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PublicationEntwicklung eines Prozess- und Informationsmodells für das Produktlebenszyklusmanagement in der digitalen Transformation(Fraunhofer Verlag, 2023)Die Digitalisierung erfordert von industriellen Unternehmen, reaktionsfähig neue Kundenbedürfnisse zu bedienen. Der tägliche Umgang mit digitalen Technologien verändert die Erwartungen der Nutzer an Produkte und Services. Um im Wettbewerb zu bestehen, sind Geschäftsmodelle konsequent kundenorientiert auszurichten und permanent anzupassen. Innovationen ressourceneffizient und schnell in Form von Produkten und Services zu operationalisieren, setzt voraus, dass die Prozesse und Systeme von Unternehmen ein durchgängiges, anpassbares und transparentes Wissens-, Informations- und Datenmanagement gewährleisten. In dieser Arbeit wird ein Modell für ein strukturiertes Vorgehen entwickelt, um neue Geschäftsmodelle zu gestalten und die dafür notwendigen Adaptionen des Produktlebenszyklusmanagements vorzunehmen. Die Anforderungen an das Modell werden anhand der praxisbezogenen Aktionsforschung und qualitativer Untersuchungsmethoden abgeleitet. Darauf aufbauend erfolgt die Modellbildung, in die konkrete Techniken und Handlungsanleitungen einfließen. Anschließend wird das Modell durch den Use Case „Automatisiertes Laden“ evaluiert.
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PublicationStudie zur Stärkung der Holzbauwirtschaft in der Metropolregion Berlin-Brandenburg(Fraunhofer IPK, 2023)Berlin verfolgt das Ziel, sich bis zum Jahr 2050 zu einer klimaneutralen Stadt zu entwickeln: Im Vergleich zur Gesamtsumme der CO2-Emissionen des Jahres 1990, sollen diese bis 2030 um mindestens 60 Prozent und bis zum Jahr 2050 um mindestens 85 Prozent verringert werden. Fast ein Drittel der CO2-Emissionen in Deutschland kann dem Gebäudebereich zugerechnet werden. Einen enormen Hebel zur Verbesserung der Klimabilanz bietet der konsequente Einsatz von Baumaterialien auf Basis nachwachsender Rohstoffe. Insbesondere der Baustoff Holz kann für die Metropolregion Berlin-Brandenburg eine zentrale Stellung zur Erreichung der Klimaziele einnehmen. Hierzu wurde bereits im Frühjahr 2021, in der Vorhabensliste1 des Strategischen Gesamtrahmens Hauptstadtregion, eine regionale Holzbau-Offensive festgehalten. Diese hat zum Ziel, die Region Berlin-Brandenburg zu einer Region des Holzbaus zu entwickeln. Damit die holzbasierte Transformation des Bauens in der Hauptstadtregion nachhaltig gelingt, ist insbesondere eine starke kreislaufwirtschaftsbasierte regionale Holzbauwirtschaft von Bedeutung.
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PublicationA Data-Driven Concept and Realization for Engineering Change Management Decision Support(Fraunhofer Verlag, 2023)In today's automotive industry, quickly reacting to engineering changes and providing market-driven products within a short period remains a competence for all Original Equipment Manufacturers (OEMs). Due to the complexity of products, changes to one component can lead to unexpected chain reactions in others. Besides, from creation to the approval of a change request can take weeks or even months without apparent reasons for the delays. To coordinate and control changes, companies established Engineering Change Management (ECM) processes. ECM processes can impact all determinants of competition of products: cost, quality, and time-to-market. Without proper management of Engineering Changes (ECs), negative impacts will happen. In the scope of this dissertation, a machine-learning based ECM decision support solution is developed which includes two main functions: change impacts prediction and lead time prediction. These functions support engineers to have an overview of change consequences in the early phase of the ECM process. The solution was evaluated based on the data from an automotive company and reached good performance. Therefore it was rated as beneficial to increase the efficiency, effectiveness, and quality of the existing ECM processes.
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PublicationInfraschallunterstütztes Dornhonen(Fraunhofer Verlag, 2023)Der Einsatz von Schwingungen bei Fertigungsverfahren ist seit Jahrzehnten ein allgegenwärtiges Thema in der Forschung. Die Vorteile lassen sich insbesondere an verringerten Bearbeitungskräften und damit an der Steigerung der Wirtschaftlichkeit und Ressourcenschonung erkennen. Die Komplexität des zielgerichteten Einsatzes, wie die Notwendigkeit zusätzlicher Aktuatoren und die konstruktive und schwingungstechnische Auslegung der Komponenten und Prozessbedingungen, verhindert jedoch den industriellen Einsatz. Innerhalb dieser Arbeit werden Dornhonprozesse untersucht, bei denen zusätzliche Schwingungen mit Hilfe der integrierten Antriebe eines Bearbeitungszentrums realisiert werden. Dafür werden realisierbare Schwingungsparameter und resultierende Veränderungen der Prozessparameter analysiert. Zur Identifikation von Prozessveränderungen dienen ein geometrisch kinematisches Durchdringungsmodell sowie Einkornritzversuche. An Werkstücken aus Gusseisen mit Lamellengraphit werden die Auswirkungen von erzwungenen Schwingungen beim Dornhonen technologisch untersucht. Die Arbeit leistet einen Beitrag zum Verständnis sowie zur Auslegung und Nutzung der infraschallunterstützten Dornhonbearbeitung.
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PublicationResource efficient production of car body parts - implementation of digital twins across process chains( 2022-09-21)
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PublicationResult quality evaluation of Directed Energy Deposition Additive Manufacturing simulations with progressive simplification of transient heat-source motion( 2022-09-05)
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PublicationInvestigation of liquid metal embrittlement avoidance strategies for dual phase steels via electro-thermomechanical finite element simulation( 2022-06)Modern advanced high-strength steel (AHSS) sheets used in automotive body construction are mostly zinc coated for corrosion resistance. The presence of zinc can cause cracking in steels due to liquid metal embrittlement (LME) during resistance spot welding (RSW). In combination with factors such as tensile strains, liquid zinc can lead to the formation of brittle, intergranular cracks in the weld and heat affected zone. While practical investigations to mitigate LME occurrence exist, the reason why a certain parameter might cause or prevent LME is often unknown. Numerical resistance spot welding simulation can visualize the underlying stresses, strains and temperatures during the welding process and investigate experimentally unmeasurable phenomena. In this work, a 3-dimensional electro-thermomechanical finite element approach is used to assess and investigate the critical parameters leading to LME occurrence. Experimentally observed crack sizes are correlated with the corresponding local strain rates and temperature exposure durations in the simulation. With this data, a map of LME occurrence over driving influence factors is drafted and discussed for effectiveness.
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PublicationIntegrated weld preparation designs for the joining of L-PBF and conventional components via TIG welding( 2022-04-18)Laser powder bed fusion (L-PBF) of entire assemblies is not typically practical for technical and economic reasons. The build size limitations and high production costs of L-PBF make it competitive for smaller, highly complex components, while the less complex elements of an assembly are manufactured conventionally. This leads to scenarios that use L-PBF only where it's beneficial, and it require an integration and joining to form the final product. For example, L-PBF combustion swirlers are welded onto cast parts to produce combustion systems for stationary gas turbines. Today, the welding process requires complex welding fixtures and tack welds to ensure the correct alignment and positioning of the parts for repeatable weld results. In this paper, L-PBF and milled weld preparations are presented as a way to simplify the Tungsten inert gas (TIG) welding of rotationally symmetrical geometries using integrated features for alignment and fixation. Pipe specimens with the proposed designs are manufactured in Inconel 625 using L-PBF and milling. The pipe assembly is tested and TIG welding is performed for validation. 3D scans of the pipes before and after welding are evaluated, and the weld quality is examined via metallography and computed tomography (CT) scans. All welds produced in this study passed the highest evaluation group B according to DIN 5817. Thanks to good component alignment, safe handling, and a stable welding process, the developed designs eliminate the need for part-specific fixtures, simplify the process chain, and increase the process reliability. The results are applicable to a wide range of components with similar requirements.
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PublicationQuality Prediction in Directed Energy Deposition Using Artificial Neural Networks Based on Process Signals( 2022-04-14)The Directed Energy Deposition process is used in a wide range of applications including the repair, coating or modification of existing structures and the additive manufacturing of individual parts. As the process is frequently applied in the aerospace industry, the requirements for quality assurance are extremely high. Therefore, more and more sensor systems are being implemented for process monitoring. To evaluate the generated data, suitable methods must be developed. A solution, in this context, was the application of artificial neural networks (ANNs). This article demonstrates how measurement data can be used as input data for ANNs. The measurement data were generated using a pyrometer, an emission spectrometer, a camera (Charge-Coupled Device) and a laser scanner. First, a concept for the extraction of relevant features from dynamic measurement data series was presented. The developed method was then applied to generate a data set for the quality prediction of various geometries, including weld beads, coatings and cubes. The results were compared to ANNs trained with process parameters such as laser power, scan speed and powder mass flow. It was shown that the use of measurement data provides additional value. Neural networks trained with measurement data achieve significantly higher prediction accuracy, especially for more complex geometries.
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PublicationLearning Demonstrator for Anomaly Detection in Distributed Energy Generation( 2022-04-07)Machine learning based anomaly detection methods on process data can be used to secure critical infrastructure. The design and installation of these methods require detailed understanding of both the facilities and the machine learning methods. Therefore, they are mostly incomprehensible for non-experts and thus acting as a barrier hindering the fast spread of such technologies. This article presents the systematic development of a demonstrator which enables presentations of anomaly detection on the example of a simulated wind farm. The specially designed user-interface allows a comprehensive experience. This article documents the use of the demonstrator for experts experienced in energy systems which are interested in the application of machine learning algorithms.
