@inproceedings{33803, author = {{Hanses, Hendrik and Horwath, Ilona}}, booktitle = {{Conference proceedings 38th Danubia Adria Symposium on Advances in Experimental Mechanics}}, editor = {{Kourkoulis, Stavros K.}}, isbn = {{978-618-86278-0-2}}, location = {{Poros}}, title = {{{OPERATIONAL AND DEMAND-ORIENTED FIREFIGHTING EQUIPMENT }}}, year = {{2022}}, } @inproceedings{32871, author = {{Triebus, Marcel and Ostermann, Moritz and Tröster, Thomas and Horwath, Ilona}}, booktitle = {{Materials in Car Body Engineering - Bad Nauheim}}, location = {{Bad Nauheim}}, title = {{{Advanced Automotive Components by Fiber-Metal-Laminates}}}, year = {{2022}}, } @inproceedings{44376, author = {{Tonbul, Güldeniz and Kappler, Julian and Murugan, Saravanakumar and Schoch, Roland and Nowakowski, Michal and Lange, Pia and Bauer, Matthias and Buchmeiser, Michael R.}}, location = {{Edinburgh}}, title = {{{Development of Battery System Based on Na-S and Characterization Using X-ray Absorption Spectroscopy}}}, year = {{2022}}, } @article{30213, abstract = {{Requirement changes and cascading effects of change propagation are major sources of inefficiencies in product development and increase the risk of project failure. Proactive change management of requirement changes yields the potential to handle such changes efficiently. A systematic approach is required for proactive change management to assess and reduce the risk of a requirement change with appropriate effort in industrial application. Within the paper at hand, a novel method for Proactive Management of Requirement Changes (ProMaRC) is presented. It is developed in close collaboration with industry experts and evaluated based on workshops, pilot users’ feedback, three industrial case studies from the automotive industry and five development projects from research. To limit the application effort, an automated approach for dependency analysis based on the machine learning technique BERT and semi-automated assessment of change likelihood and impact using a modified PageRank algorithm is developed. Applying the method, the risks of requirement changes are assessed systematically and reduced by means of proactive change measures. Evaluation shows high performance of dependency analysis and confirms the applicability and usefulness of the method. This contribution opens up the research space of proactive risk management for requirement changes which is currently almost unexploited. It enables more efficient product development.}}, author = {{Gräßler, Iris and Oleff, Christian and Preuß, Daniel}}, issn = {{2076-3417}}, journal = {{Applied Sciences}}, keywords = {{Fluid Flow and Transfer Processes, Computer Science Applications, Process Chemistry and Technology, General Engineering, Instrumentation, General Materials Science}}, number = {{4}}, publisher = {{MDPI AG}}, title = {{{Proactive Management of Requirement Changes in the Development of Complex Technical Systems}}}, doi = {{10.3390/app12041874}}, volume = {{12}}, year = {{2022}}, } @inbook{44462, author = {{Eckel, Julia}}, booktitle = {{Mimesis Expanded. Die Ausweitung der mimetischen Zone}}, editor = {{Balke, Friedrich and Linseisen, Elisa}}, pages = {{267--294}}, publisher = {{Fink}}, title = {{{Animation und Mimesis. Zur digitalen Expansion bewegtbildlicher Mimesis und ‚animimetischem‘ Denken}}}, 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}}, } @article{44468, author = {{Schmidt, Stephan and Gräßer, Melanie and Schmid, Hans-Joachim}}, issn = {{1064-8275}}, journal = {{SIAM Journal on Scientific Computing}}, keywords = {{Applied Mathematics, Computational Mathematics}}, number = {{4}}, pages = {{B1175--B1194}}, publisher = {{Society for Industrial & Applied Mathematics (SIAM)}}, title = {{{A Shape Newton Scheme for Deforming Shells with Application to Capillary Bridges}}}, doi = {{10.1137/20m1389054}}, volume = {{44}}, year = {{2022}}, } @article{44469, author = {{Menge, Dennis and Schmid, Hans-Joachim}}, issn = {{1022-1360}}, journal = {{Macromolecular Symposia}}, keywords = {{Materials Chemistry, Polymers and Plastics, Organic Chemistry, Condensed Matter Physics}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Low Temperature Laser Sintering with PA12 and PA6 on a Standard System}}}, doi = {{10.1002/masy.202100397}}, volume = {{404}}, year = {{2022}}, } @phdthesis{30255, author = {{Wiens, Eugen}}, isbn = {{978-3-8440-8408-5}}, publisher = {{Shaker}}, title = {{{Innendrückwalzen – Ein innovatives Umformverfahren zur inkrementellen Formgebung von wanddickenkonturierten Rohren mit lokal einstellbaren mechanischen Eigenschaften}}}, year = {{2022}}, } @inproceedings{44514, author = {{Scheveleva, Tatyana and Wawer, Max Leo and Oladazimi, Pooya and Koepler, Oliver and Nürnberger, Florian and Lachmayer, Roland and Auer, Sören and Mozgova, Iryna}}, title = {{{Creation of a Knowledge Space by Semantically Linking Data Repository and Knowledge Management System - a Use Case from Production Engineering}}}, doi = {{10.1016/j.ifacol.2022.10.006}}, year = {{2022}}, } @inproceedings{44510, author = {{Mozgova, Iryna and Altun, Osman and Scheveleva, Tatyana and Castro, Andre and Oladazimi, Pooya and Koepler, Oliver and Lachmayer, Roland and Auer, Sören}}, title = {{{Knowledge Annotation within Research Data Management System for Oxygen-Free Production Technologies}}}, doi = {{10.1017/pds.2022.54}}, year = {{2022}}, } @inproceedings{44513, author = {{Schneider, Jannik and Scheidel, Wieben and Wurst, Johanna and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Comparative Evaluation of Product and Service Solutions in the Context of Product-Service Systems and Technical Inheritance}}}, doi = {{https://doi.org/10.1007/978-3-030-94335-6_23}}, year = {{2022}}, } @inproceedings{44515, author = {{Herrmann, Kevin and Bode, Behrend and Wurst, Johanna and Gembarski, Paul and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Quantification of the material-related environmental impact of topology-optimized multi-material components}}}, doi = {{10.35199/dfx2022.01}}, year = {{2022}}, } @inproceedings{44517, author = {{Wurst, Johanna and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Sustainability Assessment of Products manufactured by the Laser Powder Bed Fusion (LPBF) Process}}}, doi = {{10.1016/j.procir.2022.02.040}}, year = {{2022}}, } @inproceedings{44516, author = {{Schneider, Jannik and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Life cycle cost impact of maintenance networks for product-service system fleets}}}, doi = {{10.1016/j.procir.2022.02.087}}, year = {{2022}}, } @inproceedings{44511, author = {{Altun, Osman and Kutay, Y and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Procedure to Create an Automated Design Environment for Functional Assemblies}}}, doi = {{10.1017/pds.2022.57}}, year = {{2022}}, } @inproceedings{44508, author = {{Sheveleva, Tatyana and Herrmann, Kevin and Wawer, Max Leo and Kahra, Christoph and Nürnberger, Florian and Koepler, Oliver and Mozgova, Iryna and Lachmayer, Roland and Auer, Sören}}, title = {{{Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection}}}, doi = {{10.1007/978-3-031-16281-7_39}}, year = {{2022}}, } @inbook{44519, author = {{Lachmayer, Roland and Mozgova, Iryna}}, booktitle = {{Design Methodology for Future Products}}, title = {{{Technical Inheritance as an Approach to Data-Driven Product Development}}}, doi = {{10.1007/978-3-030-78368-6_3}}, year = {{2022}}, } @inproceedings{44520, author = {{Wurst, Johanna and Schneider, Jannik and Ehlers, Tobias and Mozgova, Iryna and Lachmayer, Roland}}, title = {{{Corporate Strategy Based Quantitative Assessment of Sustainability Indicators at the Example of a Laser Powder Bed Fusion Process}}}, doi = {{10.1007/978-981-16-6128-0_4}}, year = {{2022}}, }