@article{32813, author = {{Martin, Sven and Kurtusic, Kristijan and Tröster, Thomas}}, journal = {{Key Engineering Materials}}, location = {{Braga}}, title = {{{Influence of the Surrounding Sheet Geometry on a Clinched Joint}}}, doi = {{ https://doi.org/10.4028/p-09md1c}}, volume = {{927}}, year = {{2022}}, } @article{34000, abstract = {{Abstract This paper presents the characterization of the microstructure evolution during flow forming of austenitic stainless steel AISI 304L. Due to plastic deformation of metastable austenitic steel, phase transformation from γ-austenite into α’-martensite occurs. This is initiated by the formation of shear bands as product of the external stresses. By means of coupled microscopic and micromagnetic investigations, a characterization of the microstructure was carried out. In particular, this study shows the distribution of the strain-induced α’-martensite and its influence on material properties like hardness at different depths. The microstructural analyses by means of electron backscattered diffraction (EBSD) technique, evidence a higher amount of α’-martensite (ca. 23 %) close to the outer specimen surface, where the plastic deformation and the direct contact with the forming tool take place. In the middle area (ca. 1.5 mm depth from the outer surface), the portion of transformed α’-martensite drops to 7 % and in the inner surface to 2 %. These results are well correlated with microhardness and micromagnetic measurements at different depths. EBSD and atomic force microscopy (AFM) were used to make a detailed characterization of the topography and degree of deformation of the shear bands. Likewise, the mechanisms of nucleation of α’-martensite were discussed. This research contributes to the development of micromagnetic sensors to monitor the evolution of properties during flow forming. This makes them more suitable for closed-loop property control, which offers possibilities for an application-oriented and more efficient production.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2195-8599}}, journal = {{Practical Metallography}}, keywords = {{Metals and Alloys, Mechanics of Materials, Condensed Matter Physics, Electronic, Optical and Magnetic Materials}}, number = {{11}}, pages = {{660--675}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Coupled microscopic and micromagnetic depth-specific analysis of plastic deformation and phase transformation of metastable austenitic steel AISI 304L by flow forming}}}, doi = {{10.1515/pm-2022-0064}}, volume = {{59}}, year = {{2022}}, } @article{33999, abstract = {{The production of complex multi-functional, high-strength parts is becoming increasingly important in the industry. Especially with small batch size, the incremental flow forming processes can be advantageous. The production of parts with complex geometry and locally graded material properties currently depicts a great challenge in the flow forming process. At this point, the usage of closed-loop control for the shape and properties could be a feasible new solution. The overall aim in this project is to establish an intelligent closed-loop control system for the wall thickness as well as the α’-martensite content of AISI 304L-workpieces in a flow forming process. To reach this goal, a novel sensor concept for online measurements of the wall thickness reduction and the martensite content during forming process is proposed. It includes the setup of a modified flow forming machine and the integration of the sensor system in the machine control. Additionally, a simulation model for the flow forming process is presented which describes the forming process with regard to the plastic workpiece deformation, the induced α’-martensite fraction, and the sensor behavior. This model was used for designing a closed-loop process control of the wall thickness reduction that was subsequently realized at the real plant including online measured feedback from the sensor system.}}, author = {{Kersting, Lukas and Arian, Bahman and Vasquez, Julian Rozo and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, issn = {{1662-9795}}, journal = {{Key Engineering Materials}}, keywords = {{Mechanical Engineering, Mechanics of Materials, General Materials Science}}, pages = {{862--874}}, publisher = {{Trans Tech Publications, Ltd.}}, title = {{{Innovative Online Measurement and Modelling Approach for Property-Controlled Flow Forming Processes}}}, doi = {{10.4028/p-yp2hj3}}, volume = {{926}}, year = {{2022}}, } @inproceedings{36563, author = {{Rozo Vasquez, Julian and Walther, Frank and Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar}}, booktitle = {{Proceedings of the 14th International Conference on Barkhausen Noise and Micromagnetic Testing}}, location = {{Stockholm}}, title = {{{Soft sensor concept for micromagnetic depth-specific analysis of phase transformation during flow forming of AISI 304L steel.}}}, year = {{2022}}, } @book{36412, author = {{Kersting, Lukas and Trächtler, Ansgar and Arian, Bahman and Homberg, Werner and Rozo Vasquez, Julian and Walther, Frank}}, isbn = {{978-3-948749-23-1 }}, publisher = {{Diedrich}}, title = {{{Echtzeitfähige Modellierung eines innovativen Drückwalzprozesses für die eigenschaftsgeregelte Herstellung gradierter Bauteile.}}}, year = {{2022}}, } @article{30228, abstract = {{Confidence in additive manufacturing technologies is directly related to the predictability of part properties, which is influenced by several factors. To gain confidence, online process monitoring with dedicated and reliable feedback is desirable for every process. In this project, a powder bed monitoring system was developed as a retrofit solution for the EOS P3 laser sintering machines. A high-resolution camera records each layer, which is analyzed by a Region-Based Convolutional Neural Network (Mask R-CNN). Over 2500 images were annotated and classified to train the network in detecting defects in the powder bed at a very high level. Each defect is checked for intersection with exposure areas. To distinguish between acceptable imperfections and critical defects that lead to part rejection, the impact of these imperfections on part properties is investigated.}}, author = {{Klippstein, Sven Helge and Heiny, Florian and Pashikanti,, Nagaraju and Gessler, Monika and Schmid, Hans-Joachim}}, journal = {{JOM - The Journal of The Minerals, Metals & Materials Society (TMS)}}, location = {{Online}}, pages = {{1149–1157}}, publisher = {{Springer}}, title = {{{Powder Spread Process Monitoring in Polymer Laser Sintering and its Influences on Part Properties}}}, doi = {{https://doi.org/10.1007/s11837-021-05042-w }}, volume = {{74}}, year = {{2022}}, } @inproceedings{33356, abstract = {{By monitoring the recoating process within polymer laser sintering production, it was shown that multiple powder-spread-flaws can be detected. Those groove-like flaws are expected to be the result of agglomerates jamming between the recoater and the last powder layer. This work is analyzing the interaction between powder-spread-flaws and part properties, showing the influence of the recoating process on the performance of laser sintering parts. Therefore, artificial powder-spread-flaws are applied to the build jobs of tensile test specimens which are measured and analyzed regarding the elongation at break, strength and fracture position. For the characteristics of the flaws, the artificial grooves are varied in depth and width. Furthermore, the position of the flaw is changed form mid part to close to surface areas. It was shown, that several flaws are visible at the part surface, resulting in stress concentration and reduced performance. But there are as well parts with flaw-layers, which are not visible after the build process on the part. Those parts can have significantly reduced mechanical properties as well.}}, author = {{Klippstein, Sven Helge and Schmid, Hans-Joachim}}, booktitle = {{Proceedings of the 33nd Annual International Solid Freeform Fabrication Symposium}}, keywords = {{Selective Sasersintering, Process Monitoring, Powder Spread}}, title = {{{Powder Spread Flaws in Polymer Laser Sintering and its Influences on Mechanical Performance}}}, year = {{2022}}, } @inproceedings{44838, author = {{Yigitbas, Enes}}, publisher = {{die hochschullehre Jahrgang 8/2022}}, title = {{{Einsatz und Evaluation von Virtual Reality-Technologie in einem Informatik-Seminar}}}, year = {{2022}}, } @inproceedings{46289, author = {{Banh, Ngoc Chi and Scharlau, Ingrid and Rohlfing, Katharina J.}}, booktitle = {{52. Kongress der Deutschen Gesellschaft für Psychologie}}, editor = {{Bermeitinger, Christina and Greve, Werner }}, location = {{Hildesheim, Germany}}, title = {{{Folgen wiederholter Negation auf die Aufmerksamkeit}}}, year = {{2022}}, } @inproceedings{31871, author = {{Kletetzka, Ivo and Klippstein, Sven Helge}}, booktitle = {{3D-DRUCK HAUTNAH - Der Einfluss einer Zukunftstechnologie auf unser Leben }}, location = {{Paderborn}}, publisher = {{Universität Paderborn}}, title = {{{Pulver im 3D-Druck - von Mascarabürsten bis zum Interieur eines Mini-Coopers (Vortrag)}}}, year = {{2022}}, } @misc{43011, author = {{Hanselle, Felix Paul}}, title = {{{Untersuchung und Modellierung der Materialeigenschaften von glaskugelgefüllten, im Lasersinterprozess verarbeiteten Dry-Blends}}}, year = {{2022}}, } @misc{43010, author = {{Kosanke, Maren}}, title = {{{Oberflächenmodifikation von Glaskugeln zur Verbesserung der Adhäsion im Lasersinterverfahren}}}, year = {{2022}}, } @misc{43007, author = {{Henke, Frederic}}, title = {{{Potenzialanalyse für die Nutzung additiver Fertigungsverfahren bei einem Büromöbelhersteller und Realisierung eines Beispielbauteils (Studienarbeit)}}}, year = {{2022}}, } @misc{46858, author = {{Ostermeier, Jakob}}, title = {{{Einfluss des Lasersinter-Prozesses auf die Recyclingfähigkeit von flammgeschütztem PA12 Pulver}}}, year = {{2022}}, } @misc{43012, author = {{Sural, Ilknur}}, title = {{{Einfluss der Lagerdauer von PA12- Lasersinterpulver auf die Verarbeitungs- und Bauteileigenschaft}}}, year = {{2022}}, } @book{47417, author = {{Föllinger, Otto and Konigorski, Ulrich and Lohmann, Boris and Roppenecker, Günter and Trächtler, Ansgar}}, publisher = {{VDE-Verlag}}, title = {{{Regelungstechnik. Einführung in die Methoden und ihre Anwendung}}}, year = {{2022}}, } @inproceedings{51343, abstract = {{This paper presents preliminary work on the formalization of three prominent cognitive biases in the diagnostic reasoning process over epileptic seizures, psychogenic seizures and syncopes. Diagnostic reasoning is understood as iterative exploration of medical evidence. This exploration is represented as a partially observable Markov decision process where the state (i.e., the correct diagnosis) is uncertain. Observation likelihoods and belief updates are computed using a Bayesian network which defines the interrelation between medical risk factors, diagnoses and potential findings. The decision problem is solved via partially observable upper confidence bounds for trees in Monte-Carlo planning. We compute a biased diagnostic exploration policy by altering the generated state transition, observation and reward during look ahead simulations. The resulting diagnostic policies reproduce reasoning errors which have only been described informally in the medical literature. We plan to use this formal representation in the future to inversely detect and classify biased reasoning in actual diagnostic trajectories obtained from physicians.}}, author = {{Battefeld, Dominik and Kopp, Stefan}}, booktitle = {{Proceedings of the 8th Workshop on Formal and Cognitive Reasoning}}, keywords = {{Diagnostic reasoning, Cognitive bias, Cognitive model, POMDP, Bayesian network, Epilepsy, CDSS}}, location = {{Trier}}, title = {{{Formalizing cognitive biases in medical diagnostic reasoning}}}, year = {{2022}}, } @article{48780, abstract = {{Explainable Artificial Intelligence (XAI) has mainly focused on static learning tasks so far. In this paper, we consider XAI in the context of online learning in dynamic environments, such as learning from real-time data streams, where models are learned incrementally and continuously adapted over the course of time. More specifically, we motivate the problem of explaining model change, i.e. explaining the difference between models before and after adaptation, instead of the models themselves. In this regard, we provide the first efficient model-agnostic approach to dynamically detecting, quantifying, and explaining significant model changes. Our approach is based on an adaptation of the well-known Permutation Feature Importance (PFI) measure. It includes two hyperparameters that control the sensitivity and directly influence explanation frequency, so that a human user can adjust the method to individual requirements and application needs. We assess and validate our method’s efficacy on illustrative synthetic data streams with three popular model classes.}}, author = {{Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke}}, issn = {{0933-1875}}, journal = {{KI - Künstliche Intelligenz}}, keywords = {{Artificial Intelligence}}, number = {{3-4}}, pages = {{211--224}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Agnostic Explanation of Model Change based on Feature Importance}}}, doi = {{10.1007/s13218-022-00766-6}}, volume = {{36}}, year = {{2022}}, } @inbook{33233, abstract = {{Das Programm Maschinenbau in China (mb-cn) ist eine spezielle Ausprägung der Paderborner Masterstudiengänge Maschinenbau, Wirtschafts- und Chemieingenieurwesen. Im Rahmen dieses Programms wird der technisch-interkulturelle Fachsprachkurs »Fachspezifisches Chinesisch« angeboten, der die praktische Anwendung des Sprachenlernens mit studiengangsbezogenen Angeboten kombiniert. Ziel des Kurses ist es, die Studierenden zu befähigen eine Hanyu-Shuiping-Kaoshi-Prüfung (HSK) auf Niveaustufe 2 zu bestehen sowie ihnen vertiefendes Fachvokabular aus den Fachbereichen Mathematik, Informatik, Wirtschaft, Technik und Maschinenbau zu vermitteln. Ausgewählte Beispiele in der fachsprachlichen Anwendung beziehensich auf die Beschreibung eines Gegenstandes wie den Getriebeaufbau und das Wirkprinzip eines Prüfstandes. Der Artikel soll als Evaluation und Rückschau auf das Pilotprojekt der Universität Paderborn dienen und Hilfestellung geben, wie die Konzeption und Umsetzung (auch unter Coronabedingungen) gelingen kann.}}, author = {{Hambach, Dennis}}, booktitle = {{Handbuch China-Kompetenzen}}, editor = {{Thelen, Gabriele and Obendiek, Helena and Bai, Yinchun}}, issn = {{2699-7681}}, pages = {{161--170}}, publisher = {{transcript Verlag}}, title = {{{»Fachspezifisches Chinesisch« an der Universität Paderborn}}}, doi = {{10.14361/9783839459751-015}}, year = {{2022}}, } @inbook{33232, abstract = {{Das seit den 1990er Jahren andauernde Engagement der Universität Paderborn in China hat zur Ausbildung von technisch-interkultureller China-Kompetenz in vielen Bereichengeführt. Die Universität Paderborn (UPB) unterhält derzeit sechs intensive Austauschpartnerschaften mit chinesischen Hochschulen. Im Rahmen der Masterstudiengänge Maschinenbau, Wirtschafts- und Chemieingenieurwesen sowie Wirtschaftsingenieurwesen wird die Studienausrichtung Maschinenbau in China (mb-cn) angeboten. Diese Studienausrichtung wird inenger Zusammenarbeit mit namhaften, global agierenden Partnerfirmen durchgeführt, die eigene Tochterfirmen in China oder eine starke Verbindung zu chinesischen Unternehmen haben. Zusätzlich können die Studierenden ein Fachpraktikum in einem deutschen Unternehmen in China absolvieren. Im Rahmen des Artikels wird das mb-cn-Projekt ausführlich vorgestellt. Die hierbeigeschilderten Erfahrungen mit dem Aufbau der Kooperation sowie die gezogenen Rückschlüsse auf die Ergebnisse des Projekts sollen dazu dienen, andere Einrichtungen beim Aufbau ähnlicher Kooperation zu unterstützen.}}, author = {{Denzer, Vera and Hambach, Dennis}}, booktitle = {{Handbuch China-Kompetenzen}}, editor = {{Thelen, Gabriele and Obendiek, Helena and Bai, Yinchun}}, issn = {{2699-7681}}, pages = {{117--128}}, publisher = {{transcript Verlag}}, title = {{{Maschinenbau in China}}}, doi = {{10.14361/9783839459751-010}}, year = {{2022}}, }