Now showing 1 - 10 of 16
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Taxonomy for Biological Transformation Principles in the Manufacturing Industry

2023 , Berkhahn, Magda , Kremer, Gerald , Riedelsheimer, Theresa , Lindow, Kai , 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.

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A study of the magnetohydrodynamic effect on keyhole dynamics and defect mitigation in laser beam welding

2022 , Meng, X. , Bachmann, M. , Artinov, A. , Rethmeier, Michael

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.

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Acoustic emission-based process monitoring in the milling of carbon fibre-reinforced plastics

2022 , Uhlmann, E. , Holznagel, Tobias

Milling of fibre-reinforced plastics is a challenging task. The highly abrasive fibres lead to high tool wear and coating failures, which cause increasing process forces and temperatures. Machining with a worn tool, in turn, can result in unwanted workpiece damages such as delamination or fibre protrusion. Reliable monitoring of the process must therefore be able to detect damages to the milling tool and the workpiece alike. The presented process monitoring approach measures the acoustic emission generated by the milling tool cutting edge entering the workpiece with a sensor attached to the tool holder. Specific acoustic emission frequency spectra and waveforms are emitted in the cutting zone for different tool wear states. Coating failures as well as other acoustic emission events due to workpiece damages can be robustly detected and distinguished by feature extraction and signal processing as well. The developed setup, the monitoring parameterisation techniques and signal processing algorithms as well as experimental and monitoring results are presented and discussed in this paper.

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OptTopo: Automated set-point optimization for coupled systems using topology information

2022 , Thiele, Gregor , Johanni, Theresa , Sommer, David , Eigel, Martin , 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.

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Analyse und Nutzung von Aluminium-Bronze-Schleifstaub für das Laser-Pulver-Auftragsschweißen

2022-12 , Müller, Vinzenz , Marko, Angelina , Kruse, Tobias , Biegler, Max , 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.

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Introducing readiness scales for effective reuse of open source hardware

2022 , Mies, Robert , Häuer, Martin , 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.

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Micro-texture dependent temperature distribution of CVD diamond thick film cutting tools during turning of Ti-6Al-4V

2022 , Uhlmann, Eckart , Schröter, D. , Gärtner, Eric

Machining titanium alloys such as Ti-6Al-4V results in a high thermomechanical load on cutting tools and consequently short tool lifes. With respect to a necessary reduction of the resulting cutting tool temperatures, ultrashort pulse (USP) laser fabricated micro-textured rake faces offer direct supply of cooling lubricant into the cutting zone and lead to a reduced heat induction. As a result, micro-textured CVD diamond thick film cutting tools are also capable of machining high-performance materials due to reduced contact temperatures. In the scope of the research, the resulting temperature distribution for micro-textured rake faces will be compared under both dry and wet process conditions. Measurements show a reduction of the resulting cutting tool temperatures of Δϑt = 27.9 % using micro-textured cutting tools compared to non-textured cutting tools. A validated simulation provides valuable information about the contact temperatures enabling a specific development of the micro-texture geometry. As a result, a reduction of the contact temperature between chip and rake face by ΔϑT = 24.7 % was possible.

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Transferability of ANN-generated parameter sets from welding tracks to 3D-geometries in Directed Energy Deposition

2022-11-04 , Marko, Angelina , Bähring, Stefan , Raute, Maximilian Julius , Biegler, Max , Rethmeier, Michael

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.

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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.

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Prediction of the Roughness Reduction in Centrifugal Disc Finishing of Additive Manufactured Parts Based on Discrete Element Method

2022 , Kopp, Marco , Uhlmann, Eckart

One major drawback of additive manufacturing is the poor surface quality of parts, which negatively affects mechanical and tribological properties. Therefore, a surface finishing is necessary in most cases. Due to a high material removal rate, centrifugal disc finishing is a promising mass finishing operation for an effective surface finishing of additive manufactured parts. However, due to machining the workpieces in a freely movable manner, the process is hardly controllable, and the process design is often based on time-consuming and cost-intensive trial-and-error approaches. Especially when it comes to the machining of complex-shaped workpieces, finishing results are barely predictable. Therefore, the aim of this study is to set up a numerical simulation of the centrifugal disc finishing based on the Discrete Element Method (DEM) to predict finishing results. A procedure to determine the required DEM input parameters is presented and the simulation was validated using a freely movable force sensor. The results of the finishing experiments with additive manufactured workpieces made of Ti-6Al-4V were correlated with the simulated results. The derived correlation was used to predict local differences in the roughness reduction, which occurred when finishing workpieces with a limited accessibility to the surface. As a result, it is concluded that the complex relationship between the type of media, the accessibility to the surface, and the achievable finishing results can be modeled using the DEM.