TY - JOUR A1 - Kunkel, Maximilian Hugo A1 - Gebhardt, Andreas A1 - Mpofu, Khumbaulani A1 - Kallweit, Stephan T1 - Statistical assessment of mechanical properties of selective laser melted specimens of stainless steel JF - The International Journal of Advanced Manufacturing Technology N2 - The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements. Y1 - 2018 U6 - http://dx.doi.org/10.1007/s00170-018-2040-8 SN - 0268-3768 VL - 98 IS - 5-8 SP - 1409 EP - 1431 PB - Springer CY - London ER - TY - JOUR A1 - Franzen, Julius A1 - Pinders, Erik A1 - Pfaff, Raphael A1 - Enning, Manfred T1 - RailCrowd’s virtual fleets: Make most of your asset data JF - Deine Bahn N2 - For smaller railway operators or those with a diverse fleet, it can be difficult to collect sufficient data to improve maintenance programs. At the same time, new rules such as entity in charge of maintenance – ECM – regulations impose an additional workload by requiring a dedicated maintenance management system and specific reports. The RailCrowd platform sets out to facilitate compliance with ECM and similar regulations while at the same time pooling anonymised fleet data across operators to form virtual fleets, providing greater data insights. Y1 - 2018 SN - 0948-7263 IS - 9 SP - 11 EP - 13 PB - Bahn-Fachverlag CY - Berlin ER - TY - JOUR A1 - Bucur, Alexandru A1 - Lazarescu, Lucian A1 - Pop, Grigore Marian A1 - Achimas, Gheorghe A1 - Gebhardt, Andreas T1 - Tribological performance of biodegradable lubricants under different surface roughness of tools JF - Academic Journal of Manufacturing Engineering Y1 - 2019 SN - 1583-7904 VL - 17 IS - 1 SP - 172 EP - 178 ER - TY - JOUR A1 - Panc, Nicolae A1 - Contiu, Glad A1 - Bocanet, Vlad A1 - Thurn, Laura A1 - Sabau, Emilia T1 - The influence of cutting technology on surface wear hardness JF - Academic Journal of Manufacturing Engineering Y1 - 2019 SN - 1583-7904 VL - 17 IS - 3 SP - 205 EP - 210 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 - 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 - Franko, Josef A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Duelberg, Enno Sebastian A1 - Engemann, Heiko T1 - Design of a Multi-Robot System for Wind Turbine Maintenance JF - Energies N2 - The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future. Y1 - 2020 U6 - http://dx.doi.org/10.3390/en13102552 SN - 1996-1073 VL - 13 IS - 10 SP - Article 2552 PB - MDPI CY - Basel ER - TY - JOUR A1 - Raffeis, Iris A1 - Adjei-Kyeremeh, Frank A1 - Vroomen, Uwe A1 - Westhoff, Elmar A1 - Bremen, Sebastian A1 - Hohoi, Alexandru A1 - Bührig-Polaczek, Andreas T1 - Qualification of a Ni-Cu alloy for the laser powder bed fusion process (LPBF): Its microstructure and mechanical properties JF - Applied Sciences N2 - As researchers continue to seek the expansion of the material base for additive manufacturing, there is a need to focus attention on the Ni–Cu group of alloys which conventionally has wide industrial applications. In this work, the G-NiCu30Nb casting alloy, a variant of the Monel family of alloys with Nb and high Si content is, for the first time, processed via the laser powder bed fusion process (LPBF). Being novel to the LPBF processes, optimum LPBF parameters were determined, and hardness and tensile tests were performed in as-built conditions and after heat treatment at 1000 °C. Microstructures of the as-cast and the as-built condition were compared. Highly dense samples (99.8% density) were achieved after varying hatch distance (80 µm and 140 µm) with scanning speed (550 mm/s–1500 mm/s). There was no significant difference in microhardness between varied hatch distance print sets. Microhardness of the as-built condition (247 HV0.2) exceeded the as-cast microhardness (179 HV0.2.). Tensile specimens built in vertical (V) and horizontal (H) orientations revealed degrees of anisotropy and were superior to conventionally reported figures. Post heat treatment increased ductility from 20% to 31% (V), as well as from 16% to 25% (H), while ultimate tensile strength (UTS) and yield strength (YS) were considerably reduced. Y1 - 2020 U6 - http://dx.doi.org/10.3390/app10103401 SN - 2076-3417 N1 - Special Issue Materials Development by Additive Manufacturing Techniques VL - 10 IS - Art. 3401 SP - 1 EP - 15 PB - MDPI CY - Basel 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 - TY - JOUR A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Performance evaluation of skill-based order-assignment in production environments with multi-agent systems JF - IEEE Journal of Emerging and Selected Topics in Industrial Electronics N2 - The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models. KW - cyber-physical production systems KW - event-based simulation KW - multi-agent systems KW - digital factory KW - industrial agents Y1 - 2021 U6 - http://dx.doi.org/10.1109/JESTIE.2021.3108524 SN - 2687-9735 IS - Early Access PB - IEEE CY - New York ER -