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Mould temperature control has a significant influence on component quality and costs in the plastic injection moulding process. In the case of standard applications isothermal temperature control, in which the mould temperature is maintained at one level, is sufficient. For special applications (e.g. plastic optics; long, thin components; moulding of microstructures) variothermal temperature control using cyclically changing temperatures is beneficial. Therefore, the use of infrared radiators offers advantages in terms of achievable temperatures and investment costs but at low heating rates and efficiency. This paper therefore investigates the possibility of increasing the efficiency of energy input by infrared radiation into metals in particular into aluminium. For this purpose, a simulation model is developed. The numeric models used are validated by means of experiments. A short-wave infrared radiator is investigated, consisting of a tungsten filament in a quartz glass tube. The emitter power is varied from 1200 to 400 W. An aluminium sample with a thickness of 10 mm and a square base with an edge length of 60 mm is investigated. The temperature is measured on the non-irradiated side in the centre of the sample surface and at a distance of 20 mm from it while being irradiated. For the numerical model, a ray tracing simulation is carried out in a first step, the result of which is used as a Neumann boundary condition for a thermal simulation in second step. The model created can serve as a basis for the thermal design of more complex geometries.

The combination of hot-stamped steels and fibre-reinforced thermoplastics (FRTP) offers great potential for lightweight design. The process steps of hot stamping and thermoforming for the manufacturing of such hybrid structures are usually carried out in two separate steps. After hot stamping, the blank has to be reheated for the application of FRTP in order to enable the bonding of FRTP to the blank. Process integration of the individual processes means that reheating of the blank during thermoforming is no longer necessary. Due to non-uniform contact conditions during hot stamping between blank and tool, an inhomogeneous temperature distribution in the blank occurs, which would lead to non-uniform bonding properties between blank and FRTP after thermoforming. The aim of this work is to determine this non-uniform contact and the resulting heat transfer by a numerical model. By segmenting the tool in the model, a possibility is shown to control the non-uniform contact and to achieve a homogeneous temperature distribution in the blank after hot stamping. Furthermore, the temperature adaptability of the used tool and the resulting temperature distribution in the blank is investigated. Finally, the manufactured structures are tested in a numerical three-point bending test in order to be able to make a statement about their performances.

In an effort to reduce prototypes in the industrial manufacturing of sheet metal components and their assembly, numerical simulation is well established. Where each single process transfers into its virtual counterpart to ensure quality assurance, disregarding the influence of their preceding processes. In order to further the accuracy of a virtual process, links between sequenced methods are established to create a process chain considering all influences on a manufactured part in its early design stages. If a finite element solver change occurs within this linkage, it is necessary to transfer and/or transform source mesh bound data to fit the target mesh, if said data may influence any simulation further down the chain. This data transfer, called “mapping”, depends on the utilized allocation and interpolation algorithm. This contribution aims to link the difference in mesh discretization and position to the resulting data quality depending on both meshes as well as various approximation and interpolation procedures. The considered geometry represents a S-shaped profile common in sheet metal forming and subsequent joining whereas the mapped data consist of scalar and tensorial values such as thickness and stresses. It is expected that a large difference in the meshes coupled with certain interpolation methods lead to significant errors during mapping between source- and target-data.

The bond strength between a thermoformed fibre reinforced thermoplastic sheet and an injected polymer is the limiting factor for the structural integrity of overmoulded thermoplastic composites. In this contribution, a simulation based digital twin of the thermoforming process is presented. From numerical parametric studies a reduced order model based on Proper Orthogonal Decomposition (POD) is developed. The combination with machine learning methods enables the real-time computation of arbitrary physical reliable temperature fields with sufficient accuracy to be used for design purposes and as inline quality gates.

In this contribution, a concept is presented that combines different simulation paradigms during the engineering phase. These methods are transferred into the operation phase by the use of data-based surrogates. As an virtual production scenario, the process combination of thermoforming continuous fiber-reinforced thermoplastic sheets and injection overmolding of thermoplastic polymers is investigated. Since this process is very sensitive regarding the temperature, the volatile transfer time is considered in a dynamic process chain control. Based on numerical analyses of the injection molding process, a surrogate model is developed. It enables a fast prediction of the product quality based on the temperature history. The physical model is transferred to an agent-based process chain simulation identifying lead time, bottle necks and quality rates taking into account the whole process chain. In the second step of surrogate modeling, a feasible soft sensor model is derived for quality control over the process chain during the operation stage. For this specific uses case, the production rejection can be reduced by 12% compared to conventional static approaches.

Friction drilling is a widely used process to produce bushings in sheet materials, which are processed further by thread forming to create a connection port. Previous studies focused on the process parameters and did not pay detailed attention to the material flow of the bushing. In order to describe the material behaviour during a friction drilling process realistically, a detailed material characterisation was carried out. Temperature, strain rate, and rolling direction dependent tensile tests were performed. The results were used to parametrise the Johnson–Cook hardening and failure model. With the material data, numerical models of the friction drilling were created using the finite element method in 3D as well as 2D, and the finite volume method in 3D. Furthermore, friction drilling tests were carried out and analysed. The experimental results were compared with the numerical findings to evaluate which modelling method could describe the friction drilling process best. Highest imaging quality to reality was shown by the finite volume method in comparison to the experiments regarding the material flow and the geometry of the bushing.

In this contribution, a computational approach for the manufacturing of multi-material lightweight parts is presented. For an efficient online optimization procedure, a proper orthogonal decomposition on offline obtained numerical results is carried out to construct a surrogate model. The functionality of the proposed framework is demonstrated on a use case study of a multi-material component consisting of a sheet metal basic structure and a plastic reinforcement structure. The manufacturing process chain consists of a deep drawing process followed by an injection molding process of short fiber reinforced plastics. The proposed methodology provides a fast and accurate computational model for structural properties with respect to the process settings.

Fibre-reinforced thermoplastics (FRTP), such as organo sheets or laminates, are increasingly being used in large-scale automotive production. The high weight-saving potential, high specific strengths and stiffnesses as well as processing times suitable for large-scale production are some of the reasons for using these materials. However, the formability of such semi-finished products is severely limited by the fibre reinforcement, which can lead to fibre breakage, fibre displacement or wrinkling in complex-shaped components. In order to increase the formability, an FRTP semi-finished product is developed, which consists of discontinuous tapes. Due to the local sliding of the tape sections, a pseudo-plastic material behaviour is achieved. Experimental uniaxial tensile tests at elevated temperatures are used to investigate the forming behaviour of the material for different tape lengths and overlap lengths. Subsequently, this tensile test is numerically modelled in order to fit the pseudo-plasticity to the experimental data by a virtual parameter identification. With the help of the parameters determined from the numerical tensile test, the sliding behaviour of the tape sections can be used for forming simulations in order to achieve a higher prediction quality.

Hybrid structures made of fiber-reinforced plastics (FRP) and metals are currently in focus of research and industry to develop weight reduced and functional optimized components for lightweight solutions. Manufacturing processes were adapted and developed to produce components based on hybrid materials with high economic efficiency. The cutting process is used to pre-assemble the semi-finished products or to post-process the edges of consolidated parts. The mechanisms of damage edge behavior and possible cutting qualities on these parts are not investigated jet. To close this knowledge gap and to support the future application of hybrid FRP-Metal-Laminates different cutting procedures were studied. This paper shows the process related dependences on the failure behavior of two dimensional specimens. The failure modes are described via quality characteristics like surface roughness, trueness and precision of the cut as well as influences of aging processes. In the end optimized parameter for each process are shown and compared under technical and economic criteria for large scale production. In the scope of this work an experimental study of piercing of glass and carbon fiber reinforced thermoplastic with different steel and bonding agents at different cutting sequences were performed. It was shown that the cutting edge geometry significantly differs. Possible mechanical explanations of the dependencies were formulated. Also the accuracy of the cuts was evaluated which showed a higher accuracy for the steel component. The measurements on the surface roughness could not show any dependencies and relations.

Additive manufacturing of plastic parts is a widely spread production method for prototyping. In the recent past, additionally series applications evolved from different sectors of industry. Especially plasticizing processes are characterised by high printing speed and a broad range of materials which can be provided both as filament and granulate. The latter offers the advantage of lower material costs compared to filaments but requires a screw extruder to plasticise and homogenise the plastic melt prior to its deposition through a nozzle. Screw extruders have a wide processing range and therefore are capable of producing a huge variety of printing bead shapes. This shape is directly affected by several extrusion settings and has a great impact on manufacturing time as well as mechanical properties and surface quality of fabricated parts. It would take great effort to determine the influence of process parameters like temperatures and velocities in experimental trials.

Within product development processes, computational models are used with increasing frequency. However, the use of those methods is often restricted to the area of focus, where product design, manufacturing process, and process chain simulations are regarded independently. In the use case of multi-material lightweight structures, the desired products have to meet several requirements regarding structural performance, weight, costs, and environment. Hence, manufacturing-related effects on the product as well as on costs and environment have to be considered in very early phases of the product development process in order to provide a computational concept that supports concurrent engineering. In this contribution, we present an integrated computational concept that includes product engineering and production engineering. In a multi-scale framework, it combines detailed finite element analyses of products and their related production process with process chain and factory simulations. Including surrogate models based on machine learning, a fast evaluation of production impacts and requirements can be realized. The proposed integrated computational product and production engineering concept is demonstrated in a use case study on the manufacturing of a multi-material structure. Within this study, a sheet metal forming process in combination with an injection molding process of short fiber reinforced plastics is investigated. Different sets of process parameters are evaluated virtually in terms of resulting structural properties, cycle times, and environmental impacts.

In this contribution, the convergence behaviour of simulations with nonlinear viscoelastic models for rubber-like materials using fractional derivatives is investigated. Based on the complex step derivative approximation, numerical approximation schemes for tangent operators on the local and global algorithmic level are analysed. Material models including fractional derivatives usually exhibit numerical difficulties, since the entire stress history of the material has to be considered for the current stress state. Non-classical methods can help to reduce the numerical effort, but the convergence behaviour is not perfect. In this paper, a classical and a non-classical fractional element based viscoelastic material formulation are analysed. The local and the global convergence rate using analytically and numerically derived tangents are investigated and compared to the convergence behaviour of a standard nonlinear viscoelastic model. Numerical examples on rubber materials are exploited, showing the performance of the proposed methods. It can be proven that the outlined numerical differentiation schemes improve the convergence rate, as well as reduce the computation time for the fractional element based material models.

Based on their properties, PPS fibers are a promising material for reinforcing elastomeric components that are subjected to high mechanical and thermal loads. The use of this material is at present hindered because of the low adhesion between the fiber and matrix. Atmospheric pressure plasma treatments based on the dielectric barrier discharge were performed on PPS fibers using air as reactive gas for different treatment durations in order to improve the adhesion. The effects of these treatments have been characterized by determining the surface energy, and the residual tensile strength as well as by analyzing the surface chemistry. Required conditions for an improved wetting behavior and a significant increase in the polar component of the surface energy could then be identified.

In this contribution, we present a model reduction approach for hyperelastic materials based on Proper Orthogonal Decomposition. A separation of the solution into time and space dependent functions is performed, which allows to compute reduced solutions within real time. The functionality of the method is demonstrated by a tensile test and is further applied to a stochastic analysis and a multi-parametric analysis involving non-linear material behaviour and large deformations. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

A stochastic homogenization scheme for the computation of effective elastic properties for damaged micro-heterogeneous materials is presented. The statistics is captured by uncertain material properties as well as stochastic interpolation between the upper and lower Hashin-Shtrikman bounds. The resulting multidimensional stochastic problem is solved via sophisticated Monte Carlo methods and applied to Ultra-High-Performance-Concrete. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)