Now showing 1 - 10 of 16
  • Publication
    Taxonomy for Biological Transformation Principles in the Manufacturing Industry
    ( 2023)
    Berkhahn, Magda
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    Kremer, Gerald
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    ; ;
    Stark, Rainer
    Industry and research are seeking answers to current demands in industrial value creation, like resilience of production, sufficient product quality and sustainability of products and processes. A novel line of thought, seeking the accomplishment of those is the Biological Transformation (BT). BT describes the interweaving of biological modes of action, materials and organisms with engineering and information sciences. The conflation of disciplines from natural, technical and social sciences yields in a heterogeneous field of activities with ambiguous technical terms. An ascertainment of principles of BT is required to classify yet undifferentiated patterns in nature-based production, facilitating their systematic implementation in aiming for sustained solutions on current challenges. With increasing research in biomimetic, attempts arise to capture nature‑based activities in manufacturing through schematic classifications. Yet, basic semantics representing the effective principles of BT in the manufacturing industry is lacking. The goal of this publication is to introduce a taxonomy of Biological Transformation in manufacturing based on its core principles Bio Inspiration, Bio Integration and Bio Interaction. Within the research project BioFusion 4.0, the taxonomy was developed and applied to classify technology innovations. The paper presents the taxonomy, its development and application in use cases.
  • Publication
    Analyse und Nutzung von Aluminium-Bronze-Schleifstaub für das Laser-Pulver-Auftragsschweißen
    ( 2022-12) ;
    Marko, Angelina
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    Kruse, Tobias
    ;
    ;
    Rethmeier, Michael
    Die additive Fertigung verspricht ein großes Potenzial für den maritimen Sektor. Insbesondere Directed Energy Deposition (DED) Verfahren bieten die Möglichkeit, großvolumige maritime Bauteile wie Propellernaben oder -schaufeln herzustellen. Bei der Nachbearbeitung solcher Bauteile fällt in der Regel eine große Menge an Schleifabfällen an. Ziel des vorgestellten Projekts ist die Entwicklung einer nachhaltigen zirkulären AM-Prozesskette für maritime Komponenten auf Basis von Aluminiumbronze-Schleifresten. Dazu soll das Material wiederaufbereitet und anschließend als Rohmaterial für die Herstellung von Schiffspropellern im Laser-Pulver DED-Verfahren verwendet werden. In der vorliegenden Arbeit werden Schleifabfälle mittels dynamischer Bildanalyse untersucht und mit kommerziellem DED-Pulver verglichen. Anschließend werden Probengeometrien aus Schleifstaub gefertigt und durch metallographische Schliffe und REM/EDX analysiert.
  • Publication
    Transferability of ANN-generated parameter sets from welding tracks to 3D-geometries in Directed Energy Deposition
    ( 2022-11-04)
    Marko, Angelina
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    Bähring, Stefan
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    Raute, Maximilian Julius
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    ;
    Directed energy deposition (DED) has been in industrial use as a coating process for many years. Modern applications include the repair of existing components and additive manufacturing. The main advantages of DED are high deposition rates and low energy input. However, the process is influenced by a variety of parameters affecting the component quality. Artificial neural networks (ANNs) offer the possibility of mapping complex processes such as DED. They can serve as a tool for predicting optimal process parameters and quality characteristics. Previous research only refers to weld beads: a transferability to additively manufactured three-dimensional components has not been investigated. In the context of this work, an ANN is generated based on 86 weld beads. Quality categories (poor, medium, and good) are chosen as target variables to combine several quality features. The applicability of this categorization compared to conventional characteristics is discussed in detail. The ANN predicts the quality category of weld beads with an average accuracy of 81.5%. Two randomly generated parameter sets predicted as “good” by the network are then used to build tracks, coatings, walls, and cubes. It is shown that ANN trained with weld beads are suitable for complex parameter predictions in a limited way.
  • Publication
    A study of the magnetohydrodynamic effect on keyhole dynamics and defect mitigation in laser beam welding
    ( 2022)
    Meng, X.
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    Bachmann, M.
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    Artinov, A.
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    In this paper, the highly transient keyhole dynamics, e.g., laser absorption, keyhole geometry, and fluctuation, etc., under a magnetic field are investigated using an experimental approach and multi-physical modeling. The model provides accurate predictions to the variation of penetration depth and weld pool profiles caused by the MHD effect, which is validated by the measurements of optical micrographs and in-situ metal/glass observation. The micro-X-ray computed tomography shows a remarkable reduction of keyhole-induced porosity with the magnetic field. The correlation between the porosity mitigation and the weld pool dynamics influenced by the magnetic field is built comprehensively. It is found that the magnetic field gives a direct impact on the laser energy absorption at the keyhole front wall by changing the protrusion movement. The porosity mitigation comes from multiple physical aspects, including keyhole stabilization, widening of the bubble floating channel, and the electromagnetic expulsive force. Their contributions vary according to the bubble size. The findings provide a deeper insight into the relationship between electromagnetic parameters, keyhole dynamics, and suppression of keyhole-relevant defects.
  • Publication
    Potentials of Design Thinking for knowledge transfer of Model-Based Systems Engineering
    ( 2022)
    Manoury, Marvin Michael
    ;
    Horländer, Toni
    ;
    Zimmermann, Thomas
    Industrial products are becoming increasingly complex due to the use and development of mechatronic systems. This increasing complexity is addressed by virtual representations of the systems in the form of interdisciplinary models. Model-Based Systems Engineering (MBSE) supports product development from the early development phase through validation, verification and integration up to later life cycle phases of the product by means of system modeling.Typical drivers for innovations in the industrial environment are business viability, technology driven feasibility and human driven desirability. While business viability and feasibility are considered in most product development processes and innovation driven projects, the human factor is often neglected in this context. This is addressed by a MBSE Capability and Maturation Matrix (CMM), which consists of capabilities for the acquisition and mastering of the MBSE competencies. The authors have considered Design Thinking as a feasible approach to transfer MBSE knowledge and thus support this acquisition MBSE competencies. This publication shall present the first findings on the application of Design Thinking for the creation of a user-centered MBSE introduction event. This event shall be used in further iterative steps to teach non-experts in the MBSE field the required competencies for their work and thus support the CMM development capability.
  • Publication
    Introducing readiness scales for effective reuse of open source hardware
    ( 2022)
    Mies, Robert
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    ;
    Hassan, Mehera
    Open source hardware (OSH) describes physical products that allow for "anyone to study, modify, produce, and distribute them". While OSH principles aim to support design reuse, recent studies have challenged whether this is properly applied in practice. Therefore, this article delivers an assessment scheme that allows to identify the readiness of OSH designs for reuse. Testing the scheme on OSH ventilator designs collected by the Publnv ventilator project showed overall good usefulness of the scheme and emphasised the need of unambiguous assessment scales based on common standards. Less than two thirds of Publnv's listed projects fulfilled minimum criteria for openness.
  • Publication
    Gear Wheel Finishing with Abrasive Brushing Tools to Improve the Surface Quality of Tooth Flanks for the Industrial Application
    ( 2022)
    Gülzow, Bernhard
    ;
    A high surface quality of tooth flanks can improve the service life and the performance of gears, as well as reduce acoustic emissions. However, high demands on the gear geometry pose a challenge for the finishing of tooth flank surfaces because the dimensional accuracy that can be achieved with modern grinding processes must not be impaired by the finishing process. A preceding study has shown fundamentally that profiled abrasive brushing tools can be used to improve the quality of individual tooth flank surfaces. Due to the integration into the grinding machine, it represents a promising alternative to common finishing applications. Before the process can be used in an industrial environment, process reliability and tool life must be examined. For this purpose, complete reference gearwheels (39 × 10) were finished with the brushing tools. It could be shown that the surface roughness can be reliably reduced by ΔRa ≈ 0.2 µm by using a single brush for an entire gearwheel without changing the gear geometry. In addition to the influence of the tool specifications on the work result, the influence of the initial roughness after grinding was considered in particular. It was found that the achievable surface roughness depends significantly on the depth of the grinding grooves, as these are retained as desired, while the roughness peaks are fully smoothed. Furthermore, a device for the machine-integrated profiling and dressing of brushing tools was successfully designed, implemented, and tested.
  • Publication
    OptTopo: Automated set-point optimization for coupled systems using topology information
    ( 2022)
    Thiele, Gregor
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    Johanni, Theresa
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    Sommer, David
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    Eigel, Martin
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    Krüger, Jörg
    The manufacturing sector has witnessed a rapid rise in the importance of energy-efficient operation. For finding optimal set-points for industrial facilities, optimization problems of increasing complexity occur. Key challenges are the leak of derivative information and the curse of dimensionality. For systematic reduction of the search-space by decomposition of the model, a methodology for the inclusion of topology knowledge in the optimization procedure is developed. An implementation of OptTopo (Optimization based on Topology), embedded in a testbed, demonstrates its advantages compared to popular out-of-the-box-optimization. OptTopo could be integrated in energy management software offering advanced set-point control for complex facilities.
  • Publication
    Influence of superimposed low frequency oscillations on single-pass honing of long-chipping steel
    ( 2022)
    Uhlmann, E.
    ;
    Rozek, André
    Single-pass honing is used as a finishing process to meet high demands regarding form and dimensional accuracy of drilled bores. The disadvantages of single-pass honing compared to the conventional long-stroke honing are high process forces and torques as well as an increased risk of chip space clogging of the abrasive stones. A significant reduction in process forces and torques can be achieved by superimposing the axial movement with oscillations. In this work the kinematic basics of different oscillation parameters and their effects on single-pass honing of long-chipping steel are analyzed. It can be concluded that by superimposing low frequency oscillations in single-pass honing, the process forces and torques as well as the specific energy consumption can be reduced significantly without a decline in surface quality and form accuracy.
  • Publication
    Performance analysis of an adaptive cooling system with primary and secondary heat paths for linear direct drives in machine tools
    ( 2022) ;
    Salein, S.
    Machine tools subjected to high demands regarding productivity and accuracy are faced with the challenge that thermal losses influencing the accuracy negatively. Due to high requirements regarding thermal stability of precision related machine tool components, the focused linear direct drives (LDD) must be tempered by active cooling systems. In machine tools, a sufficient cooling capacity is available, but the cooling is insufficiently adjusted to the process and the individual demand of the heat-inducing as well as precision related components. With the intention to achieve a demand-oriented cooling, the use of thermoelectricity in machine tools is one research objective at the Institute for Machine Tools and Factory Management (IWF). Inspired by the concept of thermoelectric self-cooling (TSC)-systems for electronic devices, an Adaptive Cooling (AC)-system with thermoelectric generators (TEG) for LDD in machine tools is developed and experimentally investigated. In order to enhance the performance of AC-systems, in this research a reduction of the global thermal resistance is focused. A promising approach to achieve this goal is the division of the induced heat flow into a primary and a secondary heat path. For a model-based performance analysis of this approach, a system simulation is presented. To acquire experimental data for model validation, a test bench of the AC-system with primary as well as primary and secondary heat path is put into operation. The comparison of simulative and experimental determined data indicates a predominantly high model prediction accuracy. As a result, the implementation of a secondary heat path enables a reduction of the temperature on the upper surface of the heat source by 24.6% and thus a decrease of the global thermal resistance by 38.1%. Compared to the initial state of the AC-system only with primary heat path, the achieved thermal stability in the precision related machine tool component as well as the self-starting capability is improved.