Blank Holder Force Research Articles

Enhancing formability in deep drawing: A 3D finite element analysis of plastic wrinkling in AA2090 Al–Li alloy

Deep drawing is a manufacturing process used to produce billions of metal containers, crucial for the aerospace industry in forming thin-walled components efficiently. However, wrinkling due to compressive instability remains a significant challenge in sheet metal forming. This study investigates plastic wrinkling in sheet metal forming to enhance the final drawn shape. A 3D finite element model using ABAQUS/Explicit was developed to examine the effects of mesh topology, blank holder force, and sheet thickness on wrinkling in AA2090 Al–Li alloy. The finding indicates that that an increase in blank holder force increases wrinkle number and amplitude. Additionally, it was found that a 2000 N blank holder force is necessary to prevent wrinkling.

Study of Parameters Influencing Wrinkles in the Deep Drawing of Fiber-Based Materials Using Automatic Image Detection

The evaluation of wrinkles in deep-drawn fiber-based materials is crucial for the assessment of product quality and the optimization of manufacturing processes. Wrinkling is a common phenomenon in the deep-drawing process and is caused by tangential compressive stresses on the flanges of the blank. This phenomenon is particularly prevalent for fiber-based materials with high tensile depths and can seriously affect the appearance and mechanical properties of the final product. The objective of this study is to identify the key process parameters affecting wrinkling and to deepen the understanding of their roles and interactions using wrinkle data for deep-drawn paper products. Image analysis techniques are employed, supported by a specially constructed darkroom platform to ensure uniform light intensity for capturing photographs. An automated program is developed for the detection and evaluation of wrinkle characteristics and distribution, which allows the free choice of the region to be detected and the representation of the wrinkle geometry not limited by the number. To enhance the precision of this program, the ellipticity is initially rectified for products without flanges, specifically cup-shaped deep-drawn products. The ellipticity is caused by the pronounced springback effect of the paperboard. The approach is employed to investigate the impact of material properties, blank holder force, drawing depth, drawing clearance, and punch speed on wrinkling formation after the deep-drawing process. The findings reveal that the blank holder force and drawing clearance are critical factors in wrinkle formation, with higher blank holder force generally leading to increased wrinkle numbers.

Improving parameters for achieving uniform cylindrical cup wall thickness in two-step deep drawing processes with SPCC sheet material

Deep drawing processes are essential in modern manufacturing for creating intricate components with deep hollows, particularly cylindrical forms. These processes are widely used in industries such as household appliances, automotive manufacturing, aerospace engineering, and fire safety equipment. This study focuses on the two-step deep drawing of cylindrical cups, utilizing both simulation and experimental methods. The primary goal is to determine optimal geometric and technological parameters for mold design and to address issues like wrinkling and tearing. Key parameters, including punch nose radius (Rpf), die nose radius (Rdf), punch-die clearance (Wf), and blank holder force (BHF), are systematically analyzed. Results show that proper parameters lead to a uniform wall thickness, with deviations reduced to 4.77%. Conversely, improper parameters result in a 12.03% deviation. Improved parameters in the second-step deep drawing yield cylindrical cups that closely match experimental outcomes, free from wrinkling or rim cracking. This research highlights the importance of selecting appropriate parameters to avoid defects.

Optimization of Agricultural Tractor Engine Hood Forming Quality Based on Neural Network Genetic Algorithm Function

To improve the forming quality of agricultural tractor engine hood and effectively solve the problems of wrinkling and cracking during the drawing forming process, DYNAFORM 5.9 finite element software was used for numerical simulation of the part. Based on a comprehensive scoring method of orthogonal experiments and grey relational analysis, the critical process parameters affecting the “maximum thickening rate” and “maximum thinning rate” were determined. Latin hypercube sampling was used to randomly sample the key process parameters, and the sampled samples served as the data basis for the optimization stage of the neural network genetic algorithm function; an optimization model of the neural network genetic algorithm function was established, with the key process parameters, and the “maximum thickening rate” and “maximum thinning rate” as inputs and outputs respectively, to construct a nonlinear mapping relationship and optimize the process parameters. The study showed that the blank holder force and die clearance had the greatest impact on the “maximum thickening rate” and “maximum thinning rate”, identifying them as key process parameters; the optimal process parameter combination was the blank holder force of 462.71 kN, the die clearance of 1.09 mm, and corresponding “maximum thickening rate” and “maximum thinning rate” of 3.97% and 25.96%, respectively. Overall, this research provides a practical optimization strategy to solve the quality issues of the engine hood, offering a theoretical basis for its actual production and processing with significant practical application value.

Wrinkling suppression in cryogenic forming of high-strength Al-alloy ultra-thin shells by controlling interface shear stress

Avoiding wrinkling defects is extremely difficult in the sheet metal forming of ultra-thin components made from high-strength aluminum alloys. A novel cryogenic forming is thus proposed for solving this very challenging problem, wherein a thicker cladding blank is stacked above the thinner target blank to establish interface shear stress for reducing the hoop compressive stress, so that the critical wrinkling stress is increased. The enlarged radial deformation is transferred and withstood by the increasing hardening and ductility at cryogenic temperatures. The wrinkling suppression mechanism is revealed through mechanical and numerical analyses. Systematic experiments were conducted for studying the feasibility of high-strength AA7075 in cryogenic forming with different stacking sequences of cladding and target blanks, cladding blanks including three material strength levels (AA1060-O, AA5052-O, and SUS-304), two thicknesses (3.0, and 2.0 mm), and blank-holder forces. The effects of the cladding blank and blank-holder forces were clarified as reflected by forming defects, thickness, and strain distributions. The mechanical and numerical analyses can indicate that contact pressure can be produced by the wrinkling tendency of thinner target blank and limitation of cladding blank to wrinkling, which is accompanied by a decrease in the hoop compressive stress and increase in the critical wrinkling stress. Therefore, applying a relatively thicker blank on the punch side can prevent the wrinkling of ultra-thin components. The wrinkling tendency decreases with increasing strength and thickness of the cladding blank, which results in an increase in deformation or even splitting, which can be solved by the cryogenic temperature. The thickness of the cladding blank can be reduced by increasing the blank-holder force, which further reduces the material cost. AA5052-O, which has a strength similar to that of the target blank, is more suitable as a cladding blank for AA7075-W because the balance preventing wrinkling, improving thickness uniformity, and controlling the forming force. A Φ200 mm hemispherical shell with an initial thickness of 0.3 mm was formed successfully, and the corresponding thickness-to-diameter ratio reached 0.8‰, which almost increased one time on the basis of direct cryogenic forming. This new approach can be used for fabricating ultra-thin components from high-strength aluminum alloys.

Research on stamping formability and process simulation of AZ31 magnesium alloy based on deep learning

To study the formability of AZ31 magnesium alloy under different temperature conditions and improve the forming quality of its parts, this paper aims to solve the minimization problem of pursuing the “maximum thinning rate”. This study obtained the mechanical properties of AZ31 magnesium alloy at 25 °C, 150 °C, 250 °C, and 350 °C through uniaxial tensile tests and explored the stamping formability of AZ31 magnesium alloy mobile phone cases using the finite element inverse calculation method (MSTEP). Based on the hot stamping of AZ31 magnesium alloy at 250 °C, the Monte Carlo Simulation (MCS) method was used to randomly sample the blank holder force, stamping speed, friction coefficient, and resistance coefficient, and then simulate to obtain the corresponding “maximum thinning rate”. In addition, a hybrid prediction model optimized by Genetic Algorithm (GA) and Dung Beetle Optimization (DBO) based on the Back Propagation Neural Network (BPNN) - Random Forest (RF) was used to explore the nonlinear relationship between blank holder force, stamping speed, friction coefficient, resistance coefficient, and the “maximum thinning rate”. The results show that the plasticity of AZ31 magnesium alloy enhances with the temperature increase, especially exhibiting the best stamping formability at 250 °C. Feature importance indicates that the resistance coefficient and stamping speed have a greater impact on the maximum thinning rate, while the influence of blank holder force and friction coefficient is relatively smaller. Mean Square Error (MSE) shows that the predictive capability of the hybrid model is significantly superior to that of the single BP neural network and Random Forest model, displaying optimal efficiency. The predicted maximum thinning rate by the model is 15.39 %, with an error rate of only 0.32 % compared to the DYNAFORM finite element software simulation results, confirming the correctness, accuracy, and effectiveness of the prediction model. Overall, this study provides practical optimization strategies for metal stamping forming processes, with significant practical application value.

Failure analysis and formability improvement of GLARE laminates in warm active hydroforming technology: Experimental and numerical approach

Warm hydroforming shows considerable promise as a forming technology for Fiber Metal Laminates (FMLs) parts due to its capacity to enhance the formability of materials. However, a detailed investigation into the failure behavior during hydroforming is still lacking. In this paper, a systematic experiment was performed to analyze the possible failure modes for GLARE in warm active hydroforming. Five main defect modes have been identified, including fiber crack, combined Al & fiber crack, wrinkle, low resin, and voids defects. The related formation mechanisms have been analyzed based on both experiments and numerical methods. Additionally, the effects of critical process parameters, including the blank holder force (BHF), liquid pressure rate (PR), and temperature (T) on failure behavior are thoroughly investigated and quantified. The use of step-loading BHF was recommended to enhance formability, which caused a nearly 36% decrease in the prepreg tensile damage criteria coefficient. Conversely, decreasing PR or increasing T significantly improved the formability of GLARE but resulted in low resin content and significant void defects. Consequently, a feasibility map that quantified the BHF and liquid pressure effects on various defects was developed, leading to optimized parameters for manufacturing a box-shaped part. This study not only explores the failure model of FMLs but also offers valuable insights for process parameter improvement and how to optimize key parameters in engineering processes.

A Study on Yield Criteria Influence on Anisotropic Behavior and Fracture Prediction in Deep Drawing SECC Steel Cylindrical Cups.

The deep drawing process, a pivotal technique in sheet metal forming, frequently encounters challenges such as anisotropy-induced defects. This study comprehensively investigates the influence of various yield criteria on the anisotropic behavior and fracture prediction in SECC steel cylindrical cups. It integrates Hill'48R, Hill'48S, and von Mises yield criteria in conjunction with Swift's hardening law to evaluate material behavior under complex stress states. Experimental and numerical simulations assess the anisotropy effects across multiple orientations (0°, 45°, and 90°), revealing intricate relationships between stress criteria and material response. The findings indicate significant discrepancies between isotropic and anisotropic models in predicting fracture heights, emphasizing the importance of selecting appropriate yield criteria. Notably, the von Mises criterion results in lower fracture heights, suggesting higher susceptibility to fractures, while the Hill'48R model aligns closely with experimental data, validated through variations in punch corner radius and blank holder force parameters, with a maximum deviation of 3.23%. Hill'48S displays moderate plastic deformation characteristics.

Sheet Metal Forming Analysis of Aluminium Alloy AA6061 using |Altair INSPIRE Form Simulation

Altair INSPIRE Form is a computer simulation developed for designing and modelling sheet metal forming processes. Within the modules, the design and formability prediction can be simulated and optimized. Thus, this study focuses on analysing the formability of sheet metal Aluminium alloy AA6061 by simulating numerically a multistage forming of an end-wall process where the material properties and process parameters gained from the literature were used as input. The geometrical model was validated by comparing its formability with the literature that was simulated by Altair HyperForm. Then, to statistically analyse the influence of forming parameters on formability, Analysis of Variance (ANOVA) was applied with the design of experiment approach using the Response Surface Methodology (RSM). The simulation results observed similar strain rate distributions between Inspire Form and HyperForm under a safe forming process. For the formability of Aluminium alloy AA6061, loose metal zones with wrinkles, excessive thinning up to 23.13%, and the maximum equivalent stress at 414.6 MPa were expected to be generated. These findings clearly explained that forming parameters such as blank holder force and punch velocity have to be carefully controlled for this ductile material. The ANOVA shows a significant influence of coefficient friction and punch velocity on thinning percentages. The likelihood of tearing to form at a higher thinning percentage and its appearance was observed in the Forming Limit Diagram which evaluates its formability. The validation of optimized parameters by simulation work is concluded to be successful as no fracture appeared in this simulation with a small percentage error at 2.19% between the simulation and the predicted value.

Numerical Optimization of Variable Blank Holder Force Trajectories in Stamping Process for Multi-Defect Reduction.

An intelligent optimization technology was proposed to mitigate prevalent multi-defects, particularly failure, wrinkling, and springback in sheet metal forming. This method combined deep neural networks (DNNs), genetic algorithms (GAs), and Monte Carlo simulation (MCS), collectively as DNN-GA-MCS. Our primary aim was to determine intricate process parameters while elucidating the intricate relationship between processing methodologies and material properties. To achieve this goal, variable blank holder force (VBHF) trajectories were implemented into five sub-stroke steps, facilitating adjustments to the blank holder force via numerical simulations with an oil pan model. The Forming Limit Diagram (FLD) predicted by machine learning algorithms based on the Generalized Incremental Stress State Dependent Damage (GISSMO) model provided a robust framework for evaluating sheet failure dynamics during the stamping process. Numerical results confirmed significant improvements in formed quality: compared with the average value of training sets, the improvements of 18.89%, 13.59%, and 14.26% are achieved in failure, wrinkling, and springback; in the purposed two-segmented mode VBHF case application, the average value of three defects is improved by 12.62%, and the total summation of VBHF is reduced by 14.07%. Statistical methodologies grounded in material flow analysis were applied, accompanied by the proposal of distinctive optimization strategies for the die structure aimed at enhancing material flow efficiency. In conclusion, our advanced methodology exhibits considerable potential to improve sheet metal forming processes, highlighting its significant effect on defect reduction.

Experimental and numerical investigation to determine the optimal blank-holder force in deep drawing process based on forming force for SS304L and St14 sheets

Experimental and numerical investigation to determine the optimal blank-holder force in deep drawing process based on forming force for SS304L and St14 sheets

Clarification of appropriate conditions for forming complex shapes with multiple steps in two-stage deep drawing process

In this study, appropriate conditions for forming complex shapes with multiple steps, such as automotive side door inner in a two-stage deep drawing process are investigated, and the effectiveness of the process is verified in a test. In this forming process, the inner area of the part is formed in the first stage and the outer area is formed in the second stage. And in the second stage, a forming pad is used to reduce strain in the inner area that is formed in the first stage. The results of the forming test showed that it is necessary to control the blank holding force (BHF) and the pad force (PF) in the second stage to avoid blank ruptures in all areas. Therefore, the concept of the BHF and PF for blank rupture risk at each site was studied using the finite element method (FEM). An appropriate range of BHF and PF was estimated from the results of FEM and the validity of the estimated values was confirmed in an actual test. In addition, it was confirmed that a two-stage deep drawing process using the above appropriate values can form a more severe shape than a one-stage deep drawing process.

Study on the hot deep drawing performance and microstructural evolution of AZ91D magnesium alloy sheets

Magnesium alloys are attractive because of their low density and high specific strength and stiffness; however, secondary phase strengthening and the low number of slip systems lower formability especially for the strongest magnesium alloys such as AZ91D. The formability of AZ91D sheets is investigated through orthogonal experiments, which show that AZ91D has no deep drawing properties at room temperature and that plastic forming is only possible under hot forming conditions. When the temperature is increased from room temperature to 400 °C, the limiting drawing ratio of the sheet increases significantly to 1.91, and the thinning rate reaches a minimum value of 6% at approximately 400 °C because of the improved plastic flowability. The optimum process parameters for hot deep drawing are a temperature of 400 °C, blank holder force of 5 kN, and punch speed of 3 mm s−1. The microstructural evolution shows that plastic deformation of the AZ91D magnesium alloy at high temperatures is markedly accommodated by twinning and that, with heating, this twinning deformation mechanism is activated and overcomes the hindrances of the reinforcing phases to achieve better forming properties.

Optimizing Reverse-Engineered Finite Element Models for Accurate Predictions of Experimental Measurements

This study investigates the challenges of reverse engineering in finite element modelling of sheet metal forming, specifically for the Volvo XC90 front door inner component. Advanced models incorporating anisotropic behaviour of steel and non-linear friction are compared against actual real-world measurements. The methodology involves simplifying complex continuous parameters into more manageable representative data sets and assessing model accuracy under both uniform and varied blank holder force settings, guided by measured contact pressure distributions. Although the results indicate an improvement in accuracy, they underscore the need for additional methodological improvements and more accurate replication of tooling effects to enhance the fidelity and effectiveness of these models.

A 3D Non-Linear FE Model and Optimization of Cavity Die Sheet Hydroforming Process

Cryo-rolled aluminum alloys have a much higher strength-to-weight ratio than cold-rolled alloys, which makes them invaluable in the aerospace and automotive industries. However, this strength gain is frequently accompanied by a formability loss. When uniformly applied to the blank surface, hydroforming provides a solution by generating geometries with constant thickness, making it possible to produce complex structures with “near-net dimensions”, which are difficult to achieve with conventional approaches. This study delves into the cavity die sheet hydroforming (CDSHF) process for high-strength cryo-rolled AA5083 aluminum alloy, focusing on two primary research questions. Firstly, we explored the utilization of a nonlinear 3D finite-element (FE) model to understand its impact on the dimensional accuracy of hydroformed components within the CDSHF process. Specifically, we investigated how decreasing fluid pressure and increasing the holding time of peak fluid pressure can be quantitatively assessed. Secondly, we delved into the optimization of process parameters—fluid pressure (FP), blank holding force (BHF), coefficient of friction (CoF), and flange radius (FR)—to achieve dimensional accuracy in hydroformed square cups through the CDSHF process. Our findings reveal that our efforts, such as reducing peak fluid pressure to 22 MPa, implementing a 30 s holding period, and utilizing an unloading path, enhanced component quality. We demonstrated this with a 35 mm deep square cup exhibiting a 16.1 mm corner radius and reduced material thinning to 5.5%. Leveraging a sophisticated nonlinear 3D FE model coupled with response surface methodology (RSM) and multi-objective optimization techniques, we systematically identified the optimal process configurations, accounting for parameter interactions. Our results underscore the quantitative efficacy of these optimization strategies, as the optimized RSM model closely aligns with finite-element (FE) simulation results, predicting a thinning percentage of 5.27 and a corner radius of 18.64 mm. Overall, our study provides valuable insights into enhancing dimensional accuracy and process optimization in CDSHF, with far-reaching implications for advancing metal-forming technologies.

Experimental and numerical optimization of deep drawing process parameters for square medical container design with the Taguchi method

Medical containers that sterilize surgical instruments are constantly needed in the healthcare industry. In line with this need, improvements in the fabrication of medical containers are important. Determining the design factors of medical containers fabricated by deep drawing saves time and cost. This study determined, the design factors of square medical containers and experimentally verified the deep drawing process modeled in Abaqus/Explicit finite element (FE) software. Taguchi statistical method was used to reduce the number of experiments. Blank holder force (BHF), punch radius (RP), die radius (RD), coefficient of friction between die and blank (µDB), coefficient of friction between punch and blank (µPB), coefficient of friction between holder and blank (µHB) as variable factors while selecting thickness reduction (TR) and maximum punch force (PF) were selected as output parameters. The effect of variable factors on the output parameters was determined by ANOVA analysis. As a result of the examinations, it was deter-mined that TR and PF increased as BHF, µDB and µHB values increased, whereas they decreased as RP and RD increased. On the other hand, it was determined that TR decreased and PF increased as µPB increased. In addition, the corners of the sheets were chamfered in different sizes to prevent the formation of ears in the containers. Finally, the appropriate chamfer size was determined by examining the sheet thicknesses.

Investigation on the Effect of Blank Holder Force and Initial Blank Size on the Thinning Problem of the Fuel Tank Part Made from Aluminum Alloy Sheet 5754-O under Deep Drawing Process

Deep drawing process is a common sheet metal forming technique in motor vehicle manufacturing. There are three primary defects that could be occur in deep-drawn parts: tearing, wrinkling, and thinning. When the thinning is difficulty detected by visual inspection. As a result, this study aims to address the thinning issue in a fuel tank part made from an aluminum alloy sheet AA5754-O 1.5 mm thick under cold working deep drawing process, while the manufacturer's desired upper limit for thinning is 20%. Two influential parameters viz. blank holder force and initial size of blank, were investigated and optimized by using Finite Element Analysis (FEA) through PAM-STAMP simulation software with the validated material model was based on Hill’s 1948 anisotropic yield criterion with Swift hardening law. The mechanical parameters in the mentioned model were derived from the results of uniaxial tensile tests. In conclusion, both the hydraulic cushion's blank holder pressure and the initial size of the blank were found to influence the thinning of the part, either individually or in combination. Despite optimizing both parameters, they were unable to consistently achieve the desired limit.

Multi-Objective Optimization of VBHF in Deep Drawing Based on the Improved QO-Jaya Algorithm

Blank holder force (BHF) is a crucial parameter in deep drawing, having close relation with the forming quality of sheet metal. However, there are different BHFs maintaining the best forming effect in different stages of deep drawing. The variable blank holder force (VBHF) varying with the drawing stage can overcome this problem at an extent. The optimization of VBHF is to determine the optimal BHF in every deep drawing stage. In this paper, a new heuristic optimization algorithm named Jaya is introduced to solve the optimization efficiently. An improved “Quasi-oppositional” strategy is added to Jaya algorithm for improving population diversity. Meanwhile, an innovated stop criterion is added for better convergence. Firstly, the quality evaluation criteria for wrinkling and tearing are built. Secondly, the Kriging models are developed to approximate and quantify the relation between VBHF and forming defects under random sampling. Finally, the optimization models are established and solved by the improved QO-Jaya algorithm. A VBHF optimization example of component with complicated shape and thin wall is studied to prove the effectiveness of the improved Jaya algorithm. The optimization results are compared with that obtained by other algorithms based on the TOPSIS method.

Numerical multi-objective optimization of segmented and variable blank holder force trajectories in deep drawing based on DNN-GA-MCS strategy

Numerical multi-objective optimization of segmented and variable blank holder force trajectories in deep drawing based on DNN-GA-MCS strategy

Numerical modeling for shearing of unidirectional carbon fiber reinforced plastic laminates by means of near-net-shape blanking

Structural components made of carbon fiber reinforced plastics (CFRP) exhibit a high degree of lightweight suitability. In order to fulfill geometric and functional requirements, a finishing process step of outer and inner contours is necessary. Near-net-shape blanking processes show potential for economical finishing of CFRP structural components. For the knowledge-based design of a near-net-shape blanking process comparable to fine blanking an understanding of the separation mechanisms during shearing of CFRP laminates is required. Therefore, this paper deals with the development of a finite element (FE) process model for near-net-shape blanking of unidirectional (UD) CFRP laminates with different fiber volume fraction and fiber orientation. Material modeling of the UD CFRP laminates was carried out by means of experimental characterization based on tensile, compression and shear tests. The formulation of the material model was implemented using a VUMAT user subroutine. The application of the blank holder and counter force was realized using a kinematic model based on a VUAMP user subroutine. A validation based on experimental near-net-shape blanking tests will be conducted in the next step.