after coining operation

A common approach used to reduce springback in flanging operations is to apply additional coining around the bent regions. In this strategy, the sheet metal part is compressed between two rigid dies having a clearance less than the sheet thickness. The aim is to bring additional compressive stresses especially around bending dominated regions. These stresses are slightly larger than the current yield stress of the material. By this way, the dominant bending stress state is reduced leading to less springback. The shell elements which are the state of the art in productive utilization of finite element simulations lack the ability to consider normal deformation which occurs during coining. Hence, it is not possible for process planners to decide on the degree of coining and to predict the springback results beforehand. In order to address this problem a set of experiments were performed, whereby deep drawn cups were coined around the punch radius region and cup bottom. To investigate the changed state of residual stresses, drawn cups were cut into halves and springback was measured. The same procedure was also simulated with the new thick shell elements which are improved to incorporate the normal stresses in thickness direction. It was seen that, by the help of this enhancement, the springback prediction is improved as compared to the conventional shell elements.

Evaluation of all Springback Aspects through a Success Story on Ford Cargo Truck Door Opening Part

Springback remains as a challenge in the automotive stamping industry. Use of different new materials for lightweighting purposes like aluminium, HSS and AHSS increase studies on that subject. Moreover, constraint timings and cost reduction targets require robust strategies on springback prediction and its compensation. In this paper, the industrial approach to this issue is told through a successful large scale case study where various applied methods are mentioned for accurate springback prediction and effective compensation.On the prediction side, this includes hardening curve, yield criteria, FLC, friction, drawbeads, spacers, blankholder model, blank properties, thickness, material grade, clamping concepts, mesh parameters. On the compensation side, strategies are playing an important role and also certainly validation. For the validation, so called, full cycle simulations are performed. Full cycle simulations must be carefully evaluated due to many noise factors.

Numerical Prediction of Forming Car Body Parts with Emphasis on Springback

Numerical simulation is an important tool which can be used for designing parts and production processes. Springback prediction, with the use of numerical simulation, is essential for the reduction of tool try-outs through the design of the forming tools with die compensation, therefore, increasing the dimensional accuracy of stamped parts and reducing manufacturing costs. In this work, numerical simulation was used for performing the springback analysis of car body stamping made of aluminium alloy AA6451-T4. The finite element analysis (FEM) based software PAM-STAMP 2G was used for performing the forming and springback simulations. These predictions were conducted with various combinations of material models to achieve accurate springback prediction results. Six types of yield functions (Barlat89, Barlat2000, Vegter-Lite, Hill90, Hill48 isotropic, and Hill48 orthotropic) were used in combination with the Voce hardening model. Springback analysis was conducted in three sections of the formed part; the numerical results were compared with the experimental values. It was found that the combinations of Barlat’s yield functions and the Voce hardening law were most accurate in terms of springback prediction. Additionally, it was found that the phenomena that were investigated, which are required for the determination of the kinematic hardening model, such as the change of Young’s modulus E, the transient behaviour, work-hardening stagnation, and permanent softening, were not observed in the aluminium alloy studied.

Prediction and reduction of springback in 3D hat shape forming of AHSS

The overall objective of the current project was to develop a FE (Finite Element) model which can reliably predict springback in a 3-dimensional hat shape forming process. In this process beside wall angle change and sidewall curl, torsion or twist is also observed. The material used in this study is 1 mm DP980 and the material properties are obtained from IFU- Stuttgart. Yoshida model, as one of the advanced material models for accurate springback prediction, is used. A new approach called “inverse analysis” is also involved to evaluate the accuracy of springback prediction. Results show that the Yoshida model improves the springback prediction in terms of sidewall curl and wall angle change when 300 kN blank holder force is used. However, when applying higher blank holder forces (1500 kN in this case), simulation results with Hill48 and isotropic hardening are closer to experimental results. Inverse analysis can improve the simulation results in general. However, using the E-modulus which can provide accurate wall angle change does not improve the prediction of sidewall curl. Thus, in case of 3-dimensional U stretch-bending process, a constant average E-modulus is not appropriate to predict all three springback phenomena, i.e. wall angle change, sidewall curl, and twist. In agreement with literature, it is shown that additional stretching on the part can reduce springback. Also, simulations showed that using variable blank holder force, in the range considered in this study (from 300 to 1500kN), did not significantly reduce sidewall curl and wall angle change but it significantly reduced twist.

Effect of Constitutive Equations on Springback Prediction Accuracy in the TRIP1180 Cold Stamping

This study aimed to evaluate the effect of constitutive equations on springback prediction accuracy in cold stamping with various deformation modes. This study investigated the ability of two yield functions to describe the yield behavior: Hill’48 and Yld2000-2d. Isotropic and kinematic hardening models based on the Yoshida-Uemori model were adopted to describe the hardening behavior. The chord modulus model was used to calculate the degradation of the elastic modulus that occurred during plastic loading. Various material tests (such as uniaxial tension, tension-compression, loading-unloading, and hydraulic bulging tests) were conducted to determine the material parameters of the models. The parameters thus obtained were implemented in a springback prediction finite element (FE) simulation, and the results were compared to experimental data. The springback prediction accuracy was evaluated using U-bending and T-shape drawing. The constitutive equations wielded significant influence over the springback prediction accuracy. This demonstrates the importance of selecting appropriate constitutive equations that accurately describe the material behaviors in FE simulations.

Modeling of nonlinear elastoplastic behavior after stress reversal for high strength steel

Material characteristics have significant impact on simulation of sheet metal forming. The accuracy of springback prediction depends on the estimation of strain recovery after die release. It is well known that the experimentally obtained unloading behavior for steel sheets is nonlinear stress-strain relationship, and the response during unloading and reloading shows a hysteresis loop. This behavior should be modeled by a material model and considered in FE-simulations for accurate predictions. In this study, the in-plane stress reversal tests for high strength steel were carried out to observe the elastoplastic behaviors after stress reversal. A material model that considers the nonlinear behavior was newly developed and implemented into the FEM software. The accuracy of springback prediction with the developed material model was validated by the draw bending tests and its springback simulations. The simulations with the developed material model show better agreement with the experimentally measured springback profile as compared to the other material models.

Stress-Strain Characterization for Reversed Loading Path and Constitutive Modeling for AHSS Springback Predictions

With increasing vehicle fuel economy standards, automotive OEMs are widely using various AHSS grades including DP, TRIP, CP and 3rd Gen AHSS to reduce vehicle weight due to their good combination of strength and formability. As one of enabling technologies for AHSS application, the requirement for requiring accurate prediction of springback for cold stamped AHSS parts stimulated a large number of investigations in the past decade with reversed loading path at large strains followed by constitutive modeling. With a spectrum of complex loading histories occurring in production stamping processes, there were many challenges in this field including issues of test data reliability, loading path representability, constitutive model robustness and non-unique constitutive parameter-identification. In this paper, various testing approaches and constitutive modeling will be reviewed briefly and a systematic methodology from stress-strain characterization, constitutive model parameter identification for material card generation will be presented in order to support automotive OEM’s need on virtual stamping. This systematic methodology features a tension-compression test at large strain with robust anti-buckling device with concurrent friction force correction, properly selected loading paths to represent material behavior during different springback modes as well as the 10-parameter Yoshida model with knowledge-based parameter-identification through nonlinear optimization. Validation cases for lab AHSS parts will also be discussed to check applicability of this methodology.