Production Of Sheet Metal Parts Research Articles

Evaluating the performance of Bi58Sn42 mold produced by material extrusion additive manufacturing system for agile manufacturing

PurposeThe purpose of this study is to produce a low-cost sheet metal forming mold made from the low melting point Bi58Sn42 (bismuth) alloy by using an open-source desktop-type material extrusion additive manufacturing system and to evaluate the performance of the additively manufactured mold for low volume sheet metal forming. Thus, it was aimed to develop a fast and inexpensive die tooling methodology for low-volume batch production.Design/methodology/approachInitially, the three-dimensional printing experiments were performed to produce the sheet metal forming mold. The encountered problems during the performed three-dimensional printing experiments were analyzed. Accordingly, both tunings in process parameters (extrusion temperature, extrusion multiplier, printing speed, infill percentage, etc.) and customizations on the extruder head of the available material extrusion additive manufacturing system were made to print the Bi58Sn42 alloy properly. Subsequently, the performance of the additively manufactured mold was evaluated according to the dimensional change that occurred on it during the performed pressing operations.FindingsResults showed that the additively manufactured mold was rigid enough and proved to have sufficient strength in sheet metal forming operations for low-volume production.Originality/valueAlternative mold production was carried out using open-source material extrusion system for low volume sheet metal part production. Thus, cost effective solution was presented for agile manufacturing.

Cluster analysis for systematic database extension to improve machine learning performance in double-sided incremental sheet forming

Incremental sheet forming is a process for the production of sheet metal parts in small batch sizes. Due to the relatively low geometrical accuracy and the lack of precise and fast finite element analysis simulations of the process, industrial use cases are rare. Recently, a vast amount of scientific approaches simulated the process by utilizing machine learning techniques. Their success is limited by the quantity and quality of the used process data. Research institutes are struggling to gather enough data without industrial cooperations. For maximizing the distribution of process data in an experimental series and therefore their applicability for machine learning, the authors present a novel cluster analysis approach to systematically extend an existing database. The whole established process database consisting of 70 forming experiments and their toolpaths and digitizations is published to be used as a foundation for similar research.

Numerical and experimental investigation of direct rapid tooling for sheet metal forming using selective laser sintering

The rapid tooling approaches were most sought after for the low-volume production of sheet metal parts within a short duration. This study presents an investigation of direct rapid tools produced with Selective Laser Sintering (SLS) for sheet metal forming. SLS is one of the widely used additive manufacturing techniques to produce polymer parts. The ability to form the sheet metal components using SLS direct rapid tools was assessed through cup drawing from aluminium blanks. A full factorial experiment was formulated to design the tools by varying the punch radius, die radius and draw ratio. The tools were fabricated with SLS using glass bead - filled polyamide material (PAGF) and finite element analysis was employed to study the stress distribution. The stress concentrations were observed at the tool edge radius, yet the PAGF tools sustained the load from the cup drawing process. The inspection of the PAGF tools and drawn cups shows that they are sensitive to the edge radius and draw ratio. Wear at the edge radius was evaluated in terms of percentage deviation from the initial radius. While the designed dimension of the edge radius is a significant factor affecting respective tool edges, the die edge wear was also influenced by the draw ratio. Both the formed parts and the tools exhibit geometrical variations localised to the forming edges and demonstrate good repeatability even up to 200 draw cycles.

Reliability Prediction and FMEA of Loading and Unloading Truss Robot for CNC Punch

Loading and unloading truss robot for computer numerical control (CNC) punch is widely used in the production of sheet metal parts, as its reliability level is directly related to the quality of sheet metal parts. Especially for the automatic sheet metal production line, it is urgent to predict the reliability of the loading and unloading truss robot for CNC punch. In this paper, a new method for the reliability prediction of the loading and unloading truss robot for CNC punch is proposed. The method uses the component counting method to predict the failure rate and mean time between failures (MTBF) of the electrical control system. Then, according to the MTBF value of the electrical control system, the MTBF value and failure rate of the mechanical system and pneumatic system are calculated by expert scoring method based on fuzzy theory. The MTBF value and failure rate of the loading and unloading truss robot for CNC punch are estimated, and the weak link of the loading and unloading truss robot for CNC punch is obtained. Finally, through the collected fault maintenance data records, the failure modes and effects analysis (FMEA) of the loading and unloading truss robot for CNC punch is carried out, and the reliability prediction method proposed in this paper is validated by the fault location analysis results.

Classification-based process parameter recommendation in sheet metal forming

For the production of sheet metal parts for car bodies, continuous adjustment of process parameters is required to maintain the desired part quality in the presence of scattering blank properties. The digital transformation enables data-driven methods for finding process parameters instead of a time-consuming experience-driven trial-and-error approach. However, it is still hard to measure quality for every part due to cost and technical limitations. Removing data points of low-quality parts helps in recommending proper process parameters. In this paper, we propose a classification-based solution enhanced by a particular data preprocessing for recommending cushion cylinder forces. The solution utilizes anomaly detection and knowledge-based methods to remove potential low-quality data points without quality measures in data prepossessing. On the processed data, a classification model is trained to predict process parameters according to blank properties. Our solution detects 32.46% low-quality parts and gives competitive performance (94.30% prediction accuracy) compared to a model trained on data comprising quality measures.

A numerical and experimental analysis of noncircular blank spinning

The process of conventional spinning has been widely used in the production of sheet metal parts, but nearly in all cases, the initial blank of the process has a circular shape. In this article, the novel idea of spinning non-circular blanks is studied. To do so, an octagonal blank made of AL-1050 was chosen and the experimental works as well as numerical simulations, taking the effects of anisotropy into account, were performed. Shape deviation from the ideal form in terms of springback and strain distribution was studied for the deformed component. The numerical simulations revealed that uneven compressive strains at the edges as well as bending moment effects at the edges are responsible for the specific shape deviation in the final geometry. The comparison between the anisotropic and isotropic behavior of shell and solid elements with experimental results in three different thicknesses showed the shell element predicts the springback phenomena better than the solid element. On the other hand, solid element gives better results in the prediction of major and minor strains. The results of the numerical simulations and the experimental works show that more variety of geometries that would otherwise need an extra cutting process can be produced by deviating the initial blank geometry from circular form.

Про лазерний технологічний комплекс на машинобудівному підприємстві

The geography of manufacturers of laser devices available for the Ukrainian market is analyzed. The field of application of laser systems at mechanical engineering enterprises is quite wide: heat treatment, welding, cutting, marking, piercing, surfacing and surface alloying. One of the most promising, accurate and productive laser systems at a mechanical engineering enterprise is a laser technological complex. The modern configurations of laser technological complexes, which are used at mechanical engineering enterprises, are considered. A review of sources for generating a beam using a diode laser, as the pumping method most widespread in mechanical engineering, is carried out.The advantages of using laser technological complexes at a mechanical engineering enterprise are considered. The features of the operation of this equipment and potential disadvantages are indicated. We are talking about cutting modes, which simultaneously depend on five or more settings; the quality of oxygen, air or shielding gas used during cutting; ambient temperature during equipment operation; safety features during work. Ways to eliminate potential drawbacks are proposed.Despite the presence of peculiarities of operation of laser technological complexes, they ensure high quality and productivity of production of sheet metal parts in mass production compared to stamping equipment. The laser technological complex provides processing of sheet metals of different thicknesses, different external overall dimensions, within the working table, and different brands of non-ferrous and ferrous metals, which allows it to be used effectively in single production. Also, to the positive qualities of laser installations, you can add insignificant costs for reconfiguring the equipment for the production of new products and the low cost of consumables.

Sheared edge defect segmentation using a convolutional U-Net for quantified quality assessment of fine blanked workpieces

Fine blanking allows for the economic mass production of sheet metal parts of high dimensional accuracy. The smooth cut section at the sheared edge is an important quality characteristic that is, however, reduced by the formation of tearings and fractures in the cut-off zone. At present, the smooth cut section cannot be assessed immediately as no capable methods for a 100% inline quality control of sheared edges for fine blanking exist, causing high scrap rates. To address this deficit this work proposes U-Nets to segment tearings and measure the cut-off height at sheared edges. A systematic model search together with a transfer learning strategy is conducted based on a dataset of 80 images of sheared edges of fine blanked reference workpieces. After a hyperparameter optimization, trained models are able to measure the cut-off height on the test dataset with a mean relative error of 1.1% and a mean absolute error of <1 px corresponding to an average measurement error of 7.5 μm. Besides the natural ability to incorporate additional disturbances in a real-world application, investigations of the reproducibility and the impact of the dataset size indicate that the proposed U-Net model is easy to set up and achieves a comparable average performance of 1.14 ± 0.31 px (17.1 ± 3.7 μm) even for non-optimal model initialization and small training datasets. For this reason, the shown approach is a promising solution for an inline machine vision system.

Effect of steel forming on vehicle side impact behavior

Abstract Despite the seemingly daily development of high-strength new generation steel sheets, steel sheets still remain the most important engineering material used in a vehicle body. These steel parts in a vehicle body, meant to absorb energy during impact, are generally produced by steel forming methods. These steel forming operations may contain processes such as deep drawing, bending, cutting, spring back, spinning. According to the production conditions and type of processes used during the production of sheet metal parts, thinning, thickening, plastic deformation, folding, tearing and wrinkling may occur. In order to achieve more reliable impact simulations, these effects in the forming process should be conferred on impact analysis. Within the scope of this study, an analysis of the critical parts in steel forming that absorb the most energy during the side impact was conducted – first for vehicles. In a subsequent impact analysis, the effects of changes (thickness distribution, residual stress, plastic deformation, etc.) during steel forming were examined.

The Experimental Investigation of Punching of the AM60 and AZ61 Magnesium Alloy Sheets by Using Varied Punch Shapes

The using of magnesium alloys for industrial sheet metal part production has become increasingly common in recent years. This research aims to characterize the effects of the cutting-edge shapes of the punches on the blanking forces and the sheared edge qualities in the blanking/piercing operations of magnesium alloy sheets. Magnesium sheets (AM60 and AZ61) were produced by casting and rolling processes. AM60 and AZ61 Mg alloys produced by casting were rolled by using two different speeds, 2.5 m/min and 7.5 m/min. Material thickness was adjusted to three mm in the rolling process. Blanking tests were carried out on a die-set and hydraulic press by varying shaped punches. In the experimental studies, flat-ended, concave shaped, and 16° angled punches were used. A loadcell was fixed to the experimental setup to determine the blanking forces. The results showed that the AM60 alloy was more resistant to shearing than the AZ61. The lowest blanking force was obtained by use of the 16° angled punch. It was determined that the using of flat-ended punches for blanking operations was more convenient according to the usage purpose of the parts while all three punches can be used for piercing operations.

Modelling real contact areas caused by material straining effects in sheet metal forming simulation

Shortened product development processes in automotive industry combined with the upcoming lack of experts do challenge sheet metal part production fundamentally. Tryout time and manufacturing costs of large forming dies today are significantly influenced by their digitally supported engineering. The forming process by such tools is beside other influences is affected by elastic deformations of forming dies and press structure as well as contact areas between die and sheet metal part. In deep drawing such contact areas are influenced by the blank properties and the flange behavior in terms of thickening and thinning. Recent developments in sheet metal forming simulation do consider advanced friction models and structural modeling of die and press components improving simulation accuracy. Nevertheless thinning or thickening of sheet metal results into localized surface pressure distribution during deep drawing. For this reason, it is not sufficient to use the currently common practice of homogeneous surface pressure distribution in sheet metal forming simulation. In this respect, this paper presents a numerical approach for consideration of straining effects in the sheet metal part during forming operation. For this purpose, a systematic process improvement was developed in this paper to identify contact areas via a numeric simulation parameter. Validating the numerical investigation, a rectangle cup die is used, considering major strain. The main results of this contribution for that reason show how simulated contact areas can be estimated by reverse engineering of real forming parts. Hereby straining based contact areas lead to a novel contact area design in process planning, resulting in efficient die tryout.

A Classification-based Solution For Recommending Process Parameters of Production Processes Without Quality Measures

Abstract For production of sheet metal parts for car bodies, an adjustment of process parameters is required to maintain the desired part quality in presence of scattering blank properties. The digital transformation enables the application of data-driven methods for finding process parameters instead of a time-consuming experience-driven trial-and-error approach. However, due to cost and technical limitations, it is still hard to measure quality for every part. Removing data points of low-quality parts helps recommending proper process parameters. In this paper, we propose classification-based solution for recommending process parameters. In data preprocessing, the solution utilizes anomaly detection and knowledge-based methods to remove potential data points of low-quality parts without quality measures. On the processed data, a classification model is trained to predict process parameters according to blank properties. Our solution detects 30% low-quality parts and gives competitive performance (92.26% prediction accuracy) compared to a model trained on data comprising quality measures.

COMPENSATION OF SPRINGBACK IN LARGE SHEET METAL FORMING

A precise production of sheet metal parts has always been a main goal in press shops. Highest quality demands are required especially in automotive production. Unfortunately, even today, the production is not optimal due to an ineffective approach to the springback compensation. Springback results in geometrical shape inaccuracies of the obtained product. Based on the current approach, excessive time and financial costs emerge due to corrections on the press tools. However, these corrections do not always lead to a better accuracy of the stampings. The main objective of the research is to design a modified solution of the current approach. The modified solution is designed as a methodology with a focus on the analysis and compensation of the springback with a help of a numerical simulation. To achieve the main goal, smaller sub-goals are employed. These sub-goals, or rather experiments, mainly focus on parameters, which, more or less, influence the springback phenomenon. The designed methodology is verified with real car body parts and is carried out with a help of the department of the press tools design in ŠKODA AUTO, a.s. There, the methodology is used for improving the accuracy of the stamping process of the car body parts and for improving the quality of the final product.

Tribological Conditions Using CO2 as Volatile Lubricant in Dry Metal Forming

Deep drawing is the most important manufacturing process in order to produce sheet metal parts in mass production. In this study, volatile carbon dioxide (CO2) is used as lubricant in order to replace mineral oil-based lubricants. CO2 is injected into the void between the forming tool and the metal part through laser drilled microholes in the forming tool and acts there as a highly efficient lubricant. In order to investigate the tribological conditions during the drawing process, a new test bench having optical access to the CO2 lubricant is designed, built and used in this study. Additionally, the CO2 flow through the microholes is modeled using CFD simulation. Both the experimental and the theoretical study reveal a critical influence of the geometry of the microholes on the phase of the CO2 in the forming tool and on the friction during the drawing process. Thereby, these investigations confirm that the CO2 is in solid and/or gaseous state dependent on the surface pressure and the geometry of the microholes. Consequently, these results support the concept of microstructure-designed forming tools allowing dry metal forming for locally adjusted and environmentally friendly friction conditions.

Experimental investigation of new blank holder approach for incremental forming method

In this study, a new method is developed to reduce the variation of the wall thickness in incremental sheet forming method used in prototype production of sheet metal parts. Unlike the traditional incremental forming method, this new method defined as “rolling blank holder incremental forming method” is aimed primarily at the force optimization of the blank holder. In this context, 27 different experimental runs were carried out with 1 mm thick DC01 sheet metal. According to the experimental results, when 2 bar pressure was applied to the pneumatic clamps that supply the clamping force, 4.5% improvement of the minimum wall thickness was observed. Clearly, a better wall thickness distribution can be obtained when this new method is used, compared to the conventional incremental forming method.

Achieving maximum dimensional accuracy and surface quality at the shortest possible time in single-point incremental forming via multi-objective optimization

Single-point incremental forming is a novel and flexible method for producing three-dimensional parts from metal sheets. Although single-point incremental forming is a suitable method for rapid prototyping of sheet metal components, there are limitations and challenges facing the commercialization of this process. Dimensional accuracy, surface quality, and production time are of vital importance in any manufacturing process. The present study is aimed at selecting proper forming parameters to produce sheet metal parts which possess dimensional accuracy and good surface quality at the shortest time. Four parameters (i.e. tool diameter, tool step depth, sheet thickness, and feed rate) are chosen as design variables. These parameters are used for the modeling of the process using Group Method of Data Handing(GMDH) artificial neural networks. The data necessary for establishing empirical models are obtained from single-point incremental forming experiments carried out on a computer numerical control milling machine using central composite design. After the evaluation of the model accuracy, single- and multi-objective optimization are performed via genetic algorithm. The performance of the design variables of a tradeoff point corresponding to one of the experiments shows the efficiency and accuracy of the models and the optimization process. Considering the priorities of objective functions, a designer will be able to set proper process parameters.

Computer aided system for parametric design of combination die

In this paper, a computer aided system for parametric design of combination dies is presented. The system is developed using knowledge based system technique of artificial intelligence. The system is capable to design combination dies for production of sheet metal parts having punching and cupping operations. The system is coded in Visual Basic and interfaced with AutoCAD software. The low cost of the proposed system will help die designers of small and medium scale sheet metal industries for design of combination dies for similar type of products. The proposed system is capable to reduce design time and efforts of die designers for design of combination dies.

Improved process robustness by using closed loop control in deep drawing applications

The production of irregular shaped deep-drawing parts with high quality requirements, which are common in today’s automotive production, permanently challenges production processes. High requirements on lightweight construction of passenger car bodies following European regulations until 2020 have been massively increasing the use of high strength steels substantially for years and are also leading to bigger challenges in sheet metal part production. Of course, the more and more complex shapes of today’s car body shells also intensify the issue due to modern and future design criteria. The metal forming technology tries to meet these challenges by developing a highly sophisticated layout of deep drawing dies that consider part quality requirements, process robustness and controlled material flow during the deep or stretch drawing process phase. A new method for controlling material flow using a closed loop system was developed at the IFU Stuttgart. In contrast to previous approaches, this new method allows a control intervention during the deep-drawing stroke. The blank holder force around the outline of the drawn part is used as control variable. The closed loop is designed as trajectory follow up with feed forward control. The used command variable is the part-wall stress that is measured with a piezo-electric measuring pin. In this paper the used control loop will be described in detail. The experimental tool that was built for testing the new control approach is explained here with its features. A method for gaining the follow up trajectories from simulation will also be presented. Furthermore, experimental results considering the robustness of the deep drawing process and the gain in process performance with developed control loop will be shown. Finally, a new procedure for the industrial application of the new control method of deep drawing will be presented by using a new kind of active element to influence the local blank holder pressure onto part flange.

FEA of vertical parts formed with multistage incremental sheet metal forming based on the forming limit stress diagram

Multistage incremental sheet metal forming (MS-ISF) is used to produce sheet metal parts with a large forming angle. Similar to the forming limit diagram (FLD) in stamping, FLD in MS-ISF is not sufficiently reliable due to the effect of loading path. To solve this problem, a method to calculate the forming limit stress diagram (FLSD) from FLD was proposed. Experiments proved that FLSD is a reliable fracture indicator that is unaffected by the loading path in MS-ISF.

Influence of surface condition due to laser beam cutting on the fatigue behavior of metastable austenitic stainless steel AISI 304

Austenitic steels are among the stainless steels the most common used type of material to produce sheet metal parts which can be manufactured by laser beam cutting in a useful manner. However, the use of this technique to manufacture structural thick parts is restricted due to the creation of macroscopic defects and the lack of reliable fatigue strength data. In this context, the fatigue behavior of sheet-like samples made of metastable austenitic stainless steel AISI 304 cut by laser beam is discussed in this paper. The analyses showed that laser beam cutting creates three kinds of macroscopic defects, which are a pronounced relief-like structure along the cut surface, burr in the underside of the cut edge and pores in the interface between the recast layer and base material or inside the recast layer. As a consequence, the fatigue strength of parts cut by laser beam is 40% lower in comparison to specimens in a macroscopically quasi defect-free state. An evaluation of the fatigue results based on comprehensive fractographic analyses allows to explain the reasons for distinct differences between the aforementioned influence factors. The most significant reduction of fatigue life is attributed to the notch effect of the burr, followed by the notch effect created by pores, while the influence of the surface relief is of minor significance.