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 - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Gamified Virtual Reality Training Environment for the Manufacturing Industry Y1 - 2020 U6 - http://dx.doi.org/10.1109/ME49197.2020.9286661 SP - 1 EP - 6 ER - TY - CHAP A1 - Fateri, Miranda A1 - Gebhardt, Andreas T1 - Introduction to Additive Manufacturing T2 - 3D Printing of Optical Components N2 - Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed. KW - Additive manufacturing KW - 3D printing KW - Digital manufacturing KW - Rapid prototyping KW - Rapid manufacturing Y1 - 2020 SN - 978-3-030-58960-8 U6 - http://dx.doi.org/10.1007/978-3-030-58960-8_1 SP - 1 EP - 22 PB - Springer CY - Cham ER - TY - CHAP A1 - Chavez Bermudez, Victor Francisco A1 - Wollert, Jörg T1 - Arduino based Framework for Rapid Application Development of a Generic IO-Link interface T2 - Kommunikation und Bildverarbeitung in der Automation N2 - The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used. The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation. Y1 - 2020 SN - 978-3-662-59895-5 SN - 978-3-662-59894-8 U6 - http://dx.doi.org/10.1007/978-3-662-59895-5_2 N1 - Teil der Buchserie "Technologien für die intelligente Automation" (TIA,volume 12) SP - 21 EP - 33 PB - Springer Vieweg CY - Berlin ER - TY - CHAP A1 - Gebhardt, Andreas A1 - Hoetter, Jan-Steffen T1 - Rapid Tooling T2 - CIRP Encyclopedia of Production Engineering Y1 - 2019 SN - 978-3-662-53120-4 U6 - http://dx.doi.org/10.1007/978-3-662-53120-4 SP - 39 EP - 52 PB - Springer CY - Berlin, Heidelberg ER - TY - JOUR A1 - Ulmer, Jessica A1 - Gröninger, Marc A1 - Braun, Sebastian A1 - Wollert, Jörg T1 - AR Arbeitsplätze: Für hochflexible und skalierbare Produktionsumgebungen JF - atp Magazin N2 - Trotz fortschreitender Automatisierung bleiben manuelle Tätigkeiten ein wichtiger Baustein der Fertigung kundenindividueller Produkte. Um die Mitarbeiter(innen) zu unterstützen und um eine effiziente Arbeit zu ermöglichen, werden zunehmend auf Augmented Reality (AR) basierende Systeme eingesetzt. Die vorgestellte Arbeit konzentriert sich auf die Entwicklung ganzheitlicher AR-Arbeitsplätze für den Einsatz in kleinen und mittleren Unternehmen (KMU). Das entwickelte AR- Handarbeitskonzept beinhaltet eine Just-in-time-Darstellung der Arbeitsaufgaben auf Werkstücken mit automatisierter Fertigungskontrolle. Als Reaktion auf kurze Produktlebenszyklen und hohe Produktvielfalten sind alle Komponenten auf maximale Flexibilität ausgelegt. Ein Umrüsten auf neue Produkte kann innerhalb von Minuten erfolgen. Y1 - 2020 U6 - http://dx.doi.org/10.17560/atp.v62i10.2495 SN - 2364-3137 VL - 62 IS - 10 PB - Vulkan-Verlag CY - Essen ER - TY - CHAP A1 - Chavez Bermudez, Victor Francisco A1 - Wollert, Jörg T1 - Gateway for Automation Controllers and Cloud based Voice Recognition Services T2 - KommA, 10. Jahreskolloquium Kommunikation in der Automation Y1 - 2019 SN - 978-3-944722-85-6 SP - 1 EP - 8 PB - Institut für Automation und Kommunikation CY - Magdeburg ER - TY - JOUR A1 - Wollbrink, Moritz A1 - Maslo, Semir A1 - Zimmer, Daniel A1 - Abbas, Karim A1 - Arntz, Kristian A1 - Bergs, Thomas T1 - Clamping and substrate plate system for continuous additive build-up and post-processing of metal parts JF - Procedia CIRP N2 - The manufacturing share of laser powder bed fusion (L-PBF) increases in industrial application, but still many process steps are manually operated. Additionally, it is not possible to achieve tight dimensional tolerances or low surfaces roughness. Hence, a process chain has to be set up to combine additive manufacturing (AM) with further machining technologies. To achieve a continuous workpiece flow as basis for further industrialization of L-PBF, the paper presents a novel substrate system and its application on L-PBF machines and post-processing. The substrate system consists of a zero-point clamping system and a matrix-like interface of contact pins to be substantially connected to the workpiece within the L-PBF process. Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.procir.2020.04.015 SN - 2212-8271 VL - 93 SP - 108 EP - 113 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Human-Centered Gamification Framework for Manufacturing Systems JF - Procedia CIRP N2 - While bringing new opportunities, the Industry 4.0 movement also imposes new challenges to the manufacturing industry and all its stakeholders. In this competitive environment, a skilled and engaged workforce is a key to success. Gamification can generate valuable feedbacks for improving employees’ engagement and performance. Currently, Gamification in workspaces focuses on computer-based assignments and training, while tasks that require manual labor are rarely considered. This research provides an overview of Enterprise Gamification approaches and evaluates the challenges. Based on that, a skill-based Gamification framework for manual tasks is proposed, and a case study in the Industry 4.0 model factory is shown. Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.procir.2020.04.076 SN - 2212-8271 VL - 93 SP - 670 EP - 675 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kunkel, Maximilian Hugo A1 - Gebhardt, Andreas A1 - Mpofu, Khumbulani A1 - Kallweit, Stephan T1 - Quality assurance in metal powder bed fusion via deep-learning-based image classification JF - Rapid Prototyping Journal Y1 - 2019 U6 - http://dx.doi.org/10.1108/RPJ-03-2019-0066 SN - 1355-2546 VL - 26 IS - 2 SP - 259 EP - 266 ER -