@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{AdenackerGerhardsOttenetal.2021, author = {Adenacker, J. and Gerhards, Benjamin and Otten, Christian and Schleser, Markus}, title = {Laserstrahlschweißen von Aluminium-Kupfer-Werkstoffkombinationen f{\"u}r die Elektromobilit{\"a}t}, series = {DVS CONGRESS 2021}, booktitle = {DVS CONGRESS 2021}, publisher = {DVS Media GmbH}, address = {D{\"u}sseldorf}, isbn = {978-3-96144-146-4}, pages = {31 -- 38}, year = {2021}, language = {de} } @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} } @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}, 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{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} }