Prozessstrategien für das automatisierte Preforming von bebinderten textilen Halbzeugen mit einem segmentierten Werkzeugsystem

Stamp preforming offers high potential for the production of complex, shell-shaped preforms, which is a key process in the manufacturing of continuous fibre-reinforced plastics.An innovative approach to improve preform quality consists in a segmented tooling system. The tooling system provides a multitude of options for tool segmentation and sequence, so that an intuitive definition of the tool setting is no longer possible. In addition, sequential closing of the tool segments changes the forming temperature and duration. Suitable activation parameters for the binder must therefore be defined to ensure low resistance to deformation and sufficient stability after the forming process. The objective of this thesis constitutes in the development of a method that defines the process strategy for preforming with a segmented tooling system based on a material and a component geometry. The process strategy includes tool segmentation and sequence as well as activation time and temperature. In this thesis, different models are developed and validated to define the process strategy, which are then combined into a systematic procedure. A simplified temperature model enables the calculation of the start and end temperature of the forming process for different tool segmentations and sequences depending on the material and contact parameters. The stability of the preform requires a balanced inter- and intra-laminar binder content. To determine this aspect, an impregnation model is presented. That way, a minimum forming and activation temperature as well as a short activation time can be identified. The definition of the tool segmentation is based on a geometric analysis of the part. The tool sequence is optimised by coupling an FE-based forming model with a genetic algorithm that minimises wrinkling in the preform. On the basis of two independent parts, the procedure to increase preform quality is validated. It is thus possible to produce more complex parts by defining a process strategy for preforming with a segmented tooling system compared to a non-segmented forming tool

Modelling of the temperature distribution of spot-weldable composite/metal joints

Resistance spot welding is the most economical joining method for the production of automotive steel bodies. In modern car body construction, however, its future applicability is limited due to the growing mix of materials in multi-material design. In response to increasing weight reduction requirements to protect the environment and natural resources, lightweight materials, and fibre-reinforced plastics (FRP) in particular, are more and more used in modern vehicle bodies. To facilitate the future joining of FRP/steel structures with resistance spot welding, spot-weldable force-introduction elements may be embedded in the laminate as a joining interface. When welding the so-called inserts, thermal damage to the surrounding polymer should be avoided, as this is the only way to calculate the strength of the joint correctly. For this purpose, the paper presents a numerical model that allows the prediction of the temperature propagation during spot welding of FRP/steel joints with embedded inserts. The simulative approach is subsequently validated by comparison with experimentally determined temperature curves and in doing so, an excellent model prediction can be noted

Image based control system for improving fiber injection molding process

Fiber injection molding is an innovative process for the resource-efficient production of near net-shape long fiber preforms. The filling of the mold is crucial for the repeatability and uniformity of the produced preforms. For improving the fiber injection process a control system based on image processing has been developed. With a camera the current mold filling is recorded and processed by artificial neural networks. This information on the filling state is used for an adaptive control of the injection nozzle. The control system is validated experimentally with results showing improved reproducibility of the fiber injection molding process

Method for the Investigation of Mold Filling in the Fiber Injection Molding Process Based on Image Processing

Fiber Injection Molding is an innovative process for manufacturing 3D fiber formed parts. Within the process fibers are injected in a special mold through a movable nozzle by an air stream. This process allows a resource efficient production of near net-shape long fiber-preforms without cutting excess. For the properties of the preforms the mold filling is decisive, but current state of the art lacks methods to monitor mold filling online. In this paper a system for monitoring the mold filling based on image processing methods is presented. Therefor a camera and back-lighting has been integrated into a fiber injection mold. The detected filling level and fiber distribution is passed to the PLC of the fiber injection molding machine, which allows the operator to monitor the current mold filling state by means of a visual display. The image processing approach consists of preprocessing, binarization and segmentation. For the preprocessing and binarization several methods including a k-means algorithm, the Otsu thresholding method and a convolutional artificial neural network have been implemented and evaluated. Additionally the illumination of the mold has been investigated and found to have a very large influence on the quality of the results of all investigated methods. The results of the binarization are evaluated on the basis of ground truth images, where an absolute difference between labeled and binarized images is formed and the number of misinterpreted pixels is counted. Among the investigated methods, the method based on the Otsu threshold has been found to be the most efficient with regard to the achievable performance as well as to the correct detection of the current filling. The investigated approach allows the acquisition of more data about the mold filling process to improve models

Secure Clamping of Parts for Disassembly for Remanufacturing

Robot based remanufacturing of valuable products is commonly perceived as promising field in future in terms of an efficient and globally competitive economy. Additionally, it plays an important role with regard to resource-efficient manufacturing. The associated processes however, require a reliable non-destructive disassembly. For these disassembly processes, there is special robot periphery essential to enable the tasks physically. Unlike manufacturing, within remanufacturing there are End-of-Life (EoL) products utilized. The specifications and conditions are often uncertain and varying. Consequently the robot system and especially the periphery needs to adapt to the used product, based on an initial examination and classification of the part. State of the art approaches provide limited flexibility and adaptability to the disassembly of electric motors used in automotive industry. Especially the geometrical shape is a limiting factor for using state of the art periphery for remanufacturing. Within this contribution a new kind of flexible clamping device for the disassembly of EoL electrical motors is presented. The robot periphery is systematically developed regarding the requirements stemming from the remanufacturing approach. It consists of three clamping units with moveable pins. Utilizing two linear axes, a two dimensional working space is realized for clamping the parts depending on their conditions and shape

Production of hybrid tubular metal-fibre preforms: development of a digital twin for the draping process

Hybrid shafts or rods with a metallic end fitting and a load transmitting area made of fibre reinforced plastics possess a great potential in terms of lightweight design, e.g. in automotive industry or aviation. One essential and quality-defining process step in the manufacturing of such parts is the draping of dry braided fibre fabrics onto the shape of the metallic end fitting. To explore the immature draping process and to derive the draping tool geometry a digital twin based on finite element simulation has been developed and validated by first experiments

Analysis of Basis Weight Uniformity Indexes for the Evaluation of Fiber Injection Molded Nonwoven Preforms

Fiber injection molding is an innovative approach for the manufacturing of nonwoven preforms but products currently lack a homogeneous fiber distribution. Based on a mold-integrated monitoring system, the uniformity of the manufactured preforms will be investigated. As no universally accepted definition or method for measuring uniformity is accepted yet, this article aims to find a suitable uniformity index for evaluating fiber injection molded nonwovens. Based on a literature review, different methods are implemented and used to analyze simulated images with given distribution properties, as well as images of real nonwovens. This study showed that quadrant-based methods are suitable for evaluating the basis weight uniformity. It has been found that the indexes are influenced by the number of quadrants. Changes in sample size do not affect the indexes when keeping the quadrant number constant. The quadrants-based calculation of the coefficient of variation showed the best suitability as it shows good robustness and steady index for varying degrees of fiber distribution