@inproceedings{KesslerBalcGebhardtetal.2017, author = {Kessler, Julia and Balc, Nicolae and Gebhardt, Andreas and Abbas, Karim}, title = {Basic research on lattice structures focused on the reliance of the cross sectional area and additional coatings}, series = {The 4th International Conference on Computing and Solutions in Manufacturing Engineering 2016 - CoSME'16}, booktitle = {The 4th International Conference on Computing and Solutions in Manufacturing Engineering 2016 - CoSME'16}, edition = {Vol. 94}, doi = {10.1051/matecconf/20179403008}, pages = {7 S.}, year = {2017}, language = {en} } @inproceedings{SchleupenEngemannBagherietal.2017, author = {Schleupen, Josef and Engemann, Heiko and Bagheri, Mohsen and Kallweit, Stephan and Dahmann, Peter}, title = {Developing a climbing maintenance robot for tower and rotor blade service of wind turbines}, series = {Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16)}, booktitle = {Advances in Robot Design and Intelligent Control : Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16)}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-49058-8}, doi = {10.1007/978-3-319-49058-8_34}, pages = {310 -- 319}, year = {2017}, language = {en} } @inproceedings{FerreinSchifferKallweit2018, author = {Ferrein, Alexander and Schiffer, Stefan and Kallweit, Stephan}, title = {The ROSIN Education Concept - Fostering ROS Industrial-Related Robotics Education in Europe}, series = {ROBOT 2017: Third Iberian Robotics Conference}, booktitle = {ROBOT 2017: Third Iberian Robotics Conference}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-70836-2}, doi = {10.1007/978-3-319-70836-2_31}, pages = {370 -- 381}, year = {2018}, language = {en} } @book{GebhardtKesslerThurn2019, author = {Gebhardt, Andreas and Kessler, Julia and Thurn, Laura}, title = {3D printing : understanding additive manufacturing}, edition = {2. Auflage}, publisher = {Hanser}, address = {M{\"u}nchen}, isbn = {978-1-56990-702-3}, pages = {XVI, 204 Seiten}, year = {2019}, language = {en} } @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{KoenigWolf2016, author = {K{\"o}nig, Johannes Alexander and Wolf, Martin}, title = {A new definition of competence developing games - and a framework to assess them}, series = {ACHI 2016 : The Ninth International Conference on Advances in Computer-Human Interactions}, booktitle = {ACHI 2016 : The Ninth International Conference on Advances in Computer-Human Interactions}, isbn = {978-1-61208-468-8}, pages = {95 -- 97}, year = {2016}, abstract = {There are different types of games that try to make use of the motivation of a gaming situation in learning contexts. This paper introduces the new terminology 'Competence Developing Game' (CDG) as an umbrella term for all games with this intention. Based on this new terminology, an assessment framework has been developed and validated in scope of an empirical study. Now, all different types of CDGs can be evaluated according to a defined and uniform set of assessment criteria and, thus, are comparable according to their characteristics and effectiveness.}, language = {en} } @inproceedings{ChavezBermudezWollert2022, author = {Chavez Bermudez, Victor Francisco and Wollert, J{\"o}rg}, title = {10BASE-T1L industry 4.0 smart switch for field devices based on IO-Link}, series = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)}, booktitle = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)}, publisher = {IEEE}, address = {New York, NY}, isbn = {978-1-6654-1086-1}, doi = {10.1109/WFCS53837.2022.9779176}, pages = {4 Seiten}, year = {2022}, abstract = {The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.}, language = {en} } @inproceedings{UlmerBraunChengetal.2022, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Usage of digital twins for gamification applications in manufacturing}, series = {Procedia CIRP Leading manufacturing systems transformation - Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022}, volume = {107}, booktitle = {Procedia CIRP Leading manufacturing systems transformation - Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2022.05.044}, pages = {675 -- 680}, year = {2022}, abstract = {Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers' actions. Game elements are selected according to the work task and users' preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.}, language = {en} } @inproceedings{DannenSchindelePruemmeretal.2022, author = {Dannen, Tammo and Schindele, Benedikt and Pr{\"u}mmer, Marcel and Arntz, Kristian and Bergs, Thomas}, title = {Methodology for the self-optimizing determination of additive manufacturing process eligibility and optimization potentials in toolmaking}, series = {Procedia CIRP Leading manufacturing systems transformation - Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022}, volume = {107}, booktitle = {Procedia CIRP Leading manufacturing systems transformation - Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2022.05.188}, pages = {1539 -- 1544}, year = {2022}, abstract = {Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures. The first stage of the approach specifies the model's initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.}, language = {en} }