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In this study, the focus is on investigating prevalent issues of rupture and wrinkling that occur during the extra-deep drawing process. These defects are very common in a local sanitary equipment industrial company, mainly in the manufacture of bathtubs, which increases scrap and leads to loss of time and costs in production. To analyze these defects, a numerical simulation of the bathtub extra-deep drawing process was performed with industrial parameters. The originality lies in controlling non-uniform blank holder pressures generated from six actuators in order to control the flow of the blank between the blank holder and the die and ensure the production of defect-free bathtubs. 3D and ultrasonic thickness measurements were performed on a bathtub manufactured without defects. Numerical and experimental plots of the thickness reduction show that the two approaches are in good agreement. The numerical results demonstrate that there are no rupture or wrinkling defects in the bathtub final shape, which exactly matches the actual case manufactured by the company. The numerical analysis was also performed on different cases that can cause rupture and wrinkling defects, namely: the influence of the blank holder pressure, the blank initial shape, and the die design using draw beads. [ABSTRACT FROM AUTHOR]

Several studies have explored analytically predicting forming limits in processes like hydroforming and incremental forming, yet there's a lack of discussion on effective experimental methods. This paper introduces hydro-assisted incremental forming (HAIF) as a hybrid technique combining incremental forming and hydromechanical deep drawing, resulting in improved formability through simultaneous application of normal and through-thickness stresses. A novel test method is devised based on this process, and forming limits are assessed through both experimental and finite element approaches. The authors' earlier analytical forming limit predictions are scrutinized using experimental tests and simulations, revealing a good match. The study reaffirms that the application of normal and through-thickness stresses enhances formability across various strain paths, especially in plane strain mode. [ABSTRACT FROM AUTHOR]

This work is concerned with forming, specifically deep drawing, and its influence on the micro-mechanical properties of sheet metal. In practice, there are several applications in which fractions can occur due to weak spots in the deep-drawn sheet metal, especially after long-term use. The deep drawing process was carried out on BUP–600 machines using the LHD (Limiting Dome Height) method, which uses a forming tool with a diameter of 100 mm and bead groove. Sheet metals X8CrMnNi19-6-3 (1.4376) with thicknesses of 1, 1.5, and 3 mm were selected for this process. To study the effect of a lubricant on the formability of the sheet metal, deep drawing without and with a lubricant was compared. An FEM analysis was conducted to identify critical points in the deep drawing process, and the results were later compared with real results. The analysis was conducted using the AutoForm program. The micro-mechanical properties of these points were subsequently examined. The specified points on the formed part showed significant differences in their micro-mechanical properties, suggesting a higher strength but also less resistance to fractures. The difference in micro-mechanical properties (indentation and Vickers hardness) in points that were not deep-drawn and points located in critical areas was up to 86%. Significant changes in behavior were found in the indentation modulus and plastic/elastic deformation work as well. This study demonstrates the significant effect of the use of a lubricant in achieving the deep drawing of the sheet metal. The application of a lubricant resulted in a 33% increase in drawing range compared to drawing without lubrication. This study has a significant influence on the deep drawing of sheet metals in practice, showing the fundamental influence of the lubricant on the drawing process and also showing the problem of critical points that need to be eliminated. [ABSTRACT FROM AUTHOR]

In directional forming processes, such as rolling and extrusion, the grains can develop preferred crystal orientations. These preferred orientations—the texture—are the main cause for material anisotropy. This anisotropy leads to phenomena such as earing, which occur during further forming processes, e.g., during the deep drawing of sheet metal. Considering anisotropic properties in numerical simulations allows us to investigate the effects of texture-dependent defects in forming processes and the development of possible solutions. Purely phenomenological models for modeling anisotropy work by fitting material parameters or applying measured anisotropy properties to all elements of the part, which remain constant over the duration of the simulation. In contrast, crystal plasticity methods, such as the visco-plastic self-consistent (VPSC) model, provide a deeper insight into the development of the material microstructure. By experimentally measuring the initial texture and using it as an initial condition for the simulations, it is possible to predict the evolution of the microstructure and the resulting effect on the mechanical properties during forming operations. The results of the simulations with the VPSC model show a good agreement with corresponding compression tests and the earing phenomenon, which is typical for cup deep drawing. [ABSTRACT FROM AUTHOR]

The research intends to produce conventional and intricate shapes using a deep drawing operation experimental work and finite element analysis (FEA). So, to perform experiment work, the dies of deep drawing were designed, manufactured, and then employed to produce the mugs of cylindrical and polygonal shapes from low-carbon steel (1008-AISI). In addition, a commercial software program, ANSYS (workbench), was applied to perform the numerical analysis. The research aim is to create conventional (cylindrical) and intricate (polygonal has eight edges) shapes in a deep drawing process and compare the experimental work results and the FEA of both shapes. The comparison saw that with the intricate shapes, the maximum drawing force demanded to create a polygonal mug registered at 39.865 and 33.675 kN with the cylindrical mug. The maximum effective strain registered was 0.4542 with mugs of intricate shapes. Conventional shapes (cylindrical) are easier than the production of intricate shapes (polygonal has eight edges) by employing the deep drawing operation. [ABSTRACT FROM AUTHOR]

The process of deep sheet metal drawing is accepted in all industrial branches. This process is, therefore, very important to maintain a certain level of quality. For this reason, measurements and tests must be carried out to determine how much sheet metal deformation occurred after the deep drawing process. For this purpose, an experiment of deep drawing of sheet metal was carried out using the example of kitchen utensils. In addition, the Taguchi method was used in this experiment to test the quality of the obtained kitchenware. In the experiment, three factors were taken with three alternatives that affect the deep drawing of sheet metal, and 27 experiments were used for the Taguchi method. The results of this experiment showed that the best results were achieved by the smallest drawing depth of 65 mm and the worst results were obtained by the drawing thickness of 70 mm. Regarding the thickness of the material, the best results were achieved by the material of 21 mm, and the material of 15 mm achieved the worst results. In addition, an analysis of variance was carried out, which determined the relationship between force and deformation of the material. [ABSTRACT FROM AUTHOR]

Laser welding is particularly relevant in the industry thanks to its simplicity, flexibility and final quality. The industry 4.0 and sustainable manufacturing framework gives massive attention to in situ and non‐destructive inspection methods to predict laser weld final quality. Literature often resorts to supervised Machine Learning approaches. However, selecting the ApTest method is non‐trivial and often decision making relies on diverse and unclearly defined criteria. This work addresses this task by proposing a statistical comparison method based on nonparametric tests. The method is applied to the most relevant supervised Machine Learning approaches exploited in literature to predict laser weld quality, specifically, considering the optimisation of a new production line, hence focussing on supervised Machine Learning methods that do not require massive data set, that is, Generalized Linear Model (GLM), Gaussian Process Regression, Support Vector Machine, Classification and Regression Tree, and Genetic Algorithms. The statistical comparison is carried out to select the best‐performing model, which is then exploited to optimise the production process. Additionally, an automatic process to optimise Machine Learning models and process parameters is resorted to, basing on Bayesian approaches, to reduce operator effect. This work provides quality and process engineers with a simple framework to compare Machine Learning approaches performances and select the most suitable process modelling technique. [ABSTRACT FROM AUTHOR]

In sheet metal forming, persistent challenges such as failure, wrinkling, and springback necessitate innovative solutions. This study elucidates a novel methodology tailored to mitigate these prevalent defects. Our primary aim was to bolster formability while concurrently diminishing defects throughout the forming cycle. To realize this objective, we deployed a segmented and variable blank holder force (S-VBHF) trajectory, facilitating precise adjustments to the blank holder force (BHF). In our quest to optimize process parameters, encompassing the S-VBHF, friction coefficient, and drawbead restraining force (DBRF), we amalgamated deep neural network, genetic algorithm, and Monte Carlo simulation techniques, collectively denoted as DNN-GA-MCS. The forming limit diagram (FLD) served as our rigorous evaluative framework, enabling a comprehensive assessment of sheet failure dynamics during the forming phase. Our proposed methodology underwent stringent validation via numerical simulations, with the cylindrical cup from NUMISHEET 2011 (BM1) providing the benchmark. Empirical outcomes underscored substantial enhancements in formed sheet quality: marked reductions of 8.33% in failure, 10.81% in wrinkling, and 5.88% in springback. In summation, our advanced methodology manifests potential in refining sheet metal forming processes, emphasizing its efficacy in substantially curtailing defects. [ABSTRACT FROM AUTHOR]

Lubrication is one of the key factors to improve metal-forming quality. In the process of deep drawing, seizing tumors easily occur on the contact surfaces between the tantalum metal and the mold, which greatly affects the forming quality of the deep-drawn parts. Quality-forming quality problems that occur during the deep drawing of tantalum metal are studied from the perspective of lubrication in this paper. Three lubrication media, caster oil, PE (polyethylene) film, and DLC (Diamond Like Carbon) film, were adopted in the deep drawing of tantalum cylindrical cups. A universal testing machine and microscope were used to investigate the effect of lubrication media on the limit-drawing ratio, maximum forming force, and surface topography quality during the deep drawing process of the tantalum sheet. The results reveal that the lubrication of the PE film and DLC film can greatly improve the forming quality of the tantalum metal sheet, in which the DLC film has higher wear resistance and lower friction coefficient and can be used as the lubricating medium in the industrial forming process of tantalum deep-drawn parts. [ABSTRACT FROM AUTHOR]

In order to improve predictive capabilities of numerical simulations, Yld2000-2D yield criterion is used to model the plastic anisotropic behaviors of AA5086 sheets. The parameters of Yld2000-2D yield criterion are identified based on the traditional testing strategy and the inverse identification strategy, respectively. The traditional testing strategy considers uniaxial and equi-biaxial tensile tests. The inverse identification strategy relies on the finite element model update (FEMU) method that couples with a biaxial tensile test using a dedicated cruciform specimen or the Pottier bulging test. The identified parameters are preliminarily evaluated by comparing predicted and experimental yield stresses, r-values, and yield loci. Then, the deep drawing test and simulations are performed. The identified parameter sets of Yld2000-2D yield criterion are further evaluated in terms of practical forming by comparing the predicted earing profile height with the experimental results. The results show that the inverse identification strategy can be an effective alternative to identify the parameters of Yld2000-2D yield criterion, and a well-designed heterogeneous test could lead to a better identification result. [ABSTRACT FROM AUTHOR]

Given the use of high-strength steels to achieve lightweight construction goals, conventional shear-cutting processes are reaching their limits. Therefore, so-called high-speed impact cutting (HSIC) is used to achieve the required cut surface qualities. A new machine concept consisting of linear motors and an impact mass is presented to investigate HSIC. It allows all relevant parameters to be flexibly adjusted and measured. The design and construction of the test bench, as well as the mechanism for coupling the impact mass, are described. To validate the theoretically determined process speeds, the cutting process was recorded with high-speed cameras, and HSIC with a mild deep-drawing steel sheet was performed. It was discovered that very good cutting edges could be produced, which showed a significantly lower hardening depth than slowly cut reference samples. In addition, HSIC was numerically modelled in LS-DYNA, and the calculated cutting edges were compared with the real ones. With the help of adaptive meshing, a very good agreement for the cutting edges could be achieved. The results show the great potential of using a linear motor in HSIC. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In solving technological problems related to sheet metal deep drawing with the use of computer tools, the key issue is still the correct determination and entering of boundary conditions to FEM-based software. The procedure for preparing input data for modelling such processes includes geometric data (drawing of tools and material), technological parameters along with the contact conditions between the workpiece and the tools (friction model and type of lubricant) and material properties, in which work-hardening curves are of particular importance. In typical material databases of FEM-based software and designed for computer modelling of deep drawing processes, the properties of only a small number of material grades are available, and commercial software producers charge additional fees for each additional quantity. Those properties that are already in the database are usually devoid of basic information, e.g. related to the state of the material (material after recrystallization, annealing, cold working has different properties). In paper, experimental tests were carried out to determine flow curves based on cold tensile curves for flat samples made of EN-AW 1050A aluminium, Cu-ETP copper, CuZn37 brass and S235JRG2 steel. The investigation used a universal testing machine with a 20 kN pressing force, equipped with specialized Test&Motion software for measuring forces and displacements. It was calibrated and satisfies the metrological requirements for class 0.5. A comparative analysis of the curves determined by the analytical method was carried out. The material models obtained in the experimental tests were used in the computer simulation of the deep drawing processes of cylindrical drawpieces in the ABAQUS software. The results were experimentally verified in terms of comparing the changes in the pressing forces as a function of the displacement of the punch. The results obtained in the research can be used in industrial practice for computer-aided design of cold-deep drawing processes for drawpieces of various shapes from the discussed materials. [ABSTRACT FROM AUTHOR]

Deep drawing is one of the most important and vastly conducted sheet metal forming method. Thus, even small improvements achieved on the deep drawability of sheet metals significantly increases the ability of sheet metal to be formed into more complex products. Advanced high strength steels (AHSSs) are one of the most popular steels in the automotive industry due to their high strengths. However, their low ductility causes considerable splitting problems on the shop floors. In this study, deep drawing experiments have been conducted in conical dies with four different angles (0⁰, 7.5⁰, 12.5⁰, and 20⁰) for DP800 and MART1400 steels to observe whether a higher deep drawing ratio (DDR) can be achieved by deep drawing in conical dies for AHSSs. In addition, finite element analysis (FEA) has been utilized to estimate the DDR for each types of steels in different conical die setups. It has been observed that the deep drawing ability of MART1400 steel has not improved in any of the conical die setups. However, DDR of DP800 has slightly increased by 2.46% by deep drawing with 20⁰ die angle. A good agreement with the numerical and experimental results has been achieved. [ABSTRACT FROM AUTHOR]

In this study, Ultrasonically Assisted Deep Drawing Process was developed in order to improve formability of sheet metals in Conventional Deep Drawing Process. Effects of ultrasonic vibrations, applied onto the blank holder in axial direction, on formability of sheet metal were investigated numerically by finite element analyses, and the results of such analyses were verified by deep drawing experiments. In the numerical study, a methodology for two-stage finite element analyses including transient structural and forming analysis was developed. In conventional and ultrasonically assisted deep drawing analyses, limiting drawing ratios and maximum drawable cup depths for DC01 and DC04 materials prone to certain process parameters were compared. With application of ultrasonic vibrations, an increase of up to 9% in limiting drawing ratio and up to 26% in cup depth were achieved. In the analyses performed on circular materials of identical diameters, it was determined that the thinning on sheet metal decreased by up to 43%. As result of the validation experiments, increase in limiting drawing ratio and cup depth was achieved as 11% and 31%, respectively. Numerical results were found to be in good agreement with experimental results since dynamic impact, stress superposition and contact separation effects of ultrasonic vibrations could be effectively modeled in finite element analyses with the proposed method. Small differences in obtained results may be due to the reason that it was not possible to involve the effects of acoustic softening and friction coefficient reduction on the material in numerical analyses. [ABSTRACT FROM AUTHOR]

The present paper proposes a mathematical development of the plasticity and damage approaches to simulate sheet metal forming processes. It focuses on the numerical prediction of the deformation of the sheet metal during the deep drawing process when a crack appears. Anisotropic plasticity constitutive equations are proposed. A fully implicit integration of the coupling constitutive equations is used and leads to two nonlinear local scalar equations that are solved by Newton's method. The developed model allows predicting the onset of cracks in sheet metals during cold forming operations. The numerical model is implemented in ABAQUS software using user-defined subroutines, which are VUMAT and UMAT. The accuracy of the anisotropic elastoplastic model fully coupled with ductile damage is evaluated using numerical examples. [ABSTRACT FROM AUTHOR]

Rapid tooling is a methodology which aims to integrate additive manufacturing into the production of tools to be used in casting, forming or machining processes. In forming, rapid tooling is applied in the production of metallic or plastic tools that guarantee good performance in small- and medium-sized batch production. However, most punches tested to date have dimensions measured in millimeters and are therefore unsuitable for typical real-world industrial processes. In this study, the performance of plastic punches with geometries designed for industrial application was investigated. A deep drawing process involving AISI 304 blanks was created for the manufacturing of cups. Experimental and numerical analyses were conducted to measure the quality of the cups produced and the behaviour of the punches involved. The results indicate that when punch dimensions increase, a more precise cup geometry is produced (99% of drawing depth, 98% of cup precision on the fillet radius, and roundness error equal to 0.53%). [ABSTRACT FROM AUTHOR]

In the deformation machining (DM) approach, the machining and incremental forming operations are combined to utilize the strengths of the two processes to produce monolithic components with thin structures using a single setup. DM offers a high degree of flexibility to manufacture monolithic components in comparison to conventional techniques. Some freeform monolithic products are difficult to machine with the 3-axis machining approach due to restricted entry of the tool in certain portions of the geometry. This paper presents a novel double-sided deformation machining (DSDM) technique to manufacture freeform double-sided monolithic components. As a test case, a double-sided monolithic impeller-shaped structure with freeform blades is manufactured with the proposed technique. For this, first, a blank is machined to create the required structure and blades of desired thickness. These machined structures are used as preforms for the incremental forming (bending) of the blades to the final shape. As the existing commercial toolpath development packages are not compatible with the DM process, a novel feature-based double-sided combined machining-forming toolpath is developed for the DSDM operation. Here, the blades are deformed separately and sequentially. This avoids the collision issue and achieves a faster forming operation. To evaluate the quality of the monolithic components developed, a few response parameters, like the process forces, the geometrical accuracy in terms of springback, and the surface roughness, are reported. [ABSTRACT FROM AUTHOR]

In this paper, the deformation law of box-shaped parts drawing was analyzed, and the mathematical expression for calculating the critical fracture blank holder force (BHF) was deduced. In order to determine the fracture parameters of 08Al sheet, notched specimen tensile tests were conducted, the full-field strain of the specimens from deformation to fracture was obtained by the digital image correlation (DIC) technology. The evolution law of the stress triaxiality and Lode parameter with plastic deformation was obtained, and the fracture parameters of the modified Mohr-Coulomb (MMC) fracture criterion were fitted by the least squares method. The finite element (FE) simulation model coupled with MMC ductile fracture criterion was established to simulate the fracture behavior of sheet. The reliability of theoretical calculation was evaluated by FE simulation and experiments under various process conditions. The results demonstrated that the prediction of the critical fracture BHF by theoretical calculation and FE simulation were both partial safety predictions and all fracture earlier than the tests. In the theoretical calculation, when the flange shrinkage rate was 0.19, the critical BHF was the smallest, and the error was 17.5% compared with the tests, the theoretical calculation was closer to the test results. The theoretical calculation and FE simulation coupled with ductile fracture criterion provide a reference value for predicting the critical fracture BHF and intelligent control in actual production. [ABSTRACT FROM AUTHOR]

The failure of bearings can have a significant negative impact on the safe operation of equipment. Recently, deep learning has become one of the focuses of RUL prediction due to its potent scalability and nonlinear fitting ability. The supervised learning process in deep learning requires a significant quantity of labeled data, but data labeling can be expensive and time-consuming. Cotraining is a semisupervised learning method that reduces the quantity of required labeled data through exploiting available unlabeled data in supervised learning to boost accuracy. This paper innovatively proposes a cotraining-based approach for RUL prediction. A CNN and an LSTM were cotrained on large amounts of unlabeled data to obtain a health indicator (HI), then the monitoring data were entered into the HI and the RUL prediction was realized. The effectiveness of the proposed approach was compared and analyzed against individual CNN and LSTM and the stacking networks SAE+LSTM and CNN+LSTM in the existing literature using RMSE and MAPE values on a PHM 2012 dataset. The results demonstrate that the RMSE and MAPE value of the proposed approach are superior to individual CNN and LSTM, and the RMSE value of the proposed approach is 54.72, which is significantly lower than SAE+LSTM (137.12), and close to CNN+LSTM (49.36). The proposed approach has also been tested successfully on a real-world task and thus has strong application value. [ABSTRACT FROM AUTHOR]

In this study research efforts have been made to unveil the ability of Cryogenic machining as a sustainable manufacturing process for deep hole drilling of AISI 1045 and Ti6Al4V. Environmental protection is the most pressing concern for manufacturers today when it comes to adverse health effects caused by cutting fluid and its disposal after usage. For better machining results, choosing the right cutting fluid is important. Investigation on drilling performance is done in terms of tool wear, hole wall temperature (HWT), circularity, surface roughness (Ra) to study the effects of input parameters such as cutting speed, coolant used, feed rate and coolant pressure. The type of coolant employed, cutting speed, feed and coolant pressure have a significant impact in determining the hole quality. Furthermore It was found that the employment of cryogenic coolant (LCo2) was effective on Ti6Al4V in compared with AISI 1045 in many output parameters. HWT of Ti6Al4V was higher compared with AISI 1045 Surface finish was better in Ti6Al4V, tool wear was considerably low while performing deep drilling on Ti6Al4V. [ABSTRACT FROM AUTHOR]

In metallurgical processes, as for example cold rolling or deep drawing of sheet metal, it is frequently observed that the crystallographic texture, and with it the anisotropic mechanical properties of a material, evolve dynamically. Hence, to describe such processes, it is necessary to model the functional dependence of anisotropic material parameters on the texture, which itself can vary locally with the different plastic strain histories. In this work, we present a new data-oriented approach to parametrize the anisotropic yield function Barlat Yld2004-18p from micromechanical simulations for different textures. This is accomplished by applying supervised machine learning (ML) methods to express the relationship between different crystallographic textures and the material parameters of the yield function. The crystallographic textures are chosen to vary continuously between a random texture on the one hand side, and a unimodal Goss or Copper texture the other. These crystallographic textures are rather common in sheet metal forming. In this way, furthermore, the transition from isotropic plasticity to a rather severe case of anisotropy can be modeled, which is thought to mimic the dynamical evolution of the texture in a metallurgical process. It is found that a regularization strategy is necessary to circumvent the known non-uniqueness between Yld2004-18p parameters and the resulting plastic yield behavior. After this regularization, a unique relationship between the material parameters and the yield onset is established, making it possible to train different ML models with excellent accuracy and generalization properties to anisotropic plastic material behavior. The trained ML models are able to reliably predict the coefficients of unknown textures even with a small amount of training data and, thus, to correctly represent the yield behavior resulting from the various textures. The proposed method represents an efficient extension of the description of anisotropic plastic yielding as it establishes a data-oriented way to explicitly consider microstructural parameters in the material description, which opens new pathways to formulate material models that include the process history. [ABSTRACT FROM AUTHOR]

In order to obtain the fracture strain of notched samples, the digital image correlation (DIC) technology is employed in this paper. The values of fracture-related state variables such as stress triaxiality and Lode parameter are obtained through mathematical transformation. The fracture parameters of Lou-Huh ductile fracture criterion (DFC) are calibrated by surface fitting with least square method, and the fracture curve is drawn and applied to the fracture prediction during deep drawing. The reliability of DFC is verified considering fracture stroke and location through tests. The results show that the fracture curve can predict the initiation and location of fracture successfully. Fractures are all predicted in advance under multiple blank holder force (BHF) conditions. Comparison results of finite element (FE) simulation and experiment show that the maximum error of fracture stroke is 12.9% and the fracture locations are generally consistent. The prediction of DFC is partial to safety. [ABSTRACT FROM AUTHOR]

A metal bushing ring is an important part of the plate heat exchanger, which plays the role of sealing, and the welding seam formed in the current forming processes shortens the life of the plate heat exchanger. A drawing-flaring process of a metal bushing ring without a welding seam is proposed, which includes deep drawing and multi-flaring processes, and the latter is the process that matters. Considering the uneven thickness after deep drawing, an analytical model is established to predict the stress and strain states, thickness distribution, flaring ratio, and driving force in multi-flaring. The whole process FE model is also established, and its reliability is validated through an experiment. Deformation characteristics, thickness distribution, flaring ratio, and driving force are studied by comparing the results of the experiment, finite element analysis (FEA), and theoretical analysis. The buckling phenomenon easily occurs in 90° flaring, so improvements are proposed to enhance the stability, which can avoid the defects. The results prove that the drawing-flaring process is feasible, and the analytical model is reliable. [ABSTRACT FROM AUTHOR]

Deep drawing is a metalworking procedure aimed at getting a cold metal sheet plastically deformed in accordance with a pre-defined mould. Although this procedure is well-established in industry, it is still susceptible to several issues affecting the quality of the stamped metal products. In order to reduce defects of workpieces, process control approaches can be performed. Typically, process control employs simple proportional-integral-derivative (PID) regulators that steer the blank holder force (BHF) based on the error on the punch force. However, a single PID can only control single-input single-output systems and cannot handle constraints on the process variables. Differently from the state of the art, in this paper we propose a process control architecture based on Model Predictive Control (MPC), which considers a multi-variable system model. In particular, we represent the deep drawing process with a single-input multiple-output Hammerstein-Wiener model that relates the BHF with the draw-in of $n$ different critical points around the die. This allows the avoidance of workpiece defects that are due to the abnormal sliding of the metal sheet during the forming phase. The effectiveness of the proposed process controller is shown on a real case study in a digital twin framework, where the performance achieved by the MPC-based system is analyzed in detail and compared against the results obtained through an ad-hoc defined multiple PID-based control architecture. Note to Practitioners—This work is motivated by the emerging need for the effective implementation of the zero-defect manufacturing paradigm in the Industry 4.0 framework. Especially in the deep drawing process, various quality issues in stamped parts can lead to significant product waste and manufacturing inefficiencies. This turns into considerable economic losses for companies, particularly in the automotive sector, where deep drawing is one of the most used cold sheet metal forming techniques. In most applications, only sample inspections are performed on batches of finished-product, with subsequent losses of time and resources. For the sake of improving the workpiece quality, innovative strategies for real-time process control represent a viable and promising solution. In this context, the proposed MPC-based process control approach allows the correct shaping of the metal sheet that is getting deformed during the forming stroke, thanks to the draw-in monitoring at various locations around the die. The draw-in is indeed one of the most effective forming variables to control in order to provide a correct BHF during the forming stroke. A useful and easy-to-implement non-linear metal sheet deep drawing process model is provided by this paper to perform an innovative process control strategy. A comprehensive methodology is applied in detail to an automotive case study, ranging from process modeling (model identification and validation based on experimental data acquisition) to MPC implementation (controller tuning and testing and software-in-the-loop system validation). The presented method can be easily implemented on any real deep drawing press, providing the multivariable constrained process with a suitable control system able to make the stamped parts well formed. [ABSTRACT FROM AUTHOR]

Laminates made of metal—glass fiber-reinforced polymers—metal layers require material parameters for each constitutive model of the constituents. First, although parameter identification for metallic materials has been frequently discussed, the stepwise identification of material parameters in terms of uncertainties of previously determined parameters is investigated by the concept of error propagation. Second, the calibration of a model of orthotropy describing the large deformation behavior of the glass fiber-reinforced kernel layer is a challenging process, especially against the background of a reliable determination of the parameters. The main problem is related to the lack of available experiments. This issue is embedded in the concept of local identifiability. Thus, the article provides experiments to determine the parameters of both the steel as well as the glass fiber-reinforced polymers. Particularly for the latter issue, μ -CT data is chosen to provide a representative volume element, where all deformation modes can be investigated. In this sense, a concept to determine all material parameters in a locally unique and reliable manner is studied. A linear error propagation concept provides the uncertainty of the resulting material parameters of the whole parameter set for the homogenized material. The entire parameter identification process is discussed thoroughly, and validation examples such as bending and deep drawing in metal forming processes, are provided to estimate the prediction accuracy. In this respect, the uncertainties found by parameter identification are applied to the prediction of finite element simulations of layered metal–composite–metal forming processes and error propagation is used to estimate the uncertainties of the simulations. In this contribution, we restrict ourselves to experiments at room temperature. [ABSTRACT FROM AUTHOR]

Copyright of Emirates Journal for Engineering Research is the property of United Arab Emirates University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article deals with the possibilities of improving part blank modelling accuracy for the process of progressive die stamping based on experience obtained in an automotive die manufacturing company. An improvement suggestion for engineering efforts is proposed. To confirm the validity of the proposition, an experimental trial run of progressive stamping dies was performed, the results of which were compared with simulation results. It was established that the improved modelling method is about 30% more accurate in respect to trim line deviation. [ABSTRACT FROM AUTHOR]

Three‐dimensional (3D) forming of fibre‐based materials has been a topic of growing interest over recent years and 3D forming processes using hydroforming, press forming and deep drawing processes have been widely explored. Thermoforming as a potential alternative method for forming these materials remains, however, relatively understudied. This research attempts to provide a fundamental understanding of the thermoforming limitations of plastic‐coated paperboards. In the work, a variety of commercial paperboards are subjected to experimental tests with different forming parameters and moulding depths. Shape accuracy, maximum acquired depth, thickness distribution behaviour and damage mechanisms are used to evaluate thermoformability, and the results linked to the material properties and forming conditions. The research findings indicate that the plastic‐coated paperboards studied are thermoformable but only in simple geometric shapes and with low mould depths. Unlike plastic, thermoforming can result in thickness increase in plastic‐coated paperboards, which is thought to be a result of out‐of‐plane auxetic behaviour of paperboards. Paperboard thermoforming was also found to be hindered by rupture, blistering and curling defects. Tensile strain at break is the key factor determining thermoformability. Additionally, the density of the paperboard can impact the heating step and the rate at which the moisture content of the material changes during the forming process. Furthermore, it was observed that changes in process parameters affected materials differently, with the direction and rate of change differing based on the material being used. [ABSTRACT FROM AUTHOR]

The mechanical clinching technique with an extensible die is selected to connect the metal‐polymer hybrid structure in this article. Al5052‐H32 is chosen as the metallic material. Polyethylene terephthalate glycol (PETG) was chosen as the polymer material. The connection between Al5052‐H32 and PETG is accomplished under diverse forming forces. To evaluate the joinability of hybrid joints, the dimension parameters of hybrid joints are measured by inspecting the transverse section of clinched joints. To evaluate the reliability of joints, the tensile shear test and the energy absorption calculation are accomplished. Moreover, the effect of various forming forces on the mechanical characteristics and failure mode of the hybrid structure is analyzed. The results showed that the Al5052‐H32 sheet and PETG sheet could be effectively connected. The optimal forming force is 38 kN in this experiment. Under this condition, the maximum tensile shear load and the maximum energy absorption value are 1520.16 N and 4.69 J, respectively. [ABSTRACT FROM AUTHOR]

Preform design is one of the dominant factors affecting the formability of tube hydroforming (THF). It refers to the intermediate geometric design between the initial tube blank and the final product shape in the THF process. An appropriately preformed cross-section configuration can avoid forming defects and improve forming performance. For this purpose, a multi-objective optimization design (MOD) procedure for concave preform of rectangular THF is proposed in this work based on surrogate models of the response functions. In this procedure, the process parameters including the geometric parameters of stamping punches, the stroke length of each punch and hydroforming pressure, are regarded as design variables. The objective is to improve the uniformity of wall thickness and reduce the forming pressure at the same time. Based on the design of experiment technique, the training samples and testing samples are obtained. Then, k-fold cross-validation strategy is used to establish the appropriate surrogate models with high accuracy. Afterward, NSGA-II is employed to search the Pareto front of MOD problem, and the ideal point method is used to determine the best compromise scheme. The application results showed that compared with direct hydroforming, the hydroforming pressure of rectangular tube with target fillet radius of 6 mm and 5 mm can be reduced by 69.4% and 64.0%, respectively. In addition, the thickness uniformity index and maximum thinning ratio can be reduced by up to 33.3% and 28.3%, respectively. Therefore, the proposed procedure is effective and reliable and can be used for the optimal design of concave preforms in rectangular THF. [ABSTRACT FROM AUTHOR]

Sheet-tube connection structures are widely applied in chemical, petroleum, medicine, and other industries. Its reliable connection and manufacturing are of great significance for the function of the corresponding equipment. To avoid the occurrence of too deep pits and easy warpage during the single-sided annular sheet squeezing process, an improved method to join sheets to tubes by double-sided annular sheet squeezing is proposed in this paper. The joining process is to squeeze the sheet through the top and bottom dies simultaneously, resulting in radial metal plastic flow, forming the interlock between the sheet and the tube. By experimental and numerical simulation, the joining process of Al6061-T6 sheet and tube under different process parameters using double- and single-sided annular sheet squeezing was conducted and compared. The pull-out test is used to evaluate the quality of sheet-tube joints. Results showed that using the double-sided annular sheet squeezing method can obtain a symmetrical interlocking structure rather than an asymmetric structure by single-sided squeezing, effectively reducing the pit depth on the sheet surface. In addition, the improved method can effectively reduce about 25% of the joining force, but the pull-out strength is about 1.5kN lower than that obtained by the single-sided squeezing method. The joining strength is comprehensively affected by the thickness of the die annulus, punch stroke, and squeezing type. The influence mechanism of process parameters on pull-out strength is discussed. This study provides a new and efficient joining way for the manufacture of sheet-tube connection structures. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate segmentation of cerebrovascular structures from Computed Tomography Angiography (CTA), Magnetic Resonance Angiography (MRA), and Digital Subtraction Angiography (DSA) is crucial for clinical diagnosis of cranial vascular diseases. Recent advancements in deep Convolution Neural Network (CNN) have significantly improved the segmentation process. However, training segmentation networks for all modalities requires extensive data labeling for each modality, which is often expensive and time-consuming. To circumvent this limitation, we introduce an approach to train cross-modality cerebrovascular segmentation network based on paired data from source and target domains. Our approach involves training a universal vessel segmentation network with manually labeled source domain data, which automatically produces initial labels for target domain training images. We improve the initial labels of target domain training images by fusing paired images, which are then used to refine the target domain segmentation network. A series of experimental arrangements is presented to assess the efficacy of our method in various practical application scenarios. The experiments conducted on an MRA-CTA dataset and a DSA-CTA dataset demonstrate that the proposed method is effective for cross-modality cerebrovascular segmentation and achieves state-of-the-art performance. • A framework for cross-modality cerebrovascular segmentation using paired data. • Two pseudo label generation schemes (ICP-based and learning-based). • A series of experiments in various practical application scenarios. • Experiments on two multi-modality cerebral datasets. [ABSTRACT FROM AUTHOR]

This paper mainly studies the influence of process parameters on the forming quality during the spinning process of 6061 aluminum alloy wheel forging blanks. The four parameters of spinning temperature, spindle speed, wheel feed and wall thickness reduction rate are selected for research, and the quality of the surface of the hub and the influence on the size of the hub are judged. Simufact software is used to simulate the influence of various process parameters on the forming quality of the hub. The results provide a certain reference for the reasonable selection of process parameters during the spinning forming process of 6061 aluminum alloy hub. [ABSTRACT FROM AUTHOR]

A four-procedure spinning forming process for manufacturing special-shaped multi-wedge belt pulley (MWBP) was proposed in this paper, which can be applied on spinning technology to produce special-shaped MWBP with web plate and cylinder. First two procedures for obtaining the preformed blank for toothing were investigated through 3D finite element (FE) simulation and experiment, including the spinning shunting procedure and the spinning flattening procedure. Based on the FE simulation results of the spinning shunting procedure, the change of the effective stress and effective plastic strain, the evolution of metal velocity field, and the plastic flow rules were studied. The asymmetric flow diversion of the blank in different positions was discussed, and volume ratio of the upper part and lower part metal (n) of the special-shaped MWBP affected by different positions. The best distance between the upper end of roller 1 and the blank (M) is 8.38 ~ 8.44 mm verified through the experiment. Moreover, the process optimization by controlling the upper fillet size of roller 1 (r1), the feed ratio of the rollers (f), and the friction coefficient (u) was studied by FE simulation. The results show that the n, wall thickness deviation, and ellipticity of the preformed blank for toothing were improved by utilizing the optimized forming parameters and the target parts were formed with high quality through experiments. [ABSTRACT FROM AUTHOR]

Machine learning has successfully introduced a new method to predict forming quality in complex systems in the manufacturing industry. This paper studied machine learning methods in predicting the maximum thinning and thickening rates of hot-stamped parts. First, partition temperature control technique was introduced in the hot stamping process. The temperatures of the die, punch, and blank holder were controlled by twenty-two partitions, and each partition was set to an independent temperature. Then, a finite element model (FEM) was established to simulate the hot stamping of an aluminum box-shaped part. A total of 1600 sets of process parameters were generated, and they were automatically simulated in the FEM software with the help of python code. The results of the 1600 simulations were the maximum thinning rate and thickening rate of the part. Third, four machine learning models were established and trained. The models were tested with an independent testing data set, and their prediction accuracies were compared. The result showed that the gradient boosting regression model could accurately predict the maximum thinning and thickening rates. [ABSTRACT FROM AUTHOR]

The hydroforming technology can realize overall forming of large storage tank's bottom, but the quality is affected by many technological parameters. In view of wrinkling and cracking defects of integral storage tank's bottom in hydroforming, a multi-objective optimization model is established for process parameters including pre-expansion pressure, hydraulic pressure, blank holder force, and fillet radius of blank holder. Based on finite element simulation, the surrogate model between process parameters and quality criteria is established using Kriging technique. NSGA-III is used to determine optimal process parameters when storage tank's bottom reaches targets including minimum wall thickness variations, minimum fracture trend, minimum flange wrinkle, and minimum wrinkle trend. Compared with particle swarm optimization (PSO) algorithm, NSGA-III algorithm is more suitable to solve this optimization problem. The validity of this method and accuracy of the results are verified by simulation experiments. [ABSTRACT FROM AUTHOR]

The interest in magnesium alloys has progressively increased in several industrial fields in recent years, and AZ31 has become an object of the study of lightweight development. Due to its low density and high specific strength, magnesium alloys represent a promising alternative to aluminum alloys and high strength steels, especially for applications in the automobile industry, being used in structural components to reduce weight and, consequently, improve performance fuel efficiency. In recent decades, several tests were conducted to evaluate the formability of AZ31 and showed its high dependency on the temperature range. The main objective of the present study is to propose a fuzzy model to predict the limit drawing ratio (LDR) of an AZ31 sheet by varying its thickness, temperature, and speed in wide ranges. In order to validate the proposed model, comparisons were made with 6 studies performed by other authors -an amount of 46 experimental tests-, showing a very good agreement between experimental results and fuzzy results. The model predicts the limit drawing ratio with an accuracy of 92.1%. [ABSTRACT FROM AUTHOR]

When the fine-blanking process is used, secondary grinding or processing can be omitted because the shear surface of fine-blanking parts can achieve almost zero fracture zone requirements. The primary objective of the fine-blanking process is to reduce the fracture zone depth and die roll zone width. This study used a 2.5-mm-thick central processing unit (CPU) thermal heat spreader as an example. Finite element analysis software was employed to simulate and optimize the main eight process parameters that affect the fracture zone depth and die roll zone width after fine-blanking: the V-ring shape angle, V-ring height of the blank holder, V-ring height of the cavity, V-ring position, blank holder force, counter punch force, die clearance, and blanking velocity. Simulation analysis was conducted using the L18 (21 × 37) Taguchi orthogonal array experimental combination. The simulation results of the fracture zone depth and die roll zone width were optimized and analyzed as quality objectives using Taguchi's smaller-the-better design. The analysis results revealed that with fracture zone depth as the quality objective, 0.164 mm was the optimal value, and counter punch force made the largest contribution of 25.89%. In addition, with die roll zone width as the quality objective, the optimal value was 1.274 mm, and V-ring height of the cavity made the largest contribution of 29.45%. Subsequently, this study selected fracture zone depth and die roll zone width as multicriteria quality objectives and used the robust multicriteria optimal approach and Pareto-optimal solutions to perform multicriteria optimization analysis. The results met the industry's fraction zone depth standard (below 12% of blank thickness) and achieved a smaller die roll zone width. [ABSTRACT FROM AUTHOR]

During the process of deep drawing of cylindrical thin-walled products from aluminum sheets, the occurrence of product defects in the form of breaking the material continuity is observed. This has a very large impact on the efficiency of production lines and the number of generated scraps. The number of defects depends on many factors, including the material and the process properties. Because the problem appears after changing one material to another, while the process parameters do not change, it was assumed that the material has the main influence on the number of defects. To reduce the number of defects, a tool is needed to predict threats to the process. Decision tree models were used for this purpose. Using the tree interaction algorithms, the influence of the chemical composition and strength parameters of the 3xxx series aluminum alloy on the number of generated defects was investigated. Increased Silicon (Si) and Iron (Fe) values generated a higher number of defects. Increased yield strength (YS) and decreased elongation (E) also generated a higher number of defects. Based on the results, a defect prediction tool was created, where after entering the parameters of the material, it is possible to predict production hazards. [ABSTRACT FROM AUTHOR]

Copyright of Materials & Technologies / Materiali in Tehnologije is the property of Institute of Metals & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A new electro-permanent magnet combined blank holder technique has been developed by using permanent magnetic force to supply the blank holding force (BHF) for sheet metal deep drawing. In this work, the workability of the designed magnetic circuits was simulated and tested. A series of numerical simulations and experiments have also demonstrated its ability to overcome temperature rise and provide sufficient magnetic force. The advantages and availability of the combined blank holder technique were expatiated by theoretical derivation, and analyzed by FE stress analysis. The feasibility and effectiveness of the new blank holder method have been proven by a series of experiments for deep drawing a workpiece of 08Al with a diameter of 220 mm. With the segmental blank holder, the flange wrinkling is demonstrated to be suppressed well than using the single blank holder. Also, experimental results corroborated that current is only instantaneously imposed when switching magnetic force state, and not at other times. [ABSTRACT FROM AUTHOR]

Process specific actuators and sensors embedded in the tooling can enable closed-loop control of product properties in manufacturing processes to achieve desired final component characteristics. Alternatively, actuation conducted by the machine tool used and sensors positioned within the machine, i.e., outside of the tool, could increase robustness and reduce investment and installation costs for closed-loop control systems. This contribution presents and compares different closed-loop control strategies for deep drawing and demonstrates the advantages of machine based actuators and sensors in experiments and simulations. [ABSTRACT FROM AUTHOR]

Stamping is the main manufacturing process for sheet metal parts. However, during the stamping process, based on excessive blank holder force, unreasonable mold design, and other factors, it is easy to generate defects such as cracks in the drawing area and flange wrinkles. In this paper, a novel hybrid model based on a restricted Boltzmann machine and back-propagation neural network is proposed and its validity is verified through different testing functions. Additionally, an improved multi-objective particle swarm optimization (MOPSO) method based on a crowding operator is proposed and compared to several powerful existing algorithms. The proposed method was applied to the process optimization of a double-C part. The sensitivity of the forming quality to different process parameters was analyzed and a novel index was used to describe quality changes. A mapping relationship between the process parameters and forming quality was established based on the proposed hybrid model. Furthermore, optimal process parameters were obtained using MOPSO. The results demonstrated that the proposed method significantly reduces flange wrinkles without excessive thinning and improves the uniformity of formed parts. [ABSTRACT FROM AUTHOR]

The Nakajima test is a well-known material test from the steel and metal industry to determine the forming limit of sheet metal. It is demonstrated how FE2TI, our highly parallel scalable implementation of the computational homogenization method FE 2 , can be used for the simulation of the Nakajima test. In this test, a sample sheet geometry is clamped between a blank holder and a die. Then, a hemispherical punch is driven into the specimen until material failure occurs. For the simulation of the Nakajima test, our software package FE2TI has been enhanced with a frictionless contact formulation on the macroscopic level using the penalty method. The appropriate choice of suitable boundary conditions as well as the influence of symmetry assumptions regarding the symmetric test setup are discussed. In order to be able to solve larger macroscopic problems more efficiently, the balancing domain decomposition by constraints (BDDC) approach has been implemented on the macroscopic level as an alternative to a sparse direct solver. To improve the computational efficiency of FE2TI even further, additionally, an adaptive load step approach has been implemented and different extrapolation strategies are compared. Both strategies yield a significant reduction of the overall computing time. Furthermore, a strategy to dynamically increase the penalty parameter is presented which allows to resolve the contact conditions more accurately without increasing the overall computing time too much. Numerically computed forming limit diagrams based on virtual Nakajima tests are presented. [ABSTRACT FROM AUTHOR]

Purpose: Though prior studies have attempted to explore the various effects of managing information technology (IT) investment on firm performance, the mechanism through which management of IT impact on firm performance rests less clear. The purpose of this study is to examine the impact of managing IT and business-IT alignment on firm performance. Design/methodology/approach: Drawing on the resource-based theory and process theory, this study examines how managing IT impacts business-IT alignment and firm performance. The primary survey of 182 responses from IT and business managers from Sri Lanka was empirically examined. Findings: The findings reveal that managing IT has a positive and strong impact on business-IT alignment and firm performance. Further, business-IT alignment partially mediates between managing IT investment and firm performance relationships. Research limitations/implications: Today, businesses have invested a massive amount of money in IT investment, and the return on this investment is always a serious concern for managers and industry practitioners. This study finding proposes meaningful insights on managing IT, business-IT alignment and firm performance. Originality/value: This study opens up the black box on the above nomological linkage and contributes to the literature by extending the theoretical lenses while suggesting insightful and practical implications. [ABSTRACT FROM AUTHOR]

The deep drawing process is implemented for sheet metal forming in industries for acquiring the intricate shape of products and helping to maintain a high productivity rate. Failures viz. wrinkling, earing, tearing and fracture of the sheet metal, during this process are common. The aspects related to these failures are explored in this paper to reduce the occurrence of these failures. The latest method for analyzing failures is through simulation techniques in which numerical methods are combined with software packages. Different cases of failures and their corresponding method of analysis are discussed such as—effect of blank holder force, die shape, stress–strain development, contact pressure distribution, effect of die and blank holder shapes, wrinkling and fracture failures in sheet metal. Failures can be predicted from simulation for different product designs. The tool widely used for this is ANSYS which is found effective to obtain the desired results. [ABSTRACT FROM AUTHOR]