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The cold forming process becomes necessary in ship hull panel production when certain physical properties cannot be altered. To achieve precise cold forming results for doubly curved hull plates using reconfigurable dies, this paper introduces springback ratio (SR) matrices and SR feature values as descriptors and compensatory measures for springback. The feasibility and validity of the SR matrix and SR feature value are confirmed through an examination of springback outcomes from nine single-curvature plates, as documented in existing literature. Theoretical deductions highlighted a substantial contrast between sail-type and saddle-type plates. Subsequently, 14 metal doubly curved plate forming experiments are introduced employing reconfigurable dies. Upon comparing the springback results of sail-type and saddle-type plates described by SR feature values, it becomes evident that saddle-type plates exhibit significantly less springback than sail-type plates. In response, a novel springback compensation algorithm is proposed based on SR matrices. This algorithm is compared with an existing method, and the results demonstrate its superior performance in springback compensation.

The springback of laterally compressed thin-walled tubes is an important issue, which affects the prediction of tubular structure energy absorbing ability and the final sectional profile. So, the springback of laterally compressed tubes after plastic compression should be predicted and calculated in the process of the tube design. However, predicting the springback with traditional theoretical or experimental methods is hard. In the present paper, an explicit and implicit sequence-solving method based on ANSYS/LS-DYNA was developed for calculating and analyzing the springback of the tube under lateral compression by the code ANSYS LS-DYNA. The result implied that the explicit and implicit sequence-solving method is reasonable, and the values of the tube’s springback after lateral compression can be predicted by this FEA method.

Springback compensation for symmetrical and quasi-symmetrical sheet metal parts presents specific challenges. The common approach involves modifying forming tools in the opposite direction of the springback to achieve dimensional accuracy. However, asymmetrical springback effects, such as twisting, can occur even in symmetrical parts. These effects should not be compensated, as they are typically unstable, whether numerical or physical. Numerical distortions can be avoided using symmetry boundary conditions in simulations, but this is not always advisable for quasi-symmetrical parts or symmetrical parts with low stiffness. In quasi-symmetrical cases, it is often unclear whether asymmetry arises from numerical artefacts or slight geometric differences. For theoretically symmetrical parts, ensuring symmetrical behaviour in reality is crucial before applying compensation. This paper analyses springback behaviour in symmetrical and quasi-symmetrical parts and presents a guideline for handling such cases. Quantitative criteria for applying asymmetric compensation are proposed. Additionally, methods are introduced to systematically induce asymmetrical springback to enhance stability.

With the advantages of continuous bending, small bending diameter, and variable curvature, the spatial variable curvature (SVC) bent metallic tube (MT) is widely used in the aeronautics industry. Due to the complex characteristics of its central axis, SVC MT bending is prohibitive in terms of modeling and analysis, which results in a rather high calculation complexity. The springback is the primary detection that directly affects the axial forming accuracy. To achieve higher forming accuracy, this paper provides a numerical approximation springback prediction and compensation method considering cross-section distortion for SVC MT. The curvature and torsion mapping function of MT central axis before and after springback is constructed. According to the characteristics of different SVC MT, the differential equations in the SVC springback prediction model are solved by using three numerical approximation methods. The springback compensation method is subsequently obtained by inverse operation of the mapping relationship. To verify the feasibility of the proposed method, a 00Cr17Ni14Mo2 tube is bent with a multi-roll bender into the spiral shape. The results of the three springback numerical approximation methods and the numerical simulation result are compared. It illustrates that the Runge–Kutta method owns the highest prediction accuracy, so that we choose the Runge–Kutta method for bending compensation. The result indicates that the position deviation of each node is less than 1.4% along with the average position deviation of 0.80% after springback compensation.

Similar to springback in sheet metal forming, shape deviation due to welding in part assembly needs to be monitored and controlled. A surrogate model for welding distortion is implemented in AutoForm’s assembly finite element solver and is validated with help of hat shape laboratory scale welding experiments. The practical applicability of the approach is demonstrated with an automotive door sill that has 84 short laser line welds with a total length of more than 2100 mm.

Accurately predicting the amount of springback has always been a prior focus in metal forming industry, particularly for creep age forming (CAF), for its significant effect on tool cost and forming accuracy. In this study, a closed-form solution for CAF springback prediction covering deformation from elastic to plastic loadings was developed by combining the beam theory and Winkler’s theory, based on which an efficient springback compensation method for CAF was proposed. This developed solution extends the application area beyond the traditional beam theory-based springback prediction methods, maintaining its validity with large loading deflection in plastic range. Finite element (FE) simulation and four-point bending CAF tests adopting a 3rd generation Al-Li alloy were conducted in both elastic and plastic forming regions and the results showed close agreement with the closed-form springback predictions. For the proposed compensation method, an adjustment factor was introduced for complex flexible tool CAF to consider its deviation from the uniform stress loading and can be obtained using the closed-form solution. The flexible tool CAF tests using the Al-Li alloy demonstrated the applicability of the proposed compensation method to obtain the target shape within reasonable iterations, which can be further reduced by combining FE simulation.

Due to the discrete die of multi-point stretch bending, there are contact zone and non-contact zone on the profile, which makes the springback phenomenon more complicated. In this paper, considering that the neutral layer will shift due to the application of pre-stretching and post-stretching, an analytical model of the relationship between springback error and stress is established. Under the different bending radius, the maximum springback error obtained by theoretical calculation is 6.9%, while the average springback error of the traditional springback model is 10.5%, which means that the springback prediction model proposed in this paper is more reliable. Multi-point stretch bending has been unanimously recognized by everyone because of its adjustable die surface. In this paper, the secant method is used to calculate the springback compensation factor, so that the springback error of the profile is within the allowable error range of the production under the limited numbers of springback compensation.

Springback is one of the major shape defects in roll forming. It is difficult to predict springback accurately and efficiently because the process involves complicated deformation. In this paper, a high accuracy Support Vector Regression (SVR) algorithm based on the Simulated Annealing Particle Swarm Optimization algorithm (SAPSO) is proposed to predict springback. Firstly, simulations of the forming process of V-channel profile are carried out to investigate the springback at different fillet radii, yield strengths, uphill volumes and roll span spaces. Then with the data obtained, the accuracy of SAPSO-SVR, SVR, and Back Propagation Neural Network (BPNN) prediction models was tested. The experimental results show that SAPSO-SVR has the highest prediction accuracy, and its average absolute error is about 0.11 ∘ , which is 38.7% less than BPNN, and 61.8% less than SVR. Furthermore, in order to explore the applicability of emerging Artificial Intelligence (AI) models in investigating forming mechanisms, the relationship between forming parameters and springback was elucidated based on the prediction model. It is found that the roll span space had a small impact on springback, but a larger roll span space would reduce the impact of the uphill volume on springback. And applying an uphill volume of - 10 mm will minimize the variation of longitudinal strain in the cross section, thereby reducing the trend of flange inward shrinkage and leading to an increase in springback. The above conclusions are mutually verified with traditional theoretical research. This paper establishes a high accuracy prediction model and explores the springback mechanism, which can provide important theoretical references for future research on intelligent roll forming.

In bending process, the need of the precise material property characterization has become more and more important. So a new sheet metal bending equipment is independently developed to obtain the moment curvature characteristic in bending, bending-unloading and cyclic bending processes. The purpose of this paper is to describe the structure of the equipment and show the results about three kinds of bending tests for QP980. The tests performed by QP980 demonstrate that the bend and cyclic bend ability suits for researching non-linear springback and Bauschinger effect in this equipment.

This study adopts the method combining experiments and numerical simulations to investigate the springback of roll forming. The forming force and hardness of each pass from 0° to 50° were measured, and the springback rate of each pass was calculated. The research results show that the change in hardness is similar to the change in springback rates. The work hardening phenomenon on the outside of the corner is larger than that on the inside of the corner. The springback phenomenon of the sheet metal under repeated overbending and rebending is analyzed through a numerical model. The springback decreases when the number of gradual approximation passes increases.