Klaus Dröder

Increasing the Structural Integrity of Hybrid Plastics-Metal Parts by an Innovative Mechanical Interlocking Effect

In order to exploit full potential of hybrid materials, it is necessary to develop optimized load-dependent component designs, new manufacturing processes and joining technologies. Structural integrity concerning the interfaces between the single materials of the hybrid component poses a key factor to success. In this case, adhesion often constitutes the limiting factor for the maximum transferable load. In this investigation, a load-oriented innovative concept to increase the structural integrity of hybrid plastic-metal parts was developed. Local mechanical undercuts on the metal surface were created to generate an additional mechanical interlocking effect between the join partners. The aim is to find the best surface structure geometry to enhance mechanical bonding. Therefore, metal samples were structured by a new process and transferred to hybrid specimens by injection molding. For comparison, specimens with adhesive bonding (epoxy resin) of metal and plastic were prepared. The join partners aluminum AlCuMg1-2017 and PA6 as well as PA6GF30 were investigated. The evaluation of an increase in the structural integrity was determined using tensile tests. A significant improvement in joint strength compared with direct joining using adhesive bonding was achieved.

Novel form-flexible handling and joining tool for automated preforming

Abstract The production rates of carbon fiber reinforced plastic (CFRP) parts are rising constantly which in turn drives research to bring a higher level of automation to the manufacturing processes of CFRP. Resin transfer molding (RTM), which is seen as a production method for high volumes, has been accelerated to a high degree. However, complex net-shape preforms are necessary for this process, which are widely manually manufactured. To face these challenges a new concept for the manufacturing of carbon fiber preforms with a form-flexible gripping, draping and joining end-effector is presented and discussed. Furthermore, this paper investigates the application of this concept, describes the initial build-up of a demonstrator, focusing on material selection and heating technology, and discusses test results with the prototype. This prototype already validates the feasibility of the proposed concept on the basis of a generic preform geometry. After a summary, this paper discusses future in-depth research concerning the concept and its application in more complex geometries.

Disassembly Planning and Assessment of Automation Potentials for Lithium-Ion Batteries

Traction batteries are composed of various materials that are both economic valuable and environmentally relevant. Being able to recover these materials while preserving its quality is not only economically attractive, but it can also contribute to decrease the environmental impact of electric vehicles. Disassembly can play in this regard a key role. On the one hand it might allow to separate potential hazardous substances and avoid an uncontrolled distribution of these substances into other material flows. One the other hand disassembly might promote improving the rate of material recovered while preserving its quality and decreasing disassembly costs. In this chapter we present a methodology for the estimation of disassembly sequences and for the estimation of automation potentials for the disassembly of traction batteries. The methodology is illustrated with an experimental case study.

Safe, Flexible and Productive Human-Robot-Collaboration for Disassembly of Lithium-Ion Batteries

The rising number of electric vehicles will lead to an increase of EV batteries reaching their end-of-life. Efforts are therefore being made to develop technologies and processes for recycling, remanufacturing and reusing EV batteries. One important and necessary step for the recycling process is the disassembly of EOL EV batteries. Unpredictable lot sizes and volumes, as well as significant variations in battery design between different car models challenges the disassembly automation. Disassembly is therefore currently carried out manually. Fully-automated disassembly would require high product specific investments which is not economically feasible in changing production environments. Human robot collaboration aims to overcome those problems with partial-automation by incorporating sensor integrated robotics in more fields of human activity. This chapter presents the implementation of human robot collaboration for disassembly of lithium-ion Batteries. While the human operator performs the more complex tasks, the robot performs simple, repetitive tasks such as removing screws and bolts. An intuitive programming environment, which does not require experience in robot programming, is combined with cost efficient tooling and additional 3D safety sensors to realize a safe, productive and ergonomic workspace.

Development of a Shotcrete 3D-Printing (SC3DP) Technology for Additive Manufacturing of Reinforced Freeform Concrete Structures

In this paper, a novel Additive Manufacturing (AM) technique for robot-based fabrication of large-scale freeform reinforced concrete elements is presented. The AM technology, called Shotcrete 3D Printing (SC3DP), is based on an automated shotcreteing process and offers the ability to integrate structural reinforcement in both principal directions and enables printing of horizontal cantilevers onto vertical surfaces. Moreover, the SC3DP technique effectively addresses the problem of cold joints that is inherent to other 3D printing techniques. However, as controlling the process parameters of the SC3DP technique is significantly more complex than it is for conventional 3D concrete printing processes, several closed-loop online control routines were developed and integrated. The resulting gain of control for this adaptive fabrication process is demonstrated through a case study for the production of a complexes reinforced concrete component. Moreover, its conceptual implications are discussed and an outlook for future work is given.

Automated Additive Manufacturing of Concrete Structures without Formwork - Concept for Path Planning

At the Digital Building Fabrication Laboratory in Braunschweig, automated additive manufacturing of concrete structures without formwork is researched. The system consists of a six-axis robot and a three-axis milling machine, which are each connected to a three-axis portal. At the robot a shotcrete sprayer is installed to generate concrete structures. In this paper a first path planning concept for the robot is described. The given algorithm calculates from the CAD data of an object a path for the robot. A difficulty of path planning is that the shotcrete application depends on various parameters. Therefore, a simplified model for the shotcrete application is developed. For the purpose of error minimization while spraying, an online monitoring approach by using a laser scanner is presented.

Mediendichte Hybridverbunde für fluidführende Gehäusestrukturen

Prozessanforderungen für den hybriden Verbund Hybridverbunde aus Metallen und Kunststoffen kombinieren die werkstoff lichen Vorteile verschiedener Materialklassen und liefern somit effiziente Leichtbaulösungen für den Automobilbau. In der Regel wird dabei ein metallischer Werkstoff partiell durch einen faserverstärkten Kunststoff substitutiert. Im entstehenden Hybridverbund sind die unterschiedlichen Werkstoffe dann stoff-, kraftoder formschlüssig angebunden. Möglich ist auch die Kombination von Anbindungsmechanismen, beispielsweise über Haftvermittler oder Mikro-/Makroverklammerungen. Je nach Bauteilanforderungen resultiert dies in einer anspruchsvol-

Media-tight Hybrid Composites for Fluid-bearing Housing Structures

bonded. It is also possible to combine bonding mechanisms, for example by using bonding agents or micro/macro form-locking. Depending on component requirement this results in challenging development of proven large-scale production technologies, such as conventional injection molding or thermopressing. For the former, for example, a semi-finished metal insert can be injected directly within the cavity. For the hybridization of case structures, the media-tight design of the boundary surface architecture between the two material classes is particularly important, since it must be tight against vehicle-relevant f luids. The production technology used for this must be aligned and optimized along the entire proHybrid Composites

Development of Novel Fe-Based Coating Systems for Internal Combustion Engines

Nowadays, combustion engines are the most common way to power vehicles. Thereby, losses occur due to cooling, exhaust gas and friction. With regard to frictional losses, highest potentials for optimization can be found in the tribological system of the inner surface of combustion chamber and piston ring. Besides friction, corrosive stress increases, e.g., due to utilization of exhaust gas recovery. In order to save energy, reduce emissions and enhance the life span of combustion engines, the demand for innovative coating material systems, especially for the inner surface of combustion chamber, increases. This study focuses on the development of innovative iron-based coating materials for the combustion chamber. As a first step, the plasma transferred wire arc and rotating single wire arc (RSW) technologies were compared using 0.8% C-steel as a reference. Subsequently, RSW was used for coating deposition using an innovative iron-based feedstock material. In order to improve wear and corrosion resistance, boron and chromium were added to the feedstock material. After deposition, different honing topographies were manufactured and compared under tribological load. Furthermore, electrochemical corrosion tests were conducted using an electrolyte simulating the exhaust gas concentrate. Especially with regard to corrosion, the novel coating system FeCrBMn showed promising results.

DEVELOPMENT OF AN AUTOMATED ASSEMBLY PROCESS SUPPORTED WITH AN ARTIFICIAL NEURAL NETWORK

A central problem in automated assembly is the ramp-up phase. In order to achieve the required tolerances and cycle times, assembly parameters must be determined by extensive manual parameter variations. Therefore, the duration of the ramp-up phase represents a planning uncertainty and a financial risk, especially when high demands are placed on dynamics and precision. To complete this phase as efficiently as possible, comprehensive planning and experienced personnel are necessary. In this paper, we examine the use of machine learning techniques for the ramp-up of an automated assembly process. Specifically we use a deep artificial neural network to learn process parameters for pick-and-place operations of planar objects. We describe how the handling parameters of an industrial robot can be adjusted and optimized automatically by artificial neural networks and examine this approach in laboratory experiments. Furthermore, we test whether an artificial neural network can be used to optimize assembly parameters in process as an adaptive process controller. Finally, we discuss the advantages and disadvantages of the described approach for the determination of optimal assembly parameters in the ramp-up phase and during the utilization phase.