@inproceedings{KaschSchmidtEichleretal.2020, author = {Kasch, Susanne and Schmidt, Thomas and Eichler, Fabian and Thurn, Laura and Jahn, Simon and Bremen, Sebastian}, title = {Solution approaches and process concepts for powder bed-based melting of glass}, series = {Industrializing Additive Manufacturing. Proceedings of AMPA2020}, booktitle = {Industrializing Additive Manufacturing. Proceedings of AMPA2020}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-54333-4 (Print)}, doi = {10.1007/978-3-030-54334-1_7}, pages = {82 -- 95}, year = {2020}, abstract = {In the study, the process chain of additive manufacturing by means of powder bed fusion will be presented based on the material glass. In order to reliably process components additively, new concepts with different solutions were developed and investigated. Compared to established metallic materials, the properties of glass materials differ significantly. Therefore, the process control was adapted to the material glass in the investigations. With extensive parameter studies based on various glass powders such as borosilicate glass and quartz glass, scientifically proven results on powder bed fusion of glass are presented. Based on the determination of the particle properties with different methods, extensive investigations are made regarding the melting behavior of glass by means of laser beams. Furthermore, the experimental setup was steadily expanded. In addition to the integration of coaxial temperature measurement and regulation, preheating of the building platform is of major importance. This offers the possibility to perform 3D printing at the transformation temperatures of the glass materials. To improve the component's properties, the influence of a subsequent heat treatment was also investigated. The experience gained was incorporated into a new experimental system, which allows a much better exploration of the 3D printing of glass. Currently, studies are being conducted to improve surface texture, building accuracy, and geometrical capabilities using three-dimensional specimen. The contribution shows the development of research in the field of 3D printing of glass, gives an insight into the machine and process engineering as well as an outlook on the possibilities and applications.}, language = {en} } @article{CosmaKesslerGebhardtetal.2020, author = {Cosma, Cosmin and Kessler, Julia and Gebhardt, Andreas and Campbell, Ian and Balc, Nicolae}, title = {Improving the Mechanical Strength of Dental Applications and Lattice Structures SLM Processed}, series = {Materials}, volume = {13}, journal = {Materials}, number = {4}, publisher = {MDPI}, address = {Basel}, issn = {1996-1944}, doi = {10.3390/ma13040905}, pages = {1 -- 18}, year = {2020}, abstract = {To manufacture custom medical parts or scaffolds with reduced defects and high mechanical characteristics, new research on optimizing the selective laser melting (SLM) parameters are needed. In this work, a biocompatible powder, 316L stainless steel, is characterized to understand the particle size, distribution, shape and flowability. Examination revealed that the 316L particles are smooth, nearly spherical, their mean diameter is 39.09 μm and just 10\% of them hold a diameter less than 21.18 μm. SLM parameters under consideration include laser power up to 200 W, 250-1500 mm/s scanning speed, 80 μm hatch spacing, 35 μm layer thickness and a preheated platform. The effect of these on processability is evaluated. More than 100 samples are SLM-manufactured with different process parameters. The tensile results show that is possible to raise the ultimate tensile strength up to 840 MPa, adapting the SLM parameters for a stable processability, avoiding the technological defects caused by residual stress. Correlating with other recent studies on SLM technology, the tensile strength is 20\% improved. To validate the SLM parameters and conditions established, complex bioengineering applications such as dental bridges and macro-porous grafts are SLM-processed, demonstrating the potential to manufacture medical products with increased mechanical resistance made of 316L.}, language = {en} } @article{WilbringEnningPfaffetal.2020, author = {Wilbring, Daniela and Enning, Manfred and Pfaff, Raphael and Schmidt, Bernd}, title = {Neue Perspektiven f{\"u}r die Bahn in der Produktions- und Distributionslogistik durch Prozessautomation}, series = {ETR - Eisenbahntechnische Rundschau}, volume = {69}, journal = {ETR - Eisenbahntechnische Rundschau}, number = {3}, issn = {0013-2845}, pages = {15 -- 19}, year = {2020}, language = {de} } @incollection{EngemannDuKallweitetal.2020, author = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and Ning, Chuanfang and Anwar, Saqib}, title = {AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation}, series = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020}, booktitle = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020}, publisher = {IOS Press}, address = {Amsterdam}, isbn = {978-1-64368-137-5}, doi = {10.3233/FAIA200770}, pages = {89 -- 97}, year = {2020}, abstract = {We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.}, language = {en} } @article{EngemannDuKallweitetal.2020, author = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and C{\"o}nen, Patrick and Dawar, Harshal}, title = {OMNIVIL - an autonomous mobile manipulator for flexible production}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {24, art. no. 7249}, publisher = {MDPI}, address = {Basel}, isbn = {1424-8220}, doi = {10.3390/s20247249}, pages = {1 -- 30}, year = {2020}, language = {en} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Gamified Virtual Reality Training Environment for the Manufacturing Industry}, doi = {10.1109/ME49197.2020.9286661}, pages = {1 -- 6}, year = {2020}, language = {de} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Simulation und Verifikation komplexer Handarbeitsprozesse durch die Kombination von Virtual Reality und Augmented Reality im Single-Piece-Workflow}, series = {AALE 2020, 17. Fachkonferenz Angewandte Automatisierungstechnik in Lehre und Entwicklung, Automatisierung und Mensch-Technik-Interaktion, Leipzig, DE, 4.-6.3.2020}, booktitle = {AALE 2020, 17. Fachkonferenz Angewandte Automatisierungstechnik in Lehre und Entwicklung, Automatisierung und Mensch-Technik-Interaktion, Leipzig, DE, 4.-6.3.2020}, isbn = {978-3-8007-5180-8}, pages = {1 -- 4}, year = {2020}, language = {de} }