@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} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg F.}, title = {Gamified Virtual Reality Training Environment for the Manufacturing Industry}, series = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)}, booktitle = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ME49197.2020.9286661}, pages = {1 -- 6}, year = {2020}, abstract = {Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users' pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs.}, language = {de} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg F.}, title = {Simulation und Verifikation komplexer Handarbeitsprozesse durch die Kombination von Virtual Reality und Augmented Reality im Single-Piece-Workflow}, series = {Tagungsband: AALE 2020}, booktitle = {Tagungsband: AALE 2020}, isbn = {978-3-8007-5180-8}, pages = {4 Seiten}, year = {2020}, language = {de} } @inproceedings{SchmidtKaschEichleretal.2021, author = {Schmidt, Thomas and Kasch, Susanne and Eichler, Fabian and Thurn, Laura}, title = {Process strategies on laser-based melting of glass powder}, series = {LiM 2021 proceedings}, booktitle = {LiM 2021 proceedings}, pages = {10 Seiten}, year = {2021}, abstract = {This paper presents the laser-based powder bed fusion (L-PBF) using various glass powders (borosilicate and quartz glass). Compared to metals, these require adapted process strategies. First, the glass powders were characterized with regard to their material properties and their processability in the powder bed. This was followed by investigations of the melting behavior of the glass powders with different laser wavelengths (10.6 µm, 1070 nm). In particular, the experimental setup of a CO2 laser was adapted for the processing of glass powder. An experimental setup with integrated coaxial temperature measurement/control and an inductively heatable build platform was created. This allowed the L-PBF process to be carried out at the transformation temperature of the glasses. Furthermore, the component's material quality was analyzed on three-dimensional test specimen with regard to porosity, roughness, density and geometrical accuracy in order to evaluate the developed L-PBF parameters and to open up possible applications.}, language = {en} } @inproceedings{EvansChavezBermudezWollert2023, author = {Evans, Benjamin and Ch{\´a}vez Berm{\´u}dez, Victor Francisco and Wollert, J{\"o}rg F.}, title = {Automatic generation and orchestration of active asset administration shells with IO-Link}, series = {Kommunikation in der Automation : 14. Jahreskolloquium, 21./22.11.2023, Magdeburg}, booktitle = {Kommunikation in der Automation : 14. Jahreskolloquium, 21./22.11.2023, Magdeburg}, publisher = {Otto von Guericke University Library}, address = {Magdeburg}, doi = {10.25673/111743}, pages = {12 Seiten}, year = {2023}, abstract = {This paper presents a proof of concept for automatically generating and orchestrating active asset administration shells (AAS) with IO-Link. AAS are software-based representations of physical assets that enable interoperability and standardised communication across different industrial systems. IO-Link is a widely adopted communication protocol for sensors and actuators in industrial automation. Our method uses an approach to generate AASs based on the IO-Link device description files. The generated AASs can then be orchestrated to form a distributed system that provides dynamic information about the status and performance of the connected assets. We demonstrate the effectiveness of our method through a proof of concept that involves the automatic generation and orchestration of AASs for a fluid processing unit equipped with pressure and flow sensors and a pump. The results show that our approach reduces the time and effort required to create and maintain active AASs.}, language = {en} } @inproceedings{ChavezBermudezWollert2024, author = {Ch{\´a}vez Berm{\´u}dez, Victor Francisco and Wollert, J{\"o}rg F.}, title = {An industry 4.0 ontology-based architecture for interoperability at the field level}, series = {Automation, Robotics \& Communications for Industry 4.0/5.0}, booktitle = {Automation, Robotics \& Communications for Industry 4.0/5.0}, publisher = {IFSA}, address = {Barcelona}, isbn = {978-84-09-58219-8}, issn = {2938-4796}, doi = {10.13140/RG.2.2.20923.18722}, pages = {319 -- 321}, year = {2024}, abstract = {Industrial field devices exchange information through standardized communication interfaces and data models, encompassing process data, communication properties, and vendor details. Despite enhancing interoperability within a specific protocol, integrating these devices with diverse systems poses challenges due to data model fragmentation and custom interfaces. The absence of a universal semantic model for categorizing field device process data independently of standards necessitates engineers to repetitively devise custom exchange data models for different sensors and actuators, relying on standards like OPC-UA. In response, this work proposes an ontology-based architecture to tackle information data model fragmentation, aiming for seamless data interoperability across a universal interface. By focusing on two open-access field device standards, IO-Link and CANOpen, we compare their information data models, identify existing limitations, and put forth a semantic information model. The objective is to offer an interoperable interface for Industry 4.0 applications, showcasing the potential of an ontology-based approach in streamlining data exchange and reducing heterogeneity among field devices.}, language = {en} }