Sheet Metal Forming Research Articles

EXPERIMENTAL DETERMINATION OF THE DRAW BEAD COEFFICIENT OF FRICTION OF CuZn SHEETS IN SHEET METAL FORMING PROCESSES

In sheet metal forming, draw beads are used to limit the flow of sheet metal in specific areas of the stamping die. The value of the coefficient of friction at the draw bead determines achievement of the desired resistance to sheet displacement. This article presents the results of experimental tests for determining the coefficient of friction on a draw bead using a specially developed tribotester. The test material consisted of CuZn37, CuZn30 and CuZn10 brass sheets in various states of hardening. Investigations were carried out with different roughness of the countersamples and sliding speeds. In addition, the tests were carried out under conditions of dry friction and lubrication of the sheet surface with LAN-46 machine oil. The relationships between the process parameters and the value of the coefficient of friction were analysed using the analysis of variance. It was found that the coefficient of friction decreases with increasing mean roughness of the countersamples. Lubrication reduced friction by about 6.2-29.8% depending on the grade of the tested sheet and the sliding speed.

Investigating the Static Recrystallization Behavior of 22MnB5 Manganese–Boron Steel through Stress Relaxation Analysis

A constitutive model was developed to characterize the static recrystallization (SRX) and evolution of the grain size of the industrially relevant press-hardening steel, 22MnB5, subsequent to the hot forming of sheet metal. Isothermal stress relaxation tests were conducted using the BAEHR 805 A/D thermomechanical simulator, encompassing a temperature range of 950 to 1050 °C, prestrain levels ranging from 0.01 to 0.1, and strain rates spanning from 0.01 to 0.8 s−1. The results obtained from the isothermal stress relaxation tests facilitated the formulation of an Avrami equation-based model, which aptly describes the kinetics of SRX in relation to the temperature, prestrain, and strain rate. Notably, an increase in temperature led to accelerated recrystallization kinetics, signifying temperature-dependent behavior. When the temperature increased from 950 to 1050 °C, the recrystallization time was reduced to approximately one-third. Additionally, the prestrain exhibited a positive influence on the acceleration of SRX kinetics. A quintupling of the prestrain from 0.01 to 0.05 resulted in a reduction of the static recrystallization duration to approximately one-fifth. Among the parameters studied, the strain rate had the least impact on the SRX kinetics, as doubling the strain rate from 0.01 to 0.8 only resulted in a halving of the recrystallization duration. Moreover, an analysis of the microstructural evolution in response to the forming parameters was undertaken. While the grain-size investigation post-isothermal stress relaxation tests provided results in line with the SRX kinetics calculations, the observed effects were comparatively subdued. Furthermore, a comprehensive examination was conducted using electron backscatter diffraction (EBSD) analysis, aiming to explore the effects of specific stress relaxation states on the morphology of martensite. The findings reveal fully recrystallized globulitic microstructures, characterized by relatively minor differences among them.

Parameter determination of anisotropic yield function using neural network-based indentation plastometry

Understanding the impact of plastic anisotropy on the formability of sheet metals is crucial for their industrial application and high-precision forming simulation. Existing multiple uniaxial tensile tests for measuring the plastic flow of anisotropic materials, however, are costly, time-consuming, and destructive. Therefore, it is more efficient to focus on indentation plastometry, a simple, nondestructive test that can quickly extract tensile properties. The objective of this work is to directly derive the parameters of the advanced Poly6 yield criterion and hardening, which describes strong plastic anisotropy, using indentation plastometry basd on a neural network (NN) system. The identification process for these parameters through conventional tensile tests is inherently complex, thereby determining the parameters directly from indentation data presents an unprecedented challenge. We trained NNs using a database generated from verified finite element (FE) simulations of spherical indentations. To systematically iterate these FE simulations, we designed a strategy generating a set of input anisotropic parameters that ensure the convexity of the yield function. We considered the radial and vertical displacement fields around the indentation mark along with the load-depth curve as indentation responses. Through a comprehensive analysis of the correlation between displacement profiles, we have proposed an optimal feature extraction method for NN training. The developed FE-NN model was evaluated by comparing the predicted parameters from the indentation responses of the target materials with those measured from tensile tests. These parameters were expressed as the yield locus and directional properties. The results demonstrated that the FE-NN modeling approach is robust and can accurately capture the anisotropic plastic flow from indentation responses.

Towards the Digital Model of Tool Lifecycle Management in Sheet Metal Forming

Towards the Digital Model of Tool Lifecycle Management in Sheet Metal Forming

Investigation of feature-based and space-filling tool path strategies for formability in incremental sheet metal forming

Investigation of feature-based and space-filling tool path strategies for formability in incremental sheet metal forming

Aluminum alloy W-temper cryogenic forming with enhanced formability and strength

Simultaneously obtaining excellent formability and post-form strength in the traditional sheet metal forming of heat-treatable aluminum alloy is challenging, owing to the coexistence of wrinkling and splitting defects during forming and the control problem of microstructure. To solve these problems, W-temper cryogenic forming was proposed based on the cryogenic ‘dual-enhancement effect’ of an as-quenched (W-temper) aluminum alloy. The effects of the cryogenic temperature gradient and blank-holder force on the drawing behaviors were studied by analyzing the forming defects and thickness distribution. Strength distributions were reflected through Vickers hardness measurements under different aging conditions. The related strengthening mechanism was revealed through microstructure characterization. The drawability can be significantly improved at small or large cryogenic temperature gradients. An Al-Cu alloy semispherical shell component was fabricated via W-temper cryogenic forming. The depth of the formed hemispherical specimens increased by more than 106.4%. Uniform thickness can be also obtained at the temperature gradient of 216 °C, with an average thickness deviation rate of 6.5%, benefiting from the cryogenic dual enhancement effect and enlargement of the stress gradient. The hardness in all regions was higher than 146.5 HV of traditional T8-temper because of the enough accelerating precipitation of θʺ and θʹ phases by prior cryogenic deformation. Strain and precipitation strengthening were the main strengthening mechanisms under post-forming and post-aging conditions, respectively. The peak-aging time can be shortened to 6 h, which is one-third that of the traditional process. Enhanced formability and post-form strength can be simultaneously obtained by W-temper cryogenic forming, which has great potential for the fabrication of thin shells made from heat-treatable aluminum alloys.

On Improving Sheet Metal Formability in Hydrodynamic Deep Drawing Process through a Solid‐Oil‐Type Mineral Grease Pressure Medium

In this research, the improvement in sheet metal formability obtained through the utilization of a mineral grease in solid‐oil‐type (SMG) pressure medium in the hydrodynamic deep drawing process assisted by radial pressure is investigated by experiments and finite‐element method (FEM) simulations on flat‐bottom cups realized with pure copper and DIN 1.0338 steel. To determine the process parameters ranges, an FEM model is developed in ABAQUS/Explicit and validated against experimental results. Afterward, experiments are carried out using two pressure mediums with different viscosities, i.e., water and SMG. Considering the results relevant for both sheet materials, the SMG medium allows an average reduction of the sheet metal thinning of 15% and 10% on the corner edges while also granting a negligible thickness variation on the cup walls. In contrast, the higher viscosity of the SMG, in comparison to the water medium, also results in an average 16% increase in the forming force when compared to the water pressure medium.

A Study on the Effect of Multistage Toolpath in Fabricating a Customized Cranial Implant in Incremental Sheet Metal Forming

Incremental sheet forming (ISF) process offers a high degree of flexibility in the manufacturing of different sheet parts, which makes it an ideal candidate for prototype parts as well as efficient at fabricating various customized products at low production costs compared to traditionally used processes. However, parts produced in this process exhibit notable geometrical inaccuracy and considerable thickness reduction. In this paper, the single point incremental sheet forming variant of the process has been implemented to manufacture a highly customized cranial implant starting from the computed tomography (CT) scan data of the patient's anatomy. A methodology, from the modeling to the realization of the implant, is presented and discussed. The primary aim of the research was to analyze and study the effect of the multistage toolpath strategy compared to the traditional single-stage toolpath in terms of geometrical accuracy and thickness distribution. The final results show that the part formed in the multistage toolpath strategy exhibited a more uniform thickness distribution compared to the single-stage approach. Regarding the geometrical accuracy, the deviation analysis between the nominal and actual data has revealed that the multistage forming has significantly enhanced the final geometrical accuracy of the formed part.

Assessing the Feasibility of Cold Forming of Automotive Parts from Quenched and Partitioned Martensitic Stainless Steels

Sheet metal forming is among the most widely employed processes in manufacturing. Its economic feasibility relies on many factors, including the mechanical properties of the processed materials, energy efficiency of the metal‐forming processes, and quality of the manufactured parts. This work focuses on developing a computational approach to assess the mechanical behavior of quenched and partitioned (QP) martensitic stainless steels (MSSs) undergoing cold forming, aiming at the serial production of automotive parts. The Johnson–Cook (J–C) constitutive model and forming limit diagram (FLD) are derived and validated for each alloy using the experimental data from tensile and Nakajima tests. From the simulated FLD, a theoretical forming limit stress diagram (FLSD) is calculated. The latter is used as a fracture criterion for the cold‐forming process. Cold stamping of two automotive parts, B‐pillar and tunnel, is modeled using the J–C constitutive model and the FLSD. It is demonstrated that the tunnel can be successfully cold‐formed from all three studied steels. In contrast, extensive cracking is expected during the cold forming of the B‐pillar from all materials. It is envisaged that these computational models can be employed for the assessment of any comparable part manufacturing procedure from the QP MSSs.

An Investigation into the Friction of Cold-Rolled Low-Carbon DC06 Steel Sheets in Sheet Metal Forming Using Radial Basis Function Neural Networks

This article presents the friction test results for cold-rolled low-carbon DC06 steel sheets, which are commonly processed into finished products using sheet metal forming methods. A strip drawing test with flat dies was used in the experimental tests. The strip-drawing test is used to model the friction phenomena in the flange area of the drawpiece. The tests were carried out using a tester that enabled lubrication with a pressurised lubricant. The friction tests were carried out at different nominal pressures, oil pressures, and friction conditions (dry friction and oil lubrication). Oils destined for deep-drawing operations were used as lubricants. Neural networks with radial base functions (RBFs) were used to explore the influence of individual friction parameters on the value of the coefficient of friction (COF). Under lubrication with both oils considered, the value of the COF increased with decreasing oil pressure. This confirms the correctness of the concept of the device for reducing friction in the flange area of the drawpiece. The developed concept of pressurised lubrication is most effective at relatively small nominal pressures of 2–4 MPa. This range of nominal pressures corresponds to the actual nip pressures when forming deep-drawing steel sheets. Under conditions of dry friction, the values obtained for the COF rise above 0.3, while under lubrication conditions, even without pressure-assisted lubrication, the COF does not exceed 0.2. As the nominal pressure increases, the effectiveness of the lubrication exponentially decreases. It was found that the Sq parameter carries the most information regarding the value of the COF. The RBF neural network with nine neurons in the hidden layer (RBF-8-9-1) and containing the Sq parameter as the input was characterised by an R2 of 0.989 and an error of 0.000292 for the testing set.

Comparison of forming processes for micro textured cups

Friction losses are present in all kinds of technical systems. This is always associated with additional energy consumption, which can be partly avoided as it arises. Energy savings can be achieved by a wide range of approaches. The application of friction reducing coatings on bodies in relative motion is widespread. The coating of parts is however only suitable to a limited extent for the production in large batches. Therefore, research approaches consider alternative methods to achieve friction reductions. A promising approach is the integration of miniaturized pockets on the surface of the component. In lubricated contacts, the lubricant can then accumulate in these indentations. The relative motion between two bodies thus builds up a hydrodynamic pressure and consequently reduces friction. Forming technology is suitable for the efficient production of metallic components in large quantities. The aim of this study is therefore to identify challenges in the integration of micro coining in established forming processes. Two processes from sheet metal forming and bulk metal forming are investigated. In a combined experimental and numerical approach, process-specific challenges are derived regarding the texturing process and the numerical process modelling for combined micro coining. The analysis is carried out on a cup geometry, as used in the automotive sector as tappets in the valve train. The case hardening steel 16MnCr5 (1.7131) is used as workpiece material.

Three Dimensional Metal-Surface Processing Parameter Generation Through Machine Learning-Based Nonlinear Mapping

The accuracy and efficiency of three-dimensional (3D) surface forming, which directly affects the cycle and quality of production, is important in manufacturing. In practice, given the uncertainty of metal plate springback, an error exists between the actual plate and the target surface, which creates a nonlinear mapping from computer aided design models to bending surfaces. Technicians need to reconfigure parameters and process a surface multiple times to delicately control springback, which greatly wastes human and material resources. This study aims to address the springback control problem to improve the efficiency and accuracy of sheet metal forming. A basic computation approach is proposed based on the DeepFit model to calculate the springback value in 3D surface bending. To address the sample data shortage problem, we put forward an advanced approach by combining a deep learning model with case-based reasoning (CBR). Next, a multi-model fused bending parameter generation framework is devised to implement the advanced springback computation approach through surface data preprocessing, CBR-based model matching, convolution neural network-based machining surface generation, and bending parameter generation with a series of model transformations. Moreover, the proposed approaches and the framework are verified by considering saddle surface processing as an example. Overall, this study provides a new idea to improve the accuracy and efficiency of surface processing.

Development of combined hardening model for spring-back simulation of DP600 in multi-stage sheet metal forming

High strength steel DP600 is widely used in automobile industry due to its excellent mechanical property compared to conventional steel, but spring-back issue is considered to be the major challenge of DP600 in forming process, as the spring-back is triggered by the release of complicated internal stress. In multi-stage sheet metal forming, the sheet may be subject to several cycles of loading and reverse loading, Bauschinger effect greatly influence the strain stress behaviour. A well designed material model can be used to accurately predict and compensate spring-back in forming process. A combined hardening model especially designed for multi-stage forming is proposed in this paper, and the iterated compensation method could be applied by using LS-DYNA to get an optimized result. An experimental testing facility was developed for calibration of this model with cyclic tension and compression strain stress curve. The compensation method is applied in the numerical simulation of a multi-stage manufacturing process of an A-pillar, the result demonstrates the feasibility of the combined hardening model.

Increasing the efficiency of the forming process by the DRECE method

The DRECE method is a progressive method for forming sheet metal strips using the principle of severe plastic deformation (SPD). The DRECE method is characterized by extruding the sheet metal strip with a forming device which creates a forming angle of 108 ° in the deformation zone. During the practical verification of the DRECE method, it was found that the materials formed by the method show a significant increase in mechanical properties after the first pass through the forming equipment while maintaining sufficient ductility of the materials. With each subsequent pass of the material through the forming device, the mechanical properties increase. For the subsequent industrial use of the DRECE method, the key technological parameter of the forming equipment is the feed speed of the sheet metal strip. At present, the forming device makes it possible to regulate the feed speed of the sheet metal strip in the range of 10 - 100 mm / s. The device allows continuous sensing and recording of torque, extrusion force and feed rate of the sheet metal strip during the forming process. These facts are very important for the subsequent use of the method in industrial practice.

An enhanced boundary lubrication friction model for sheet metal forming

A new micromechanics-based friction model a under boundary lubrication is proposed to enhance an existing surface asperity-based friction model. The study presents a formulation of equilibrium between the plastically deformable workpiece and contact tool, and the newly proposed geometrical modeling of the tool surface to implement the plowing effect. Under this scheme, the contact tool is modeled based on the primary summits in the tool height distribution identified by a measured wavelength, which avoids the dependency on the accurate measurement of summit profiles. Also, the model can consider the micro-scale interaction between metal workpiece and tool surface. The developed micromechanics-based friction model is validated by comparing the calculated nominal friction coefficients of advanced high-strength steels (AHSS) at different contact pressures with those of experiment. Finally, the friction model is implemented in finite element (FE) software to simulate two forming processes: U-draw/bending and an in-line incremental die forming. The predicted forming force and springback in the sheet metal forming agree well with the experimentally measured ones, which verifies the accuracy and numerical efficiency of the proposed friction model and its numerical implantation.

Analysis of the Frictional Performance of AW-5251 Aluminium Alloy Sheets Using the Random Forest Machine Learning Algorithm and Multilayer Perceptron.

This paper is devoted to the determination of the coefficient of friction (COF) in the drawbead region in metal forming processes. As the test material, AW-5251 aluminium alloys sheets fabricated under various hardening conditions (AW-5251-O, AW-5251-H14, AW-5251-H16 and AW-5251H22) were used. The sheets were tested using a drawbead simulator with different countersample roughness and different orientations of the specimens in relation to the sheet rolling direction. A drawbead simulator was designed to model the friction conditions when the sheet metal passed through the drawbead in sheet metal forming. The experimental tests were carried out under conditions of dry friction and lubrication of the sheet metal surfaces with three lubricants: machine oil, hydraulic oil, and engine oil. Based on the results of the experimental tests, the value of the COF was determined. The Random Forest (RF) machine learning algorithm and artificial neural networks (ANNs) were used to identify the parameters affecting the COF. The R statistical package software version 4.1.0 was used for running the RF model and neural network. The relative importance of the inputs was analysed using 12 different activation functions in ANNs and nine different loss functions in the RF. Based on the experimental tests, it was concluded that the COF for samples cut along the sheet rolling direction was greater than for samples cut in the transverse direction. However, the COF's most relevant input was oil viscosity (0.59), followed by the average counter sample roughness Ra (0.30) and the yield stress Rp0.2 and strength coefficient K (0.05 and 0.06, respectively). The hard sigmoid activation function had the poorest R2 (0.25) and nRMSE (0.30). The ideal run was found after training and testing the RF model (R2 = 0.90 ± 0.028). Ra values greater than 1.1 and Rp0.2 values between 105 and 190 resulted in a decreased COF. The COF values dropped to 9-35 for viscosity and 105-190 for Rp0.2, with a gap between 110 and 130 when the oil viscosity was added. The COF was low when the oil viscosity was 9-35, and the Ra was 0.95-1.25. The interaction between K and the other inputs, which produces a relatively limited range of reduced COF values, was the least relevant. The COF was reduced by setting the Rp0.2 between 105 and 190, the Ra between 0.95 and 1.25, and the oil viscosity between 9 and 35.

Analysis of the Effectiveness of Technological Lubricants with the Addition of Boric Acid in Sheet Metal Forming.

One of the main problems during sheet metal forming is the reduction in coefficient of friction and separation of contact surfaces in order to eliminate buildups of the formed material on the forming tools. For this purpose, technological lubricants based on mineral or synthetic oils are usually used. Unfortunately, their removal from the drawn parts and their subsequent utilization pose many problems and are expensive. Environmentally benign lubricants based on vegetable oils with the addition of boric acid could be an effective alternative to lubricants based on mineral and synthetic oils; however, the solubility of boric acid in oils is limited. Therefore, the paper proposes new, effective, and environmentally friendly methods for applying boric acid to the metal sheet by spraying it on a thin rapeseed oil layer previously applied to the metal sheet or by spraying a 25% solution of boric acid in methyl alcohol onto the sheet. The effectiveness of such lubrication was assessed on the basis of the so-called strip drawing test, Erichsen cupping test, and formation of cylindrical drawn parts in industrial conditions. The tests showed that the addition of boric acid was most effective for forming the DC01 steel sheet, reducing the coefficient of friction by about 60% compared to base oil lubrication. Although its usefulness is lower in the case of other frictional pairs, it eliminates the phenomenon of the formed material sticking to the tool, thus extending the life of the forming tools. The use of the proposed solution reduces production costs and indirectly boosts environmental protection. Moreover, an explanation of the tribological mechanism contributing to the lubrication action of boric acid is given.

Multi-objective parametric optimization of driver-based electromagnetic sheet metal forming of SS304 using AA6061-T6 driver

This study uses statistical techniques to optimize the electromagnetic forming process for driver-based sheet metal forming with a flat coil. AA6061T6 sheet was used as a driver to form SS304 sheets. The optimization of maximum elongation, die fitting, maximum Lorentz force, and peak current was carried out. The results were verified through simulation which were in close agreement with the experimental results. The most influential factor was the voltage (C.R of 72.97%), followed by coil gap and SS304 sheet thickness (7.99 and 6.07%, respectively).

Friction and Wear in Stages of Galling for Sheet Metal Forming Applications

Aluminum is a very commonly used material at present, and roughly half of the produced aluminum products undergo forming during manufacturing. Galling is a severe form of wear that occurs during sheet metal forming operations and is a common failure mode of materials in sliding contact; however, the causes and mechanisms of galling are poorly understood. In this work, sliding wear experiments were conducted to produce galling wear between a tool steel ball bearing and aluminum alloy Al5083, to study the relationship between the coefficient of friction, the lump growth on the tool and the scratch morphology. Whilst the characteristic friction regimes were observed, the characteristic damage (grooves running parallel to the scratch direction) was not observed. Instead, when galling was developed on the indenter, the scratch surface morphology displayed a series of peaks and grooves perpendicular to the scratch direction. It is likely that the difference in scratch morphology observed once galling was initiated is due to the lower hardness and reduced work hardening behavior of the Al5083 alloy, compared to the high strength steels previously examined in sheet metal forming applications. The evolution of the scratch morphology has been characterized in a novel way by investigating the distribution of the longitudinal cross-section profile height along the scratch length in relation to the three-stage friction regime observed. This showed that, as the galling wear progressed, the longitudinal cross-section profile height distribution shifts towards negative values, with a corresponding shift in the distribution of material transferred to the tool shifting to the positive. This indicates that, as the amount of material adhered to the indenter increased, the depth of the grooves on the scratch surface perpendicular to the sliding direction also increased.

The effect of high solid solution Mg contents (7–13 wt%) on the dynamic strain aging behavior of Al–Mg alloys

Plastic instability caused by Portevin–Le Chatelier (PLC) due to the interaction of dislocations with solute atoms, known as dynamic strain aging (DSA), remains a serious hindrance for sheet metal forming, especially for 5000 series Al alloys. Here, we investigated the DSA behavior of hot extruded Al–Mg alloys with high solid solution Mg contents varying from 7 to 13 wt% at different tensile strain rates. With increasing the Mg content and decreasing the strain rate, the critical strain for the onset of serrated stress flow increases gradually, indicating the greatly suppressed plastic instability. Moreover, serrations changes from type B to type C with increased concentrations of Mg at 5 × 10−4 s−1 and 1 × 10−3 s−1. In the Al–7Mg alloy, the critical strain exhibits an inverse behavior at lower strain rates (< 1 × 10−3 s−1) but a normal behavior at higher strain rates (> 1 × 10−3 s−1). Whereas, the inverse behavior predominates the entire range of strain rates in the Al–10Mg and Al–13Mg alloys, where the waiting time of dislocations at temporary barriers is longer than the diffusion time of Mg solutes at the critical strain. Dislocations are pinned prior to the critical strain and the first plastic instability depends on the first unpinning event.