Sheet Metal Stamping Research Articles

Re-manufacturing of Pre-deformed Automotive Sheet Metal Stamping Scrap Without Melting

Abstract The recycling of aluminium sheet metal typically involves shredding and re-melting, processes which are both energy-intensive and challenged by the presence of metallic contaminants. To mitigate these issues, this study explores an alternative approach: the re-manufacturing of deep-drawn parts directly from scrap aluminium sheets, thus bypassing the melting step. We used 2 mm thick Al-Mg sheet metal in H111 temper to produce simulated stamping scrap (miniaturized bonnets). Blanks were cut from these bonnets and secondary parts in a cross-cup geometry were deep-drawn using two different forming processes: warm-forming at 200 °C and O-temper forming at room temperature. The resulting maximum draw depths were 20-22 mm for warm-forming and 25-30 mm for O-temper forming. While warm-forming resulted in lower draw depths, O-temper forming led to coarse recrystallized grain formation in some regions. Our approach could significantly reduce the energy consumption associated with aluminium recycling.

A generalisable tool path planning strategy for free-form sheet metal stamping through deep reinforcement and supervised learning

AbstractDue to the high cost of specially customised presses and dies and the advance of machine learning technology, there is some emerging research attempting free-form sheet metal stamping processes which use several common tools to produce products of various shapes. However, tool path planning strategies for the free forming process, such as reinforcement learning technique, derived from previous path planning experience are not generalisable for an arbitrary new sheet metal workpiece. Thus, in this paper, a generalisable tool path planning strategy is proposed for the first time to realise the tool path prediction for an arbitrary sheet metal part in 2-D space with no metal forming knowledge in prior, through deep reinforcement (implemented with 2 heuristics) and supervised learning technologies. Conferred by deep learning, the tool path planning process is corroborated to have self-learning characteristics. This method has been instantiated and verified by a successful application to a case study, of which the workpiece shape deformed by the predicted tool path has been compared with its target shape. The proposed method significantly improves the generalisation of tool path planning of free-form sheet metal stamping process, compared to strategies using pure reinforcement learning technologies. The successful instantiation of this method also implies the potential of the development of intelligent free-form sheet metal stamping process.

Analysis and optimization of stamping and forming process of bearing outer ring

To address the common issues of wrinkling, tearing, and uneven wall thickness in the actual sheet metal stamping process of the outer ring of needle roller bearings, this study analyzes critical technical indicators such as forming limits, thickness distribution, and principal strains in the forming process in detail. Three-dimensional models of the concave and convex dies were constructed. The effects of different process parameters, including stamping speed, edge pressure, sheet metal thickness, and friction coefficient, on the quality of the forming parts were investigated by varying these parameters. Subsequently, the orthogonal experimental method was used to determine an optimal experimental group from multiple sets of experiments. It was found that under the process parameters of a stamping speed of 3000 mm/s, edge pressure of 2000 N, sheet metal thickness of 0.9 mm, and friction coefficient of 0.125, the forming quality of the outer ring of the bearing is ideal.

Deep Learning Approach for automatic detection of split defects on sheet metal stamping parts

Sheet metal stamping processes are used primarily for high-volume products produced for a range of sectors, from white goods manufacturing to the automotive and aerospace sectors. However, the process is susceptible to defects. Due to the numerous potential defects that may arise in the stamping product, human inspectors are often deployed for their detection. However, they are unreliable and expensive, especially when operating at production speeds equivalent to the stamping rate. This study investigate CNN-based automatic inspection for stamping defects. The study carried out two sets of experiments. All the Experiments yielded high classification accuracy, recall and precision demonstrating the viability of the CNN method for defect detection in the sheet metal stamping process. Additionally, this study revealed that in limited data confounding factors can be a challenge. The second experiment further explored the impact of small neck defects, harsh lighting and reflections on defect detection. The observations indicated that the model struggled to identify defects occluded by reflections, particularly small neck defects.

Contribution to the formability improvement in sheet metal stamping by a novel technique to control press kinetics

The thickness variation during sheet deep drawing process has an impact on the quality of the final product and can lead to local material fractures. To minimize this phenomenon caused by varying degrees of stretching in different areas of the sheet, various methods can be employed. This research paper introduces a novel technique for metal sheet deep drawing, specifically designed for parts with complex geometric shapes that exhibit significant variations in deformation levels across different areas. The objective of this method is to enhance the quality of the deep drawing process by reducing thickness variations in the final part. In this proposed approach, the vertical movement of the punch is accomplished through two vertical rotational movements. This increases the flexibility of the deformation process, ensuring that the active tools elements occupy the most advantageous positions determined by the material flow in the die. As a result, the material's deformability is improved, allowing for a higher degree of deformation. Additionally, this new method offers a relatively simple design and kinematics solutions for the press and eliminates the need for lengthy assembly-disassembly times.

Formation of reflective shells by electric arc spraying and application of composite material to the punch

In the course of the work, the process of forming reflective shells and finding the position of grid elements after deformation was investigated. Fixation of mesh nodes by electric arc spraying. After that, a composite material such as polystyrene is applied to form reflective shells. Minimization of potential energy is carried out numerically by an iterative method. The result of the work is the formation of the antenna array shell by the method of electric arc spraying and the application of the composite material. The following forming operations of sheet metal stamping are known: drawing, rotary drawing, relief forming, trimming, including rubber and liquid drawing, hydromechanical drawing, explosion drawing, electric discharge stamping, electromagnetic stamping, hydropneumatic drawing, which allow to obtain a shell from sheet material (solid or gas and water permeable) by pressing it against a die or punch with a transfer medium.

Numerical analysis of maximum force in deep drawing processes of prismatic parts

The high competitiveness of the industrial sector and the short time for developing new products drives the use of process analysis tools that enable speeding up the design phase. In sheet metal stamping projects, numerical simulation has become indispensable. As a replacement for traditional trial-and-error methods, the finite element method (FEM) enables the optimization of process-related variables. Consequently, it is possible to mitigate some of its main problems, such as the emergence of fracture, wrinkling, and springback. A second alternative for analyzing the process, even faster and cheaper, is based on the use of analytical calculations. These can predict, among other parameters, the forces involved in stamping. This study aims to evaluate the degree of accuracy of equations predicted in the literature to estimate the maximum stamping force of non-axisymmetric parts. For this purpose, analytical results of the stamping force of 1 mm thick austenitic stainless steel AISI 304 sheets were compared to results obtained via numerical simulation.

PROSES PEMBUATAN PLATE HOOK FUEL LID MENGGUNAKAN MESIN STAMPING PRESS

When starting to do practical work at PT Persada Selaras Indonesia several problems were found, one of which was why the SPHC-PO material was used in the production of Plate Hook Fuel Lid and how the production process was used Stamping Sheet Metal Press in the production process using the Blanking and Bending processes Based on the process of making the Plate Hook Fuel Lid, this practical work has the goal of knowing the working process of the Stamping Press machine. The methods used in this practical work are the process of observing, summarizing and recording data from sources and hard copies from PT. Persada Selaras Indonesia After carrying out the methods systematically obtained several results from practical work, including being able to make a product using a Stamping Press machine and recognizing the flow of the production process in the automotive part industry

Industrial Application of Surface Crack Detection in Sheet Metal Stamping Using Shift-and-Add Speckle Imaging

Industrial Application of Surface Crack Detection in Sheet Metal Stamping Using Shift-and-Add Speckle Imaging

Improving shape formation under conditions of plane tensile stress

Thin-walled axisymmetric truncated parts made of sheet billets are actively used in rocket and aerospace engineering. Improvement to their shape formation, based on directed material thickness change will ensure the production of parts with minimum thickness variation. This will also enable aviation and space industry enterprises to attain leading positions, as well as reduce labor costs. This work studies the possibility of obtaining thin-walled axisymmetric parts of truncated tapered shape using one of the methods of sheet metal stamping under flat tensile stress conditions (flanging). The mechanism was identified and the analysis of the stress-strain state of the billet during deformation was carried out. This takes into account the minimizing of the difference between the specified and technologically possible thicknesses. A mathematical model was developed to consider the shaping method based on the process of flanging. Theoretical studies were based on the principles of the plastic deformation theory of sheet materials. This was achieved by the following factors: approximate differential equations of force equilibrium; equations of constraint; plasticity conditions; and fundamental constitutive relations under given initial and boundary conditions. The process of flanging was simulated using the LS-DYNA software package with the following initial data of a conical billet made of 12Kh18N10T steel: cone angle 16.4°, thickness Sbillet = 0.3 mm. The aim was to eliminate errors in designing a tool for future implementation of the method on a manufactured die tooling, as well as to confirm the theoretical conclusions on the selection of technological parameters and achieve minimal thickness variation. The steps of computer modeling are presented, indicating the main process parameters such as material model, mechanical characteristics of the workpiece material, type of elements, kinematic loads, conditions of contact interaction of elements with each other, etc.

Design, performance, and cost savings of using GF-PC additively manufactured tooling for stamping of HSS 590 sheet metal

Conventional sheet metal forming tooling in the automotive industry is made up of hardened steel and used for mass-production. Prototype tooling made of metal is durable, but it is only used for a small number of parts despite its high cost, contributing heavily to the vehicle development cost. Additive Manufacturing (AM) offers a low-cost alternative for fabricating tooling suitable for low-volume production. This study investigates the feasibility of using AM polymer composite tooling for the stamping of 1.5 mm thickness HSS 590 steel sheets through a two-pronged approach – experimental and numerical analysis. Sheet metal stamping experiments were conducted with glass fiber reinforced polycarbonate (GF-PC) AM polymer tooling and their performance was evaluated based on various metrics such as tool deformation and part accuracy. Finite element simulations of the stamping process were performed, which accurately captured the tool deformations seen in experiments with the use of anisotropic material models. The effective use of simulations in optimizing process parameters to achieve the desired final part geometry is also demonstrated. The GF-PC AM polymer composite tooling was found to be well suited for low volume production applications with potential cost savings.

An evaluation method for experimental necking detection of automotive sheet metals

In sheet metal stamping, the occurrence of strain localization in a deformed sheet is considered a failure. As so, sheet metal’s formability is conventionally evaluated using the Forming Limit Diagram (FLD), which separates the principal strain space into safety and unsafety regions by a Forming Limit Curve (FLC). This study presents an evaluation method for detecting strain localization based on Digital Image Correlation (DIC) during the experiment. The commercial DIC software ARAMIS is adopted to monitor the strain-field distribution on the deformed specimen’s surface. A detailed analysis of the proposed method is presented considering Nakajima tests conducted for two automotive sheet metals: AA6016 and DP800. The identified FLC based on the proposed method is compared with that of well-established methods such as ISO 12004:2-2008 and time-dependent methods. For both investigated materials, the proposed method presents a lower FLC than the others.

Modeling the strain localization of shell elements subjected to combined stretch–bend loads: Application on automotive sheet metal stamping simulations

This study presents a modeling approach for predicting strain localization during sheet metal stamping processes focused on automotive engineering applications. The so-called stretching-to-bending ratio, ρ, is proposed to characterize the loading conditions acting on an element during stamping processes. Then, localized strain or necking strain is suggested to be a function of ρ. Different stretch–bending tests with different tool radii, i.e., R3, R6, R10, and R50 are conducted for two automotive sheet metals, DP800 and AA6010, to identify their forming limits under combined stretch–bend loads. The calibrated necking limit curve of the AA6016 sheet is then employed in AutoForm R10 software to predict the necking and failure of a stamped panel. Agreement with the experimental observation of failure positions of the panel validates the usefulness of the proposed modeling approach in practice.

A Data-Based Tool Failure Prevention Approach in Progressive Die Stamping

The research on methods for monitoring sheet metal stamping is benefiting from the increased availability of enabling technologies such as sensors, data mining software, cloud computing, and artificial intelligence. The predictive maintenance policies of tools (punches and dies) can be targeted at monitoring progressive wear or at the detection of sudden failures or anomalies. Early detection of tool failure is the method preferred by the recent literature on data management in sheet metal stamping. However, the stamping of small parts poses challenges due to multiple tools and signals and limited visibility of die wear, requiring management of multiple sensors and data sources. This paper proposes a failure prevention approach for progressive die stamping using global and local force sensors with upper bounds for maximum values to indicate unhealthy conditions. The methodology was tested on millions of small washers made of carbon steel. The stamping process was implemented using a servo-press with a high rate. The press was equipped with eight in-process sensors, including strain gauges, thin foil force sensors, and acoustic sensors. The data of material properties, maintenance reports, statistical process control data, and in-process sensors were collected and stored in a data lake. By combining the in-process sensor acquisition with the corresponding log events and maintenance data in the same time span, it is possible to look for correlations among the variables and build an effective tool health prevention policy.

Effect of pre-strain on microstructure and stamping ability of TA2 titanium alloy and H260 low-alloy steel

Applying pre-strain can not only change the microstructure and the mechanical property of metal material but also affect sheet metal stamping ability. In this paper, taking H260 low-alloy steel and TA2 titanium alloy as experimental materials, pre-strain ranging from 0 to 0.16 was applied using the one-step and the multi-step method respectively. Microstructure observation, tensile test, bending test, and cup bulging test were conducted on the pre-strained samples. Results show that in the pre-strain loading stage, the slipping and twinning deformation occurs in the TA2 alloy sample while dislocation sliding mainly happens in H260 low-alloy. With pre-strain increasing, the product of ultimate tensile strength and elongation rate gradually decreases, and the true ultimate tensile stress and accumulating elongation change rarely. The “product of yielding strength and elongation rate” can be enhanced by applying a pre-strain of 0.04 on the condition that plasticity is still at a high level. In the pre-strain range of 0 - 0.16, a bending test with a 30.8 °-opening angle can be completed on H260 steel. The springback angle changes from negative to positive with an increase in pre-strain. The bending ability of TA2 titanium alloy is very poor, for a crack can easily occur even in the original sample. The cupping value decreases gradually with an increase in pre-strain. The cupping value of TA2 titanium alloy is higher than that of H260 low alloy steel for the constant pre-strain. A quite large difference exists between the two experimental materials. Pre-strain loading pass has no significant effect on the microstructure evolution, mechanical properties, and stamping properties.

HDR image-based deep learning approach for automatic detection of split defects on sheet metal stamping parts

Sheet metal stamping is widely used for high-volume production. Despite the wide adoption, it can lead to defects in the manufactured components, making their quality unacceptable. Because of the variety of defects that can occur on the final product, human inspectors are frequently employed to detect them. However, they can be unreliable and costly, particularly at speeds that match the stamping rate. In this paper, we propose an automatic inspection framework for the stamping process that is based on computer vision and deep learning techniques. The low cost, remote sensing capability and simple implementation mean that it can be easily deployed in an industrial setting. A particular focus of this research is to account for the harsh lighting conditions and the highly reflective nature of products found in manufacturing environments that affect optical sensing techniques by making it difficult to capture the details of a scene. High dynamic range images can capture details of an environment in harsh lighting conditions, and in the context of this work, can capture highly reflective metals found in sheet metal stamping manufacturing. Building on this imaging technique, we propose a framework including a deep learning model to detect defects in sheet metal stamping parts. To test the framework, sheet metal ‘Nakajima’ samples were pressed with an industrial stamping press. Then optimally exposed, sequence of exposures, tone-mapped and high dynamic range images of the samples were used to train convolutional neural network-based detectors. Analysis of the resulting models showed that high dynamic range image-based models achieved substantially higher accuracy and minimal false-positive predictions.

Research on springback compensation for multi-point forming of corrosion-resistant aluminum alloy hyperbolic component

Springback is the reverse elastic deformation produced by the unloading process, which is a common phenomenon in the sheet metal stamping and forming process and affects the final forming accuracy of the part. Aiming at the problem of springback error in the multi-point forming process of hyperbolic component for ships, the springback phenomenon of hyperbolic component was studied by combining theoretical analysis, numerical simulation and forming test. The mechanical property parameters and stress-strain curves were obtained by tensile tests using a new corrosion-resistant aluminum alloy as the sheet material. The springback compensation method is introduced, the springback compensation formula based on surface curvature is derived, and the compensated mold surface is further corrected and fitted using the cubic B-sample method. The multi-point punch tooling was generated and modeled by the multi-point 3D modeling software MPFCAD and finite element software to simulate the multi-point forming and unloading springback process of the hyperbolic member. Multi-point forming tests were conducted on a multi-point forming press for corrosion-resistant aluminum alloy hyperbolic component, and the formed parts were checked for accuracy and error analysis by 3D scanning and GOM Inspect software. The results show that the springback compensation method used in this paper can effectively reduce the springback error in the multi-point forming process of corrosion-resistant aluminum alloy hyperbolic component, and the effect is very good.

Online monitoring of manufacturing processes by acoustic emission

For many years, Cetim has been working on on-line control methodologies for manufacturing processes in order to reduce or even eliminate controls on finished parts. After the first works by conducted by the Acoustic Emission technique (AE) on the monitoring of sheet metal stamping process [1], the monitoring of new manufacturing processes such as metal cutting, wire drawing, spot welding, forging and especially are under study. In the present paper, the results of acoustic emission monitoring carried out on additive manufacturing production and also wire drawing are presented. For both processes on-line control during manufacturing is particularly important. Due to the geometric complexity of the parts produced by additive manufacturing, suitable nondestructive testing (NDT) means are limited. In addition, these are generally small series or even single parts with a long manufacturing time. For their part, wire drawing manufacturers currently have only visual inspection, unable to detect fine scratches on the wire at the output of production.

Determining the optimum cut of sheet roll material

The profitability of forging and stamping plants is directly related to the economical use of raw materials. For sheet metal stamping, material losses can account for a significant proportion (up to 20-40%), so reducing them even by a few percent saves thousands of tonnes of sheet metal. An indicator of material utilisation efficiency and rationality of cutting is a material utilisation factor η, defined as a ratio of the weight of the workpiece to the rate of material consumption for its production. The value of material efficiency depends largely on the shape of the manufactured part, its location on the sheet (strip), and the size of the sheet (strip). One of the ways to save sheet material is by transferring parts from individual sheets to stamping directly from the sheet roll. Calculations for some types of products showed that the transition from pre-cutting of metallurgical rolling on guillotine or disk shears to cutting directly from the roll gives more than 3% of savings, and with chess-cutting this economy increases by 3-5 times. Bearing this in mind, it is of interest to find the optimum, in terms of economy of material, cutting of sheet coils when cutting out parts of various shapes, including round ones. This study solves the problem of determining a rational variant of sheet coil cutting for different sizes of sheet coils supplied by factories and diameters of cut out circles.

Isogeometric algorithm for one-step inverse forming of sheet metal

The isogeometric one-step inverse forming method aims to predict the shape of blanks and the formability of stamping parts using accurate geometry without meshing. In this paper, the discrete surface Ricci flow algorithm in computational conformal geometry is introduced as an unfolding algorithm for one-step inverse forming of isogeometric membrane elements. A combination of discrete surface Ricci flow algorithm and elastic iteration is proposed to predict the initial solution. It is proved applicable, even for the extremely curled parts which have negative angles and vertical walls. In addition, we propose a method that the external force of the punch is equivalent to the control point by means of Greville abscissae. A nonlinear equation system is established based on the principle of minimum potential energy. The Newton–Raphson iteration is used to calculate the blank shape and the thickness distribution of the stamping parts. The examples of square box, flower box, and L shape prove that the algorithm can predict the contour of the initial configuration and the formability of sheet metal stamping.