Car Body Parts Research Articles

Controllability of Temperature Induced Friction Effects during Deep Drawing of Car Body Parts with High Drawing Depths in Series Production

Today’s production of car body parts is facing steadily increasing requirements regarding weight, design and efficiency. Minimal process fluctuations may already cause part failure and thereby diminish productivity. Friction influences have drawn attention since the changing of tribological conditions increases the risk of scrap and maintenance costs. Especially at the beginning of a production run, drawing tools are heating up quickly due to the friction between the tools and the metal sheet as well as the plastic deformation of the drawn part. The resulting temperature induced friction effects lead to higher restraining forces and are one of the main reasons for excessive thinning and rupture of deep drawn car body parts with high drawing depths in particular. In this work, a method to evaluate the observability and controllability of temperature induced friction effects in sheet metal forming processes under consideration of non-measured uncertainties like material properties is presented. An inline-measurement system to gather the data required for a tribology-based control system has been integrated into a production tool. Thus, temperature induced friction effects in series production can be investigated based on material flow measurements as well as the tool temperature. The impacts of not directly measured influences and disturbances in the process are evaluated by a numerical sensitivity analysis. Furthermore, multilayer artificial neural networks based on the simulation results have been trained to evaluate the measurement system and to determine potential further measurands within the process which may improve the observability and thereby the effectiveness of the control system.

The effect of mechanical surface pre-treatment on the strength of the adhesive joint of high strength sheets

Nowadays, in the car body parts production, the quenching is often replaced by adhesive joints. The adhesive joints have a lot of advantages – they allow to keep the protective layer, enable to join different material and prevent from the formation of heat affected zones. With respect to passenger’s passive safety, plenty of car body parts are manufactured of high strength steel sheets. The body parts are hot-formed at a temperature of 900 °C to the desired shape followed by subsequent rapid quenching to achieve the required strength. The sheets are covered with an AlSi 60/60 layer which should protect them from high-temperature oxidation during the forming process. However, brittle intermetallic interlayers form during the high-temperature treatment due to the reaction of iron from the substrate with Al/Si from the protective cover, which negatively affects the final strength of adhesion joint. The paper deals with the comparison of different possible ways of removing the layer on the final strength.

Optimising fracture in automotive tail cap by firefly algorithm

Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.

Optimising fracture in automotive tail cap by firefly algorithm

Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.

Numerical investigation on the effect of wall thickness on quasistatic crushing properties of nylon honeycomb structure

Honeycomb structures are extensively used energy-absorbing structures in the airplane, spacecraft and automobile body parts. The critical parameters that influence the aggregate energy absorption are cell size, wall thickness and node length. However, wall thickness is a crucial determining factor for crushing and buckling. The type of failure manifested to the crushing of the cells can be predicted with unit cell buckling. The current work investigated on quasistatic crushing properties of honeycomb structure by varying unit cell wall thickness and at constant cell size of 10 mm. The out of plane quasistatic compression test of nylon honeycomb core of various wall thicknesses i.e 1, 1.1, 1.2, 1.3, 1.4 and 1.5 mm is carried out using ANSYS 14 simulation. The results obtained from the test are in close agreement with unit cell buckling analysis for predicting the mode of failure. The ultimate compressive strength of 1.5 mm cell is observed to be 1.4 folds higher than that of 1 mm cell. The energy absorption obtained from load-displacement graph during compression test indicates the proportional relationship between wall thickness and energy absorption. High energy absorption ability for 1.5 mm wall thickness core infers superior crushing strength enables to use as energy-absorbing devices, where lightweight and strength are the prime concern.

APPLICABILITY VERIFICATION OF AUTOFORM SOFTWARE FOR FEM SIMULATION OF MECHANICAL FIXATION OF HEMMED JOINTS

This paper deals with the problematics of fixation of hemmed joints, especially with one specific mechanical method how to ensure a dimensional stability of a hemmed joint of car-body parts, such as doors, bonnet and trunk lid, during the production process in the automotive industry. It also evaluates simulations and verify the possibility of the use of the Autoform software for this problematics. In the paper, the possibility of using the law of similarity in the analysis of the compressibility of small parts by Autoform is described.

Phase transformation temperatures and Fe enrichment of a 22MnB5 Zn-Fe coated steel under hot stamping conditions

In the last years, press-hardening steels have contributed to the automotive industry successfully to meet the increasing regulations for reducing fuel consumption and stringent greenhouse gas emissions while improving passenger safety by manufacturing lightweight car body parts. Zn-Fe coating is an alternative to prevent corrosion or even enhance the corrosion resistance in these steels. However, Zn-Fe coating is prone to liquid melting embrittlement (LME) during the hot forming process. To prevent LME, the coating must be fully transformed into a solid solution before the forming operation, avoiding the contact of the Zinc liquid phase with the steel substrate. This work aimed to determine the phase temperature transformations and critical cooling rate to define the process window for a 22MnB5 sheet with a Zn-Fe coating when submitted to a higher heating rate in comparison to the direct conventional hot forming process. The experimental results indicated that a fully martensitic microstructure is obtained with a cooling rate of 30°C/s. The adopted two-side Zn coating weight of 80g/m2 heated at 53°C/s to 900°C is fully transformed into Fe-α solid solution in 23s, which is an industrial gain compared to longer dwell times required in the conventional heating furnace processes.

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.

Predictive Analysis from numerical and experimental data in press hardening

Machine learning, big data and deep learning are today’s catchphrases for how to improve reliability and productivity of your manufacturing equipment. Production companies implement a large number of sensors to record every activity within their production lines and learn as much as possible about their running processes in order to predict shifting product properties and to prevent stoppage due to failure. The successful application of machine learning algorithms to predict machine and process behavior depends on a reliable and balanced database. Since the foremost goal of every manufacturing business is to make sound parts and to avoid defects, there is a large amount of data available for smoothly running processes but only very little for failure production. One approach to solve this imbalance would be to link the production line data with simulation data. Simulation models allow for computing failure parts with no additional costs and therefore enable the exploration of the entire parameter space. We conducted press-hardening experiments with a variation of process parameters for a structural car body part on the press hardening line at Fraunhofer IWU. As an evaluation criterion, we measured the hardness of the final part at critical spots. In order to expand the experimental data, we applied FE simulations to the entire press hardening process chain. The paper explains limitations of the model and elaborates on its parameterization. As a final task, we applied a basic machine-learning algorithm to both experimental and numerical data as well as to their combination in order to evaluate the data space expansion through simulations. The results obtained through machine learning indicate significant differences in the prediction of part quality for solely experimental data and its combination with simulation data. This is especially true for press hardening because of non-linear system behavior and a large amount of uncertain and hard-to-identify parameters. We found that the most challenging parts of uniting measured and simulated data is not only to create simulations with appropriate accuracy, which allow for a meaningful extrapolation of the parameter space, but also to compare simulation and production data based on the same criterion and to have stable simulation models for the entire parameter range.

Virtual die spotting: Compensation of elastic behavior of forming presses

The rapid change in the automotive industry towards an electrified and digitalized future necessitates companies to shorten product development cycles. To meet customer needs regarding design and quality, the requirements on the production processes are constantly increasing. As additive manufacturing cannot provide large enough batch sizes yet, conventional stamping of car body parts will be the technology in the foreseeable future. The most time-consuming step during the production of stamping dies is the manual spotting during try-out of the tools. To achieve a homogenous pressure distribution on the parts a precise tool closure is necessary. The behavior of the press has huge influence on the tool closure, especially the elastic deformations of ram, bolster and cushion during forming. Current compensation methods are solely based on experience from previous tools. This contribution presents a methodology for designing a virtual die-compensation to account for press machine behavior based on experimentally determined measurement data of the try-out press. The data is used to calibrate FE-substitute-models of ram and bolster. A forming simulation using rigid tools is coupled with structure simulation using elastic tools and machine. By evaluating the deflection of the active surfaces at the bottom dead center of the press, the necessary die-compensation can be determined.

Friction modelling in sheet metal forming simulations for aluminium body parts at Daimler AG

Tribology plays a key role in the production of high-quality car body parts. In forming simulations, often a constant value for the friction coefficient is used, which limits the overall simulation accuracy. In reality, friction depends on the pressure distribution, forming velocity, interface temperature, plastic strain, type/amount of lubrication and the surface topography of both the sheet and the tooling. The simulation accuracy, and therefore the prediction of the formability of complex geometries, can be improved significantly by taking all these parameters into account. This paper presents a selection of results for 2 aluminium cases: 1 scientific part conducted at the IFU Stuttgart and 1 complex body part from Daimler AG. Simulation results have been validated by experimental results to show the influence of friction on e.g. part quality, draw-in and spring-back. Results show that friction modelling becomes increasingly important in the stamping process of aluminium parts, and that the overall simulation accuracy increases when accounting for the actual tribological conditions in stamping.

Basics for inline measurement of tribological conditions in series production of car body parts

The quality of car body parts in series production is strongly dependent on the tribological behavior. Fluctuating material properties such as the sheet roughness and the amount of lubricant have an influence on the forming process. On the basis of large amounts of data it is possible to investigate the friction behavior in series production and to make process adjustments if required. Therefore, inline measurement systems have a great potential to detect the sheet roughness during the cutting process of blanks in the coil line. Furthermore, contactless systems are advantageous as they do not damage the surface. Nevertheless, the optical measuring is influenced by the lubricant layer on top of the surface. Therefore, the previously unknown impact of the lubricant on the measuring result is investigated.Within this study, stationary optical roughness measurements have been conducted using different amounts of lubricant on hot-dip galvanized EDT steel. The results demonstrate the influence of different amounts of lubricant on the sheet roughness measurement. Hence, it is possible to correct the inline measuring results and gain knowledge of fluctuating surface roughness. In addition, strip drawing test has been carried out to investigate the effect of fluctuating tribological conditions.

Investigating the feasibility of a new testing method for GFRP/polymer foam sandwich composites used in railway passenger vehicles

This paper investigates the feasibility and validity of a recently proposed testing method when applied to foam core sandwich composites to determine the impact resistance of train car body shells. The published method proved itself useful when applied to monolithic fibre reinforced plastic laminates, however, further analysis is required if sandwich composites are used due to the subtle differences compared to monolithic laminates. It is especially important for the front nose section of high-speed trains as these car body parts can be subjected to ballast flight at high impact velocities. Due to the aerodynamic design aspects, front nose sections generally incorporate complex 3D geometries, and sandwich composite materials are advantageous in this respect due to the ease of manufacturing of complex 3D shapes. Quasi-static punch tests (QSPT) were performed on E-glass fibre/epoxy resin/PET foam core sandwich plates. Numerical finite element model (FEM) was developed and validated with experiments in terms of penetration resistance and structural damage. Numerical model was used to investigate three railway impact related standards and high-velocity impact parameters (energy transfer, contact force, projectile velocity) were analysed for each case. Additionally, the foreseeable contribution of this work to the railway industry was given from multiple aspects.

Functional optimization of hot-stamped components by local carburization

One of the major challenges in modern car body construction is the reduction of component weight while still maintaining passenger safety. In terms of these requirements, the substitution of conventional steel grades by ultra-high strength materials is the most promising approach. Hot stamping of these steels has developed to a state of the art process for manufacturing safety-relevant car body parts such as B-pillars or front bumpers. By locally adjusting the mechanical properties, for example, increasing the ductility, passive safety can be further improved. For this purpose, the hot stamping process is adapted in different ways. Varying from these established methods, tailored carburization is an alternative approach for manufacturing functional optimized components by combining hot stamping with prior local carburization. Within this work, the potential of local carburization is analyzed by a fundamental investigation of the influence of the process parameters on the mechanical properties as well as the transition zones between carburized and non-carburized areas. Besides the mechanical properties, the heat transfer between carburized sheets and tools is studied. The process suitability is validated by a demonstrator.

Experimental Study, Modeling and Virtual Simulations of Car Part Realized from Composite Materials

In this paper we were looking for the production of a physical car body part (the left side fender of a Peugeot 206) made from composite materials based on epoxy resin and reinforced carbon fiber and kevlar woven. On the newly created fender model, a modal analysis has been made in order to determine its own frequencies on a certain direction, and an harmonic analysis with Finite Element Method.

Importance of Beam Analysis for Industry 4.0

AbstractThe laser revolutionized production. Compared to resistance spot welding, the machining speed has been increased by more than 50 % and it allows new joining and construction concepts. But whether car body parts are welded or turbine blades are repaired by laser powder cladding, both require the highest process quality and thus optimal adjustment of the laser parameters. From this point of view, the use of laser diagnostic systems, such as the PowerMeasuringModule and the FocusParameterMonitor from Primes, is worthwhile.

Optimization of the measurement path for the car body parts inspection

The most evident characteristics of body components used in automotive industries are two overall dimensions with much higher values compared to a third one, as well as the relatively uniform apportion of functional elements on the surface of the workpiece.During the inspection process, these characteristics determine the active measuring element to pass greater distances between the measuring areas, in comparison to the distances required for the effective measurement.Heuristic and approximate methods for measuring path optimization have the advantage of finding a solution making fewer operations, and the found solution differs from the optimal solution with no more than 2–3%.In the present paper, optimization algorithms based on the matrix relaxation method and nearest neighbor method were imagined and applied. These algorithms have served as a basis for developing a software. This software allows the optimization of the measurement path for car body parts which characterized by areas where the inspection is carried out, relatively uniformly apportioned over the surface of the workpiece.

Semantic content of motorcycle riders’ eye fixations during lane-splitting

A naturalistic field observation study is presented, exploring the experienced riders’ eye fixations on specific traffic objects and their relative semantic content during lane-splitting manoeuvre in urban settings. Six experienced motorcyclists rode their own motorcycles equipped with an eye-tracking system. Data were extracted using manual video annotation and stimulated retrospective think-aloud methods. In total, 54 cases of lane-splitting (i.e., passing between a consecutive set of three moving cars) were analysed in terms of traffic objects and car-body parts fixated upon. Eye-fixation results on traffic objects show that all six riders tended to fixate less on the nearest target cars, allocating more fixations in monitoring the farthest target car and traffic ahead. In addition, all six riders fixated consistently on specific car-body parts of the target cars, namely, on the front body parts of the nearest target car (i.e. wing mirror, front side window, and front wing/tyre) and on the rear body parts of the farthest target car (i.e., rear light, rear quarter pillar, and rear wing/tyre). Riders’ commentaries revealed that the aforementioned fixations were intentionally made in search of (1) assessing the level of drivers’ attentiveness of the neighboring car(s), and (2) anticipating the possible path deviations of the neighboring car(s), for monitoring the upcoming contingencies in the traffic ahead rather than simply monitoring the actual movements of the target cars. Implications for developing specifications of riders’ and drivers’ assistance systems are discussed.

The Effect of Welding Parameters on the Properties of Join between Studs and Steel Sheet USIBOR Type 22MnB5

To build the car body parts of today's cars, materials of higher strength are used on an ever-wider scale. They are, for example, boron-containing steels, which are highly resistant to special thermo-mechanical processing, coated with AlSi; e.g. USIBOR 22MnB5 type materials. For the final assembly of all body mounting components, it is necessary to apply different types of joining stud elements. One of the possibilities of making joinings between sheets and fastening elements - studs is the technology of short-circuit stud welding.This article aims to evaluate the influence of welding parameters of steel studs on high-strength steel sheet type USIBOR 22MnB5 with AlSi coating on selected mechanical properties of joints.

Effect of Gap Size on Galvanic Corrosion between AA5052 Aluminum-Magnesium Alloy and SS400 Carbon Steel in Aqueous NaCl Solutions

Recently, aluminum alloys (AAs) have been utilized to automobile body parts in order to reduce the weight of the body and improve fuel consumption efficiency. Although some aluminum alloys such as 5000 and 6000 series have relatively good corrosion resistance in atmospheric environments, galvanic corrosion between aluminum alloys and other electroconductive materials is one of the critical issues on automotive application of the aluminum alloys. So far, we have investigated galvanic corrosion between AA5052 aluminum-magnesium alloy and SS400 carbon steel in aqueous NaCl solutions and reported that the galvanic corrosion behavior changes depending on the concentration of NaCl solutions [1]. In this study, effect of gap size between aluminum alloys and steel on galvanic corrosion behavior was investigated in aqueous NaCl solutions. A galvanic couple used in this study was almost the same as that reported before, which was made of AA5052 Al-Mg alloy (Mg: 2.65, Si: 0. 08, Fe: 0.27, Cu: 0.01, Cr: 0.17, Zn: 0.01, Al: bal. (mass%)) and carbon steel (JIS SS400). The plate of both materials was 10-mm width and 15-mm length and 5-mm thickness. After lead wires were connected to each plate, both plates were embedded together in an epoxy resin. In this study, both plates were placed separately along the surface with gap sizes from 500 um to 10 mm so that a coplaner galvanic couple was prepared. The surface of the galvanic couple was ground with SiC papers up to JIS 2000 grit and rinsed in EtOH. Galvanic corrosion experiments were done for 72 h in aqueous NaCl solutions of various concentrations ranging from 5 mM to 2 M. Galvanic current and corrosion potential of the couple were measured during the immersion in the solutions. It was found from the results of corrosion potential, galvanic current, and surface observation that galvanic corrosion behavior changes depending on the gap size between AA5052 and SS400 in the NaCl solutions. When the gap size was 10 mm, no corrosion occurred on the SS400 side in all of the test solutions, suggesting that anodic dissolution reaction was dominant on the AA5052 side. However, when the gap size was decreased, the corrosion of the steel occurred in the solutions at lower concentrations, although the aluminum alloy also showed localized corrosion. These results indicated that anodic dissolution reaction was generated on both materials in the smaller gap-size condition with decreasing the NaCl concentrations. In this study, the change in the galvanic corrosion behavior with the gap size was also discussed from the results of change in the solution chemistry and polarization behavior of the materials. 1. K. Ota, E. Tada, A. Ooi, A. Nishikata, ECS meeting abstracts, MA2018-02, 574, 2018.