TY - CHAP A1 - Kasch, Susanne A1 - Schmidt, Thomas A1 - Eichler, Fabian A1 - Thurn, Laura A1 - Jahn, Simon A1 - Bremen, Sebastian T1 - Solution approaches and process concepts for powder bed-based melting of glass T2 - Industrializing Additive Manufacturing. Proceedings of AMPA2020 N2 - 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. KW - Glass powder KW - Laser processing KW - Additive manufacturing KW - Melting KW - L-PBF Y1 - 2020 SN - 978-3-030-54333-4 (Print) SN - 978-3-030-54334-1 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-54334-1_7 N1 - International Conference on Additive Manufacturing in Products and Applications. 01.-03. September 2020. Zurich, Switzerland SP - 82 EP - 95 PB - Springer CY - Cham ER - TY - JOUR A1 - Engemann, Heiko A1 - Cönen, Patrick A1 - Dawar, Harshal A1 - Du, Shengzhi A1 - Kallweit, Stephan T1 - A robot-assisted large-scale inspection of wind turbine blades in manufacturing using an autonomous mobile manipulator JF - Applied Sciences N2 - Wind energy represents the dominant share of renewable energies. The rotor blades of a wind turbine are typically made from composite material, which withstands high forces during rotation. The huge dimensions of the rotor blades complicate the inspection processes in manufacturing. The automation of inspection processes has a great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. The focus of this paper is set on the process of rotor blade inspection automation by utilizing an autonomous mobile manipulator. The main innovations include a novel path planning strategy for zone-based navigation, which enables an intuitive right-hand or left-hand driving behavior in a shared human–robot workspace. In addition, we introduce a new method for surface orthogonal motion planning in connection with large-scale structures. An overall execution strategy controls the navigation and manipulation processes of the long-running inspection task. The implemented concepts are evaluated in simulation and applied in a real-use case including the tip of a rotor blade form. KW - mobile manipulation KW - large-scale inspection KW - wind turbine production KW - autonomous navigation KW - surface-orthogonal path planning Y1 - 2021 U6 - http://dx.doi.org/10.3390/app11199271 SN - 2076-3417 N1 - Belongs to the Special Issue "Advances in Industrial Robotics and Intelligent Systems" VL - 11 IS - 19 SP - 1 EP - 22 PB - MDPI CY - Basel ER - TY - CHAP A1 - Engemann, Heiko A1 - Badri, Sriram A1 - Wenning, Marius A1 - Kallweit, Stephan T1 - Implementation of an Autonomous Tool Trolley in a Production Line T2 - Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980 Y1 - 2019 SN - 978-3-030-19648-6 U6 - http://dx.doi.org/10.1007/978-3-030-19648-6_14 SP - 117 EP - 125 PB - Springer CY - Cham ER - TY - JOUR A1 - Schwarz, Alexander A1 - Gebhardt, Andreas A1 - Schleser, Markus A1 - Popoola, Patricia T1 - New Welding Joint Geometries Manufactured by Powder Bed Fusion from 316L JF - Materials Performance and Characterization 8 Y1 - 2019 U6 - http://dx.doi.org/10.1520/MPC20180096 SN - 2379-1365 IS - in press ER - TY - JOUR A1 - Cosma, Cosmin A1 - Kessler, Julia A1 - Gebhardt, Andreas A1 - Campbell, Ian A1 - Balc, Nicolae T1 - Improving the Mechanical Strength of Dental Applications and Lattice Structures SLM Processed JF - Materials N2 - 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. Y1 - 2020 U6 - http://dx.doi.org/10.3390/ma13040905 SN - 1996-1944 VL - 13 IS - 4 SP - 1 EP - 18 PB - MDPI CY - Basel ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Lai, Chow Yin A1 - Cheng, Chi-Tsun A1 - Wollert, Jörg T1 - Generic integration of VR and AR in product lifecycles based on CAD models T2 - Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019 Y1 - 2019 ER - TY - CHAP A1 - Gerhards, Benjamin A1 - Schleser, Markus A1 - Otten,, Christian A1 - Schwarz, Alexander A1 - Gebhardt, Andreas T1 - Innovative Laser Beam Joining Technology for Additive Manufactured Parts T2 - Conference Proceedings 72nd IIW Annual Assembly and International Conference, 7-12 July 2019, Bratislava Y1 - 2019 SP - 1 EP - 8 ER - TY - CHAP A1 - Gerhards, Benjamin A1 - Schleser, Markus A1 - Otten, Christian T1 - Advancements of mobile vacuum laser welding for industrial thick sheet applications T2 - Conference Proceedings 72nd IIW Annual Assembly and International Conference, 7-12 July 2019, Bratislava Y1 - 2019 SP - 1 EP - 8 ER - TY - CHAP A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Lai, Chow Yin A1 - Wollert, Jörg T1 - Microservice Architecture for Automation - Realization by the example of a model-factory’s manufacturing execution system T2 - Proceedings of the 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019 Y1 - 2019 SP - 33 EP - 37 ER - TY - CHAP A1 - Engemann, Heiko A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Ning, Chuanfang A1 - Anwar, Saqib T1 - AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation T2 - Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020 N2 - 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. Y1 - 2020 SN - 978-1-64368-137-5 U6 - http://dx.doi.org/10.3233/FAIA200770 N1 - Frontiers in Artificial Intelligence and Applications. Vol 332 SP - 89 EP - 97 PB - IOS Press CY - Amsterdam ER -