TY - JOUR A1 - Kiefl, Sophia A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Self-employed and stressed out? The impact of stress and stress management on entrepreneurs’ mental health and performance JF - Frontiers in Psychology Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56040 VL - 15 PB - Frontiers ER - TY - JOUR A1 - Höfflin, Dennis A1 - Sauer, Christian A1 - Schiffler, Andreas A1 - Hartmann, Jürgen T1 - Process Monitoring Using Synchronized Path Infrared Thermography in PBF-LB/M JF - Sensors N2 - Additive manufacturing processes, particularly Laser-Based Powder Bed Fusion of Metals (PBF-LB/M), enable the development of new application possibilities due to their manufacturing-specific freedom of design. These new fields of application require a high degree of component quality, especially in safety-relevant areas. This is currently ensured primarily via a considerable amount of downstream quality control. Suitable process monitoring systems promise to reduce this effort drastically. This paper introduces a novel monitoring method in order to gain process-specific thermal information during the manufacturing process. The Synchronized Path Infrared Thermography (SPIT) method is based on two synchronized galvanometer scanners allowing high-speed and high-resolution observations of the melt pool in the SWIR range. One scanner is used to steer the laser over the building platform, while the second scanner guides the field of view of an IR camera. With this setup, the melting process is observed at different laser powers, scan speeds and at different locations with respect to the laser position, in order to demonstrate the positioning accuracy of the system and to initially gain thermal process data of the melt pool and the heat-affected zone. Therefore, the SPIT system shows a speed independent overall accuracy of ±2 Pixel within the evaluated range. The system further allows detailed thermal observation of the melt pool and the surrounding heat-affected zone. KW - SPIT KW - PBF-LB/M KW - additive manufacturing KW - process monitoring KW - SWIR KW - melt pool KW - galvanometer scanner Y1 - 2022 U6 - https://doi.org/10.3390/s22165943 VL - 22 IS - 16 PB - MDPI ER - TY - CHAP A1 - Hartmann, Jürgen A1 - Ochs, Dennis A1 - Lenski, Philipp A1 - Schiffler, Andreas A1 - Versch, Alexander A1 - Manara, Jochen T1 - Thermal process monitoring for additive manufacturing BT - MSE 2020 Y1 - 2020 CY - Darmstadt ER - TY - JOUR A1 - Ochs, Dennis A1 - Wehnert, Kira-Kristin A1 - Hartmann, Jürgen A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Sustainable Aspects of a Metal Printing Process Chain with Laser Powder Bed Fusion (LPBF) JF - Procedia CIRP N2 - Production companies are getting more and more aware of the relevancy of energy costs and the environmental impact of their manufactured products. Hence, the knowledge about the energy intensity of new process technologies as metal printing becomes increasingly crucial. Therefore, data about the energy intensity of entire process chains allow a detailed assessment of the life cycle costs and environmental impact of metal printed parts. As metal printing with Laser Powder Bed Fusion (LPBF) is applied from rapid prototyping to serial manufacturing processes more and more, sustainability data are useful to support a valid scale-up scenario and energetic improvements of the 3D-printing machinery as well as peripheral aggregates used in the process chain. The contribution aims to increase the transparency of the LPBF process chain in terms of its energy consumption. Therefore a generalized model to assess sustainability aspects of metal printed parts is derived. For this purpose, the LPBF process chain with the essential pre-, main- and post-processes is evaluated regarding its energy intensity. Here, the sub-processes, for example wet and dry cleaning of the printer, sieving of the metal powder or sand-blasting of the part are analyzed as well as the main printing process. Based on the derived experimental data from an installed, industry-like process chain, a model is created, which tends to generalize the experimental findings to evaluate other metal printed parts and process chain variants in terms of their energy intensity. Y1 - 2021 UR - 10.1016/j.procir.2021.01.163 VL - 98 SP - 613 EP - 618 PB - Elsevir ER - TY - CHAP A1 - Hartmann, Jürgen A1 - Lenski, Philipp A1 - Ochs, Dennis A1 - Shandy, Amir A1 - Winterstein, A. A1 - Versch, Alexander A1 - Schiffler, Andreas T1 - Thermische Prozessüberwachung für additive Fertigungsverfahren BT - Temperatur 2020 Y1 - 2020 CY - Berlin ER - TY - CHAP A1 - Rosilius, Maximilian A1 - Wirsing, Benedikt A1 - von Eitzen, Ingo A1 - Wilhelm, Markus A1 - Schmitt, Jan A1 - Engelmann, Bastian A1 - Bräutigam, Volker T1 - Evaluation of Visual Requirements and Software-Design for Immersive Visibility in Industrial Applications T2 - 2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) N2 - Currently, many sources predict increasing use of AR technology in the industrial environment. The task of immersive productive assistance systems is to provide information contextually to the industrial user. Therefore, it is essential to explore the factors and effects that influence the visibility and the corresponding quality of this information. Caused by the technical limitations of additive display technology and application conditions, this new approach has evaluated the immersive visibility of Landolt Rings in various greyscales against ambient illuminance levels on different industrial-like surfaces, coupled with and without a white virtual background. For this purpose, an empirical study in a within-subjects-design with full factorial experimental design (n=23) was conducted on Microsoft HoloLens 2 hardware. The mean values of the main effects indicate that visibility is significantly affected by ambient illuminance (best results at lower level), greyscale (best results at middle level) and virtual background (best results with background). In contrast, the choice of surface is shown to have no statistically significant effect on visibility, however it affects the response time. Additionally, cross-interactions of variables were analyzed and lead to a design recommendation for immersive industrial applications. Y1 - 2021 UR - https://www.researchgate.net/profile/Rosilius_Maximilian/publication/355896115_Evaluation_of_Visual_Requirements_and_Software-Design_for_Immersive_Visibility_in_Industrial_Applications/links/6189827807be5f31b7591290/Evaluation-of-Visual-Requirements-and-Software-Design-for-Immersive-Visibility-in-Industrial-Applications.pdf SP - 234 EP - 239 ER - TY - JOUR A1 - Fischer, Sophie A1 - Rosilius, Maximilian A1 - Schmitt, Jan A1 - Bräutigam, Volker T1 - A brief review of our agile teaching formats in entrepreneurship education JF - Sustainability N2 - Companies are confronted with increasingly demanding environments, including globalization, technologization, intergenerationality, and crises such as the coronavirus pandemic. To accept uncertainties as a challenge and to recognize opportunities for development, well-educated and resilient founders are needed who can foster innovation and sustainable development within society and the economy. The majority of today’s entrepreneurs have an academic background. Hence, institutions for higher education need to provide comprehensive educational offerings and support initiatives to train and sensitize future entrepreneurs. Therefore, since 2013, agile teaching formats have been developed in our project at a Bavarian university of applied sciences. In two stages, we founded a limited company for hands-on experimentation with entrepreneurship and also conceptualized an elective course and an annual founders’ night. Based on a theoretical model and continuous teaching evaluations, we adjusted the individual modules to suit the target group. The objective is to promote the acquisition of key competencies and exert a positive influence on the startup quotient in the region. There are six startups by students who can be traced back to our project. This indicates that a target-group-oriented educational program encourages motivation and awareness of entrepreneurial thinking and action among students. Y1 - 2022 U6 - https://doi.org/https://doi.org/10.3390/su14010251 VL - 14 IS - 1 SP - 251 EP - 251 ER - TY - CHAP A1 - Meyer, Maximilian A1 - Pechtl, Lin A1 - Bremer, Peik A1 - Schmitt, Jan T1 - Towards position-based technologies for digitized process management on the shop floor T2 - Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, Würzburg N2 - Position-based technologies, e.g Ultrawideband (UWB), WiFi or Bluetooth, for indoor localisation purposes are already commercially available. With the highly increasing digitalization of industrial processes, the potential of these technologies comes into focus of process management research. This paper aims to structure position-based technologies according to their potential to support shop-floor process management. For this purpose, a framework with the following dimensions is developed: technical performance properties of the IPS, economical aspects, relevant use-case requirements, and appropriate data aggregation strategies. Following this, two representable use-cases show the implementation of an indoor-positioning-system and the data aggregation in order to derive relevant process data from position data. Y1 - 2019 UR - https://isl21.org/wp-content/uploads/2020/04/Full-paper-20_07_2019-Final-V2.pdf SP - 232 EP - 241 ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Batres, Rafael A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A Peak Shaving Approach in Manufacturing Combining Machine Learning and Job Shop Scheduling T2 - Lecture Notes in Mechanical Engineering N2 - Computerized Numerical Control (CNC) plays an important role in highly autonomous manufacturing systems with multiple machine tools. The necessary Numerical Control (NC) programs to manufacture the parts are mostly written in standardized G-code. An a priori evaluation of the energy demand of CNC-based machine processes opens up the possibility of scheduling multiple jobs according to balanced energy consumption over a production period. Due to this, we present a combined Machine Learning (ML) and Job-Shop-Scheduling (JSS) approach to evaluate G-code for a CNC-milling process with respect to the energy demand of each G-command. The ML model training data are derived by the Latin hypercube sampling (LHS) method facing the main G-code operations G00, G01, and G02. The resulting energy demand for each job enhances a JSS algorithm to smooth the energy demand for multiple jobs, as peak power consumption needs to be avoided due to its expense. Y1 - 2025 SN - 9783031774287 U6 - https://doi.org/10.1007/978-3-031-77429-4_59 SN - 2195-4356 SP - 535 EP - 543 PB - Springer Nature Switzerland CY - Cham ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Simon A1 - Miller, Eddi A1 - Bräutigam, Volker A1 - Schmitt, Jan T1 - Advances in machine learning detecting changeover processes in cyber physical production systems JF - Journal of Manufacturing and Materials Processing N2 - The performance indicator, Overall Equipment Effectiveness (OEE), is one of the most important ones for production control, as it merges information of equipment usage, process yield, and product quality. The determination of the OEE is oftentimes not transparent in companies, due to the heterogeneous data sources and manual interference. Furthermore, there is a difference in present guidelines to calculate the OEE. Due to a big amount of sensor data in Cyber Physical Production Systems, Machine Learning methods can be used in order to detect several elements of the OEE by a trained model. Changeover time is one crucial aspect influencing the OEE, as it adds no value to the product. Furthermore, changeover processes are fulfilled manually and vary from worker to worker. They always have their own procedure to conduct a changeover of a machine for a new product or production lot. Hence, the changeover time as well as the process itself vary. Thus, a new Machine Learning based concept for identification and characterization of machine set-up actions is presented. Here, the issue to be dealt with is the necessity of human and machine interaction to fulfill the entire machine set-up process. Because of this, the paper shows the use case in a real production scenario of a small to medium size company (SME), the derived data set, promising Machine Learning algorithms, as well as the results of the implemented Machine Learning model to classify machine set-up actions. Y1 - 2020 UR - https://www.proquest.com/docview/2461685989?pq-origsite=gscholar&fromopenview=true VL - 4 IS - 4 SP - 108 EP - 108 ER - TY - JOUR A1 - Neuber, Till A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Evaluation of the Influence of Machine Tools on the Accuracy of Indoor Positioning Systems JF - Sensors Y1 - 2022 VL - 22 IS - 24 SP - 10015 EP - 10015 ER - TY - CHAP A1 - Schmitt, Anna-Maria A1 - Miller, Eddi A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Energy Prediction for CNC Machines Using G-Code Evaluation, Machine Learning and a Real-World Training Part T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 U6 - https://doi.org/10.1109/ICMRE64970.2025.10976308 ER - TY - JOUR A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Regionalstudie Auswirkungen des globalen Klimawandels in Mainfranken BT - Grundlagenwissen, aktuelle Strategien und Bedarfe ansässiger Wirtschaft N2 - Mainfränkische Unternehmen und Handwerksbetriebe stehen aufgrund expandierender Wertschöpfungsketten in einem starken Abhängigkeitsverhältnis zu ihren global verteilten Zulieferern. Dadurch ist die Wertschöpfungskette anfällig für externe Störungen, die unter anderem durch den Klimawandel ausgelöst werden. Zugleich sind die Erwärmungsraten in der bayerischen Region derzeit deutlich höher als im bundesweiten Durchschnitt. Die Entwicklung von strategischen Maßnahmen zur Klimaanpassung ist demnach unerlässlich, um die unternehmensspezifischen Risiken des Klimawandels zu antizipieren und zu minimieren. Die Klimaanpassung ist in vielen kommunalen, wirtschaftlichen und gesellschaftlichen Bereichen eine der größten Herausforderungen der Gegenwart. Die vorliegende Regionalstudie beabsichtigt daher eine Abgrenzung der Verhältnisse und Wechselwirkungen des globalen Klimawandels, der Auswirkungen in der bayerischen Region Mainfranken sowie der aufkommenden Veränderungsbedarfe für gesellschaftliche, politische und wirtschaftliche Akteure. Ein umfassender grundlagentheoretischer Überblick dient zunächst der Einordnung wichtiger Ansatzpunkte aus politischer Perspektive und stellt Angebote für Wirtschaftsakteure dar. Ferner werden die wirtschaftlichen Ausprägungen nach Handwerksbetrieben und Unternehmen differenziert, sowie deren Rolle für Wachstum und Innovation in der Region, als auch in Bezug auf den Klimawandel und die erforderliche Anpassung aufgezeigt. Die Ergebnisse einer quantitativen Erhebung veranschaulichen, dass neben der Wirtschaftlichkeit und physischen Ressourcen, menschliche Faktoren zur Erhöhung der organisationalen Klimaresilienz beitragen. Um als wirtschaftliche Organisationen einen adäquaten Umgang mit dem Klimawandel zu finden, sind bspw. zunächst Führungskräfte aufgefordert einen systemischen Ansatz mit umfangreichen Maßnahmen zu Klimaschutz und Klimaanpassung zu entwickeln, auf ihre Wirksamkeit zu erproben und ganzheitlich zu integrieren. Mit der vorliegenden Regionalstudie wird deutlich, dass neben dem Klimaschutz, der Reduzierung klimaschädlicher Treibhausgasemissionen, die Klimaanpassung ein unverzichtbarer Aspekt ist, um die wirtschaftliche Effizienz zu erhalten und sogar zu erhöhen, indem die veränderten Anforderungen als Entwicklungschancen wahrgenommen werden. KW - klimaanpassung KW - regionalstudie KW - mainklimaplus Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19959 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Anna-Maria A1 - Theilacker, Lukas A1 - Schmitt, Jan T1 - Implications from Legacy Device Environments on the Conceptional Design of Machine Learning Models in Manufacturing JF - Journal of Manufacturing and Materials Processing Y1 - 2024 UR - https://doi.org/10.3390/jmmp8010015 VL - 2024 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Anna-Maria A1 - Heusinger, Moritz A1 - Borysenko, Vladyslav A1 - Niedner, Niklas A1 - Schmitt, Jan T1 - Detecting Changeover Events on Manufacturing Machines with Machine Learning and NC data JF - Applied Artificial Intelligence Y1 - 2024 UR - https://doi.org/10.1080/08839514.2024.2381317 PB - Taylor & Francis ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Miller, Eddi A1 - Engelmann, Bastian A1 - Batres, Rafael A1 - Schmitt, Jan T1 - G-code evaluation in CNC milling to predict energy consumption through Machine Learning JF - Advances in Industrial and Manufacturing Engineering N2 - Computerized Numeric Control (CNC) plays an essential role in highly autonomous manufacturing systems for interlinked process chains for machine tools. NC-programs are mostly written in standardized G-code. Evaluating CNC-controlled manufacturing processes before their real application is advantageous due to resource efficiency. One dimension is the estimation of the energy demand of a part manufactured by an NC-program, e.g. to discover optimization potentials. In this context, this paper presents a Machine Learning (ML) approach to assess G-code for CNC-milling processes from the perspective of the energy demand of basic G-commands. We propose Latin Hypercube Sampling as an efficient method of Design of Experiments to train the ML model with minimum experimental effort to avoid costly setup and implementation time of the model training and deployment. KW - Machine Learning KW - CNC machine tools KW - G-code KW - Energy consumption Y1 - 2024 UR - https://doi.org/10.1016/j.aime.2024.100140 VL - 2024 IS - 8 ER - TY - GEN A1 - Schmitt, Jan T1 - MainWarmUp BT - Aufwärmtraining Klimawissen N2 - Das Spiel MainWarmUp bietet einen schnellen und guten Einstieg in die Thematik „Klimawissen für produzierende Unternehmen“. Mit zehn verschiedenen Aufgaben werden den Spielenden zahlreiche Maßnahmen rund um den Klimawandel vorgestellt, die Unternehmen zum Klimaschutz oder zur -anpassung anwenden könnten. Finden Sie sinnvolle Kombinationen, ordnen Sie die Karten verschiedenen Kategorien zu oder bereiten einen Klimapitch vor. KW - Klimaanpassung KW - Klimaschutz KW - game-based learning Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20756 ER - TY - CHAP A1 - Hartmann, Jürgen A1 - Dzemko, Mikita A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Toward Shifted Production Strategies Through Additive Manufacturing: A Technology and Market Review for Changing Value Chains T2 - 7th CIRP Global Web Conference (86) N2 - In the last decade many different additive manufacturing (AM) technologies for metal, plastic or ceramic processing raise from research to commercialization. As a result, AM grows into different business areas and transforms structures and processes. Hence, the contribution tends to show the change in added values though the availability of different additive manufacturing technologies based on a technology screening and market research. Regarding the named purpose, a broad market research of 83 companies and 339 printer models has been conducted to find patterns of AM technology market share and regions to structure indicators such as accuracy by processed material classes with a specified AM method. Printing materials as metal, plastic, ceramic and carbon have been considered. The categorization is done by the AM principles: power bed fusion, material extrusion, vat photopolymerization and … Y1 - 2019 U6 - https://doi.org/10.1016/j.procir.2020.01.029 VL - 86 SP - 228 EP - 233 ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Deep Reinforcement Learning for Adaptive Job Shop Scheduling in Robotic Cells: Handling Disruptions Effectively T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 UR - 10.1109/ICMRE64970.2025.10976238 ER - TY - CHAP A1 - Schmitt, Anna-Maria A1 - Antonov, Anna A1 - Schmitt, Jan A1 - Engelmann, Bastian T1 - Classification of Production Process Phases with Multivariate Time Series Techniques T2 - 2024 22nd International Conference on Research and Education in Mechatronics (REM) Y1 - 2024 U6 - https://doi.org/10.1109/REM63063.2024.10735481 ER - TY - JOUR A1 - Knopp, Kevin A1 - Shandy, Amir A1 - Manara, Jochen A1 - Vidi, Stephan A1 - Hartmann, Jürgen T1 - Metrologische Apparaturen zur Messung thermophysikalischer Materialeigenschaften bei sehr hohen Temperaturen im EU-Projekt Hi-TRACE JF - FHWS Science Journal N2 - Industriezweige wie die Glas-Industrie, die Kraftwerkstechnik sowie die Luft- und Raumfahrttechnik müssen kontinuierlich neue Methoden entwickeln, sowie bestehende Verfahren optimieren, um in ihren Bereichen wettbewerbsfähig zu sein bzw. neue Anforderungen an Umwelt- und Klimaschutz zu erfüllen. Dies beinhaltet oft die Entwicklung neuer Materialien, die leichter zu fabrizieren sind und sowohl mechanisch als auch thermisch höheren Belastungen standhalten. Für die genannten Industriezweige sind Prozesse mit hohen Betriebstemperaturen bis zu 3.000 °C kennzeichnend und damit ist die Kenntnis von Materialeigenschaften bei diesen extremen Temperaturen von großer Bedeutung. Auch wenn es bereits einige Messapparaturen für die Bestimmung von thermophysikalischen Materialdaten bei hohen Temperaturen gibt, muss die Rückführung dieser auf die SI Basiseinheiten gewährleistet werden, um die Zuverlässigkeit der gemessenen Daten für die Anforderung der genannten Branchen sicherzustellen. Diese Aufgabe ist das Ziel des EMPIR-(European Metrology Programme for Innovation and Research) Projektes Hi-TRACE [1]. Hi-TRACE zielt darauf ab, Referenzapparaturen und neue Methoden für die Messung von thermophysikalischen Materialeigenschaften, (thermische Diffusivität, spezifische Wärme, Emissionsgrad und Schmelztemperatur) sowie der Haftung von Schichten über 1.000 °C zu bestimmen. KW - thermophysik KW - temperatur Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20046 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 83 EP - 92 ER - TY - JOUR A1 - Ochs, Dennis A1 - Wehnert, Kira-Kristin A1 - Knopp, Kevin A1 - Hartmann, Jürgen A1 - Versch, Alexander A1 - Schiffler, Andreas T1 - Untersuchungen zur Temperaturleitfähigkeit additiv gefertigter Stahlproben in Abhängigkeit der relativen Dichte JF - FHWS Science Journal N2 - Das direkte Metall-Laser-Schmelzen (DMLS) aus der Familie der Additiven Fertigungsverfahren (AM) ermöglicht die schichtweise Erzeugung komplexer dreidimensionaler Geometrien mit hoher relativer Dichte unter Verwendung von Metallpulver als Ausgangsmaterial [1]. Die Technologie wird zunehmend eingesetzt, um innovative Bauteile material- und gewichtssparend herzustellen oder komplexe Produkte ohne zusätzliche Werkzeuge oder Spannvorrichtungen zu fertigen. Darüber hinaus sind Funktionsintegrationen, zum Beispiel Gussformen mit eingeprägten Kühlkanälen, möglich. Da einzelne Metallpulverschichten auf vorhergehende Schichten aufgeschmolzen werden, entstehen während der Herstellung des Bauteils komplexe, zeitabhängige Temperaturprofile [2]. Durch den Einsatz hoher Laserintensitäten und Scangeschwindigkeiten, bei denen die Belichtungszeit der Laserbestrahlung im Bereich von Millisekunden liegt, werden zudem extrem hohe Aufheiz- und Abkühlraten induziert, die zu einzigartigen Mikrostrukturen und Materialeigenschaften führen [3]. Diese extremen Prozessbedingungen können sich jedoch auch negativ auf den Fertigungsprozess auswirken. Bei komplexen Bauteilen bleibt die Prozessstabilität und Qualitätssicherung Umfragen zufolge weiterhin die wichtigste technologische Barriere für den Einsatz additiv gefertigter Bauteile in hochbelasteten oder sicherheitsrelevanten Bereichen [4]. Daher verspricht der Zusammenhang zwischen Temperaturprofil während der Fertigung, relativer Dichte der Bauteile, sowie thermophysikalischer Eigenschaften additiv gefertigter Proben wichtige Erkenntnisse, insbesondere im Hinblick auf eine zerstörungsfreie Qualitätssicherung, sowie neue Anwendungsmöglichkeiten. KW - temperatur KW - additive fertigung Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19986 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 75 EP - 82 ER - TY - JOUR A1 - Fischer, Sophie A1 - Keupp, Luzia A1 - Paeth, Heiko A1 - Göhlich, Michael A1 - Schmitt, Jan T1 - Climate adaptation as organizational learning: a grounded theory study on manufacturing companies in a Bavarian Region JF - Education Sciences Y1 - 2022 VL - 12 IS - 1 SP - 22 EP - 22 ER - TY - JOUR A1 - Fischer, Sophie A1 - Göhlich, Michael A1 - Schmitt, Jan T1 - Interrelationships of climate adaptation and organizational learning: Development of a measurement model JF - Journal of Pedagogical Research Y1 - 2022 VL - 6 IS - 5 SP - 130 EP - 152 ER - TY - CHAP A1 - Schmitt, Jan T1 - Ein integriertes Vorgehensmodell zur Implementierung eines nachhaltigen Wertstoffmanagements T2 - CSR in Süddeutschland: Unternehmerischer Erfolg und Nachhaltigkeit im Einklang Y1 - 2022 SP - 93 EP - 105 ER - TY - CHAP A1 - Bremer, Peik A1 - Tsai, Kune-muh T1 - Smartness in picker-to-parts order picking: a socio-technical systems theory perspective N2 - Purpose of this paper: Surveys have shown that most companies still use paper-based lists or RF handhelds to support picker-to-parts order picking. However, more modern approaches such as replacing handhelds with small wearables, Pick-by-Voice, Pick-by-Vision, or even autonomous picking robots are on the rise. This fits into a broader trend commonly referred to as "smart logistics". However, what "smartness" means in this context remains unclear. This paper aims to contribute to the understanding of smartness in picker-to- parts order picking by applying socio-technical systems theory. Design/methodology/approach: The methodological approach uses a socio-technical analysis and a combination of two frameworks involving smart capabilities to identify the characteristics of "smart" picker- to-parts order picking. Findings: Typically, smartness is considered a property of the assistive devices used in order picking (such as smart glasses in Pick-by-Vision). Instead, smartness should be judged by the extent to which the picking system is implemented as a socio-technical system with comprehensive, meaningful tasks. Thus, smart picker-to-parts order picking is an alternative concept to the digital Tayloristic approach supported by the prevailing assistive devices. A number of elements are proposed for the design of a smart picking system, including establishing responsible autonomy, reducing cognitive load, improving ergonomics, and human-machine interaction based on contextual adaptation. Value: This paper contributes to the still relatively small body of literature on smart picker-to- parts order picking by clarifying the dimensions of smartness in this field. A clearer understanding of smartness is helpful in avoiding getting trapped in digital Tayloristic work patterns, mediated and controlled by the currently available tools. It also supports creating a more favorable work environment for warehouse personnel. Research limitations/implications: So far, the concept of smartness in picker-to-part order picking is purely conceptual. Practical implications: The evaluation framework can be used to critically assess the technology currently used in warehouses to support picker-to-parts order picking and to guide the development of new systems. KW - Smart Logistics KW - Order picking KW - Socio-technical Systems Theory Y1 - 2023 UR - https://drive.google.com/file/d/1tbYBK_q8zDnSrWRrx6fq6qH2eEDxKu5I/view PB - International Symposium on Logistics "Managing Supply Chains during Geopolitical Turbulence", Enschede, 9.-12. Juli ER - TY - CHAP A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Industrie 4.0 für Studierende des Wirtschaftsingenieurwesens T2 - Kompetenzen für die digitale Transformation 2020: Digitalisierung der Arbeit-Kompetenzen-Nachhaltigkeit 1. Digitalkompetenz-Tagung Y1 - 2021 SP - 265 EP - 273 ER - TY - JOUR A1 - Wilhelm, Markus A1 - Manghisi, Vito Modesto A1 - Uva, Antonello A1 - Fiorentino, Michele A1 - Bräutigam, Volker A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - ErgoTakt: A novel approach of human-centered balancing of manual assembly lines JF - Procedia CIRP N2 - Although the increasing use of automation in industry, manual assembly stations are still common and, in some situations, even inevitable. Current practice in manual assembly lines is to balance them using the takt-time of each workstation and harmonize it. However, this approach mostly does not include ergonomic aspects and thus it may lead to workforce musculoskeletal disorders, extended leaves, and demotivation. This paper presents a holistic human-centric optimization method for line balancing using a novel indicator ̶ the ErgoTakt. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and its balance in time. The authors used a custom version of the ErgoSentinel Software and a Microsoft Kinect depth camera to perform online and real-time ergonomic assessment. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-value and the cycle time of each assembly workstation with respect to the worker's ability. The paper presents the concept, the system-setup and preliminary evaluation of an assembly scenario. The results demonstrate that the new approach is feasible and able to optimize an entire manual assembly process chain in terms of both, economic aspects of a well-balanced production line as well as the ergonomic issue of long term human healthy work. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1016/j.procir.2020.05.250 VL - 97 SP - 354 EP - 360 ER - TY - CHAP A1 - Schmitt, Jan A1 - Hillenbrand, Andreas A1 - Kranz, Philipp A1 - Kaupp, Tobias T1 - Assisted human-robot-interaction for industrial assembly: Application of spatial augmented reality (sar) for collaborative assembly tasks T2 - Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction Y1 - 2021 SP - 52 EP - 56 ER - TY - CHAP A1 - Schmitt, Jan A1 - Kranz, Philipp A1 - Hillenbrand, Andreas A1 - Kaupp, Tobias T1 - Assisted human-robot-interaction for industrial assembly: Video to assisted human-robot-interaction for industrial assembly T2 - Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction Y1 - 2021 SP - 665 EP - 667 ER - TY - CHAP A1 - Vogler, N. A1 - Kaupp, Tobias A1 - Schmitt, Jan A1 - Antelmann, H. T1 - Maturity level models for the evaluation of the digitalization progress of assembly-intensive production processes T2 - German Assembly Engineering 2019 Y1 - 2019 ER - TY - JOUR A1 - Miller, Eddi A1 - Engelmann, Bastian A1 - Kaupp, Tobias A1 - Schmitt, Jan T1 - Advanced Cascaded Scheduling for Highly Autonomous Production Cells with Material Flow and Tool Lifetime Consideration using AGVs JF - Journal of Machine Engineering Y1 - 2023 UR - https://doi.org/10.36897/jme/171749 SN - 2391-8071 ER - TY - CHAP A1 - Seitz, Philipp A1 - Schmitt, Jan A1 - Engelmann, Bastian T1 - Evaluation of proceedings for SMEs to conduct I4.0 projects T2 - Procedia Cirp Y1 - 2019 VL - 86 SP - 257 EP - 263 ER - TY - JOUR A1 - Hofmann, Jan A1 - Eberhardt, Lars A1 - Heusinger, Moritz A1 - Dobhan, Alexander A1 - Engelmann, Bastian A1 - Schleif, Frank-Michael T1 - Optimierung von Prozessen und Werkzeugmaschinen durch Bereitstellung, Analyse und Soll-Ist-Vergleich von Produktionsdaten JF - FHWS Science Journal N2 - Mit einem Umsatz von 103 Milliarden Euro ist die Metallindustrie eine der größten deutschen Industriebranchen. Diese ist von volatilen Marktbedingungen und hohem Wettbewerb geprägt [1][2]. Kleine und mittlere produzierende Unternehmen (sogenannte KMU) sehen zunehmend gravierende Probleme bei der Einhaltung von Lieferterminen bedingt durch hohe Durchlaufzeiten in der Produktion [3]. Neben kaufmännischen Planungssystemen zur Erstellung von Produktionsplänen nutzen Unternehmen als Planungsgrundlage weiterhin Excel mit 31 % und manuelle Prozesse mit 10 % [4]. Gleiches gilt für Produktwechselvorgänge auf Maschinen (Rüsten). Aufgrund dieser Aspekte ist es notwendig, die Rentabilität der KMU in der Metallindustrie zu steigern. Das wird durch effiziente Produktionsplanung und -steuerung, sowie der daraus resultierenden hohen Reaktionsfähigkeit und Flexibilität realisiert. Daher ist die Produktionsplanung auf die Markt- und Kundenanforderungen und die Anlageneffektivität auf ein hohes und stabiles Niveau auszurichten [5]. Hier bietet die Erfassung von Echtzeitdaten eine adäquate Reaktion auf die genannten Anforderungen. Ebenfalls liefert sie großes Potenzial für die Produktionsplanung und -steuerung, um die Disposition und Koordination von Arbeitsaufträgen zu optimieren. Weiterhin werden Störgrößen oder unvorhergesehene Planungsabweichungen reduziert [4][6]. Zusätzlich ist eine erhöhte Transparenz und Verbesserung menschlicher Entscheidungsprozesse notwendig. Dies kann durch datengetriebene Methoden unterstützt und sichergestellt werden [7]. Ein Ansatz zur Optimierung des Produktionsergebnisses kann durch die Erhöhung der Anlagenproduktivität selbst realisiert werden. Dazu muss die Verfügbarkeit der Anlagen durch Lokalisierung und Reduzierung von Verlusten erhöht werden. Die Umrüstungsprozesse tragen stark negativ zur Verfügbarkeit einer Produktion bei. Eine Steigerung der Gesamtanlageneffektivität (overall equipment effectiveness oder kurz OEE) in einer Fertigungsumgebung ist jedoch möglich durch eine intelligente Nutzung von Sensordaten mit Techniken wie z. B. Machine Learning (ML). KW - produktionsdaten KW - metall Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20012 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 135 EP - 142 ER - TY - CHAP A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Anomaly Detection for Dynamic Human-Robot Assembly: Application of an LSTM-based autoencoder to interpret uncertain human behavior in HRC T2 - Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction Y1 - 2023 U6 - https://doi.org/10.1145/3568294.3580100 SP - 881 EP - 883 ER - TY - CHAP A1 - Miller, Eddi A1 - Kaupp, Tobias A1 - Schmitt, Jan ED - Kohl, Holger ED - Seliger, Günther ED - Dietrich, Franz T1 - Cascaded Scheduling for Highly Autonomous Production Cells with AGVs T2 - Manufacturing Driving Circular Economy: Proceedings of the 18th Global Conference on Sustainable Manufacturing, October 5-7, 2022, Berlin ; Lecture Notes in Mechanical Engineering N2 - Highly autonomous production cells are a crucial part of manufacturing systems in industry 4.0 and can contribute to a sustainable value-adding process. To realize a high degree of autonomy in production cells with an industrial robot and a machine tool, an experimental approach was carried out to deal with numerous challenges on various automation levels. One crucial aspect is the scheduling problem of tasks for each resource (machine tool, tools, robot, AGV) depending on various data needed for a job-shop scheduling algorithm. The findings show that the necessary data has to be derived from different automation levels in a company: horizontally from ERP to shop-floor, vertically from the order handling department to the maintenance department. Utilizing that data, the contribution provides a cascaded scheduling approach for machine tool jobs as well as CNC and robot tasks for highly autonomous production cells supplied by AGVs. Y1 - 2023 SN - 978-3-031-28838-8 SN - 978-3-031-28839-5 U6 - https://doi.org/https://doi.org/10.1007/978-3-031-28839-5_43 SP - 383 EP - 390 PB - Springer CY - Cham ER - TY - JOUR A1 - Miller, Eddi A1 - Ceballos, Hector A1 - Engelmann, Bastian A1 - Schiffler, Andreas A1 - Batres, Rafael A1 - Schmitt, Jan T1 - Industry 4.0 and International Collaborative Online Learning in a Higher Education Course on Machine Learning JF - 2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop Y1 - 2021 SP - 1 EP - 8 ER - TY - JOUR A1 - Seitz, Philipp A1 - Scherdel, Christian A1 - Reichenauer, Gudrun A1 - Schmitt, Jan T1 - Machine Learning in the development of Si-based anodes using Small-Angle X-ray Scattering for structural property analysis JF - Computational Materials Science Y1 - 2023 VL - 218 SP - 111984 EP - 111984 ER - TY - JOUR A1 - Scherdel, Christian A1 - Miller, Eddi A1 - Reichenauer, Gudrun A1 - Schmitt, Jan T1 - Advances in the Development of Sol-Gel Materials Combining Small-Angle X-ray Scattering (SAXS) and Machine Learning (ML) JF - Processes Y1 - 2021 VL - 9 IS - 4 SP - 672 EP - 672 ER - TY - CHAP A1 - Wehnert, Kira-Kristin A1 - Schäfer, S A1 - Schmitt, Jan A1 - Schiffler, Andreas T1 - C7. 4 Application of Laser Line Scanners for Quality Control during Selective Laser Melting (SLM) T2 - SMSI 2021-System of Units and Metreological Infrastructure Y1 - 2021 SP - 298 EP - 299 ER - TY - JOUR A1 - Seitz, Philipp A1 - Schmitt, Jan T1 - Alternating Transfer Functions to Prevent Overfitting in Non-Linear Regression with Neural Networks JF - Journal of Experimental & Theoretical Artificial Intelligence N2 - In nonlinear regression with machine learning methods, neural networks (NNs) are ideally suited due to their universal approximation property, which states that arbitrary nonlinear functions can thereby be approximated arbitrarily well. Unfortunately, this property also poses the problem that data points with measurement errors can be approximated too well and unknown parameter subspaces in the estimation can deviate far from the actual value (so-called overfitting). Various developed methods aim to reduce overfitting through modifications in several areas of the training. In this work, we pursue the question of how an NN behaves in training with respect to overfitting when linear and nonlinear transfer functions (TF) are alternated in different hidden layers (HL). The presented approach is applied to a generated dataset and contrasted to established methods from the literature, both individually and in combination. Comparable results are obtained, whereby the common use of purely nonlinear transfer functions proves to be not recommended generally. KW - Machine learning; nonlinear regression; function approximation; overfitting; transfer function Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-49199 UR - https://doi.org/10.1080/0952813X.2023.2270995 ER - TY - JOUR A1 - Weber, Aleksej A1 - Wilhelm, Markus A1 - Schmitt, Jan T1 - Analysis of Factors Influencing the Precision of Body Tracking Outcomes in Industrial Gesture Control JF - sensors N2 - The body tracking systems on the current market offer a wide range of options for tracking the movements of objects, people, or extremities. The precision of this technology is often limited and determines its field of application. This work aimed to identify relevant technical and environmental factors that influence the performance of body tracking in industrial environments. The influence of light intensity, range of motion, speed of movement and direction of hand movement was analyzed individually and in combination. The hand movement of a test person was recorded with an Azure Kinect at a distance of 1.3 m. The joints in the center of the hand showed the highest accuracy compared to other joints. The best results were achieved at a luminous intensity of 500 lx, and movements in the x-axis direction were more precise than in the other directions. The greatest inaccuracy was found in the z-axis direction. A larger range of motion resulted in higher inaccuracy, with the lowest data scatter at a 100 mm range of motion. No significant difference was found at hand velocity of 370 mm/s, 670 mm/s and 1140 mm/s. This study emphasizes the potential of RGB-D camera technology for gesture control of industrial robots in industrial environments to increase efficiency and ease of use. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57575 VL - 24 IS - 18 PB - MDPI ER - TY - RPRT A1 - Asikainen, Eveliina A1 - Eskola-Salin, Nina A1 - Fischer, Sophie A1 - Giedraitiené, Vytautė A1 - Beseckas, Povilas A1 - Mairhofer, Stephanie A1 - Köder, Lea A1 - Schmitt, Jan A1 - Walter, Holger A1 - Guerrero-Perez, Olga A1 - Blázquez-Parra, Elidia Beatriz A1 - Bikuviené, Ina A1 - Lisina, Neringa A1 - Tamuliené, Rasa A1 - Liepinaitiené, Alina A1 - Mäkelä, Anne-Maria A1 - Tahlo, Sanna A1 - Selimaa, Hanna A1 - Hager, Veronika A1 - Ortega-Casanova, Joaquin A1 - Mora-Segado, Patricia T1 - Sustainability at HEIs: Mapping Good Practice N2 - Global climate change is a cognitive challenge for many people and often evokes negative associations due to its complexity and interactions with politics, social movements and economic developments. Therefore, the possession of green skills becomes central to the fight against climate change. The European Council conclusions recognize this urgency and underline the need for a transition to green skills. This recognition also extends to higher education, where institutions have a crucial role to play in tackling the climate crisis. Personal Green Skills in Higher Education (PeGSinHE) is an Erasmus+ KA2 project coordinated by Kauno Kolegija (KK, Lithuania), Tampere University of Applied Sciences (TAMK, Finland), Hochschule für Agrar- und Umweltpädagogik (HAUP, Austria), Universidad de Málaga (UMA, Spain) and Technical University of Applied Sciences Würzburg Schweinfurt (THWS, Germany). The strategically designed project aims not only to promote green skills among students and encourage personal behavioral change in line with the Sustainable Development Goals, but also to instill a sense of social responsibility in the partner institutions. The focus is on empowering lecturers at partner universities through innovative teaching and learning methods to effectively impart green skills to students. This report describes the objectives and methodology used to assess environmental and sustainability competencies in the higher education institutions involved in the project. Methodologically, the report uses an assessment template designed to provide a comprehensive overview of best practice and baseline levels of environmental and sustainability competencies. It advocates the involvement of key stakeholders from all five partner Higher Education Institutions to ensure a broad perspective on these practices and competences within their respective countries and organizations. Different methods and perspectives will be used to collect data to enable a holistic understanding of the topic. The joint completion of the assessment template serves as a catalyst for joint discussions on the level of environmental and sustainability competencies and the identification of best practices in each organization. The results show that national implementation strategies are relatively loose, although some competency descriptions set targets for undergraduate degree programs. Challenges faced by higher education staff include resource constraints, particularly lack of time, the need for a deeper understanding of sustainable development and pedagogical tools, and the need for improved opportunities for collaboration. Given the time and resource constraints of this study, the results must be considered preliminary. Nevertheless, they confirm the findings of previous studies. KW - sustainability KW - best practice KW - HEI KW - green skills Y1 - 2024 U6 - https://doi.org/10.57714/b75p-n548 N1 - Es wurde nachträglich am 28.03.2025 ein Logo in der Datei ausgetauscht, inhaltlich gab es jedoch keine Änderungen. ER - TY - JOUR A1 - Wilhelm, Markus A1 - Lotter, Frank A1 - Scherdel, Christian A1 - Schmitt, Jan T1 - Advancing Efficiency in Mineral Construction Materials Recycling: A Comprehensive Approach Integrating Machine Learning and X-ray Diffraction Analysis JF - buildings N2 - In the context of environmental protection, the construction industry plays a key role with significant CO2 emissions from mineral-based construction materials. Recycling these materials is crucial, but the presence of hazardous substances, i.e., in older building materials, complicates this effort. To be able to legally introduce substances into a circular economy, reliable predictions within minimal possible time are necessary. This work introduces a machine learning approach for detecting trace quantities (≥0.06 wt%) of minerals, exemplified by siderite in calcium carbonate mixtures. The model, trained on 1680 X-ray powder diffraction datasets, provides dependable and fast predictions, eliminating the need for specialized expertise. While limitations exist in transferability to other mineral traces, the approach offers automation without expertise and a potential for real-world applications with minimal prediction time. KW - Architecture KW - Building and Construction KW - Civil and Structural Engineering Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56030 SN - 2075-5309 VL - 14 IS - 2 PB - MDPI ER - TY - JOUR A1 - Lang, Silvio A1 - Engelmann, Bastian A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A simplified machine learning product carbon footprint evaluation tool JF - Cleaner Environmental Systems N2 - On the way to climate neutrality manufacturing companies need to assess the Carbon dioxide (CO2) emissions of their products as a basis for emission reduction measures. The evaluate this so-called Product Carbon Footprint (PCF) life cycle analysis as a comprehensive method is applicable, but means great effort and requires interdisciplinary knowledge. Nevertheless, assumptions must still be made to assess the entire supply chain. To lower these burdens and provide a digital tool to estimate the PCF with less input parameter and data, we make use of machine learning techniques and develop an editorial framework called MINDFUL. This contribution shows its realization by providing the software architecture, underlying CO2 factors, calculations and Machine Learning approach as well as the principles of its user experience. Our tool is validated within an industrial case study. KW - Management, Monitoring, Policy and Law KW - Environmental Science (miscellaneous) KW - Renewable Energy, Sustainability and the Environment KW - Environmental Engineering Y1 - 2024 U6 - https://doi.org/10.1016/j.cesys.2024.100187 SN - 2666-7894 VL - 13 PB - Elsevier BV ER - TY - CHAP A1 - Gattullo, Michele A1 - Dammacco, Lucilla A1 - Ruospo, Francesca A1 - Evangelista, Alessandro A1 - Fiorentino, Michele A1 - Schmitt, Jan A1 - Uva, Antonio E T1 - Design preferences on industrial augmented reality: a survey with potential technical writers T2 - 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) Y1 - 2020 SP - 172 EP - 177 ER - TY - JOUR A1 - Miller, Eddi A1 - Borysenko, Vladyslav A1 - Heusinger, Moritz A1 - Niedner, Niklas A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Enhanced Changeover Detection in Industry 4.0 Environments with Machine Learning JF - Sensors Y1 - 2021 VL - 21 IS - 17 SP - 5896 EP - 5896 ER - TY - JOUR A1 - Schuster, Florian A1 - Engelmann, Bastian A1 - Sponholz, Uwe A1 - Schmitt, Jan A1 - Engineering, Institute Digital T1 - Human acceptance evaluation of AR-assisted assembly scenarios JF - Journal of Manufacturing Systems Y1 - 2021 VL - 61 SP - 660 EP - 672 ER - TY - CHAP A1 - Schuster, Florian A1 - Sponholz, Uwe A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - A user study on AR-assisted industrial assembly T2 - 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) Y1 - 2020 SP - 135 EP - 140 ER - TY - CHAP A1 - Pfeuffer, Katharina A1 - Fischer, Sophie A1 - Schmitt, Jan A1 - Bräutigam, Volker T1 - Human or Robot Resource Management? The Future of Work in the Digital Transformation of Manufactoring Companies T2 - Proceedings of the Conference on Production Systems and Logistics: CPSL 2025 N2 - This article examines the transformative effects of Smart Factory technologies - such as human-robot collaboration, intelligent assistance systems and cyber-physical production systems - on organizational design, with a particular focus on central fields of action for Human Resources management (HRM) and operational management. A case study of a German automotive supplier is used to examine how digitalization and automation are changing human work and organizational structures. Two future scenarios for organizational models are proposed: the swarm organization, which consists exclusively of highly qualified employees while robots take over routine tasks, and the polarized organization, which is characterized by a division between highly qualified specialists and low-skilled employees. Each scenario brings different challenges and opportunities for HR management, as companies need to adapt to digital skills, new models of collaboration and the management of a highly specialized or polarized workforce. This paper provides a conceptual framework and actionable insights for HRM and production management to manage the shift towards advanced, automated organizational models and ensure a smooth transition to the Smart Factory of the future. Y1 - 2025 U6 - https://doi.org/10.15488/18885 PB - publish-Ing. CY - Offenburg ER - TY - CHAP A1 - Fichtel, Lars A1 - Frühwald, Alexander A1 - Hösch, Leonhard A1 - Schreibmann, Vitaliy A1 - Bachmeir, Christian T1 - Tree Localization and Monitoring on Autonomous Drones employing Deep Learning T2 - PROCEEDING OF THE 29TH CONFERENCE OF FRUCT ASSOCIATION N2 - Forest management relies on the analysis of satellite imagery and time intensive physical on-site inspections. Both methods are costly and time consuming. Satellite based images are often not updated in a sufficient frequency to react to infestations or other occurring problems. Forest management benefits greatly from accurate and recent information about the local forest areas. In order to react appropriately and in time to incidents such as areas damaged by storms, areas infested by bark beetles and decaying ground water level, this information can be extracted from high resolution imagery. In this work, we propose UAVs to meet this demand and demonstrate that they are fully capable of gathering this information in a cost efficient way. Our work focuses on the cartography of trees to optimize forest-operation. We apply deep learning for image processing as a method to identify and isolate individual trees for GPS tagging and add some additional information such as height and diameter. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-24908 ER - TY - JOUR A1 - Höfflin, Dennis A1 - Sauer, Christian A1 - Schiffler, Andreas A1 - Manara, Jochen A1 - Hartmann, Jürgen T1 - Pixelwise high-temperature calibration for in-situ temperature measuring in powder bed fusion of metal with laser beam JF - Heliyon N2 - High-temperature calibration methods in additive manufacturing involve the use of advanced techniques to accurately measure and control the temperature of the build material during the additive manufacturing process. Infrared cameras, blackbody radiation sources and non-linear optimization algorithms are used to correlate the temperature of the material with its emitted thermal radiation. This is essential for ensuring the quality and repeatability of the final product. This paper presents the calibration procedure of an imaging system for in-situ measurement of absolute temperatures and temperature gradients during powder bed fusion of metal with laser beam (PBF-LB/M) in the temperature range of 500 K–1500 K. It describes the design of the optical setup to meet specific requirements in this application area as well as the procedure for accounting the various factors influencing the temperature measurement. These include camera-specific effects such as varying spectral sensitivities of the individual pixels of the sensor as well as influences of the exposure time and the exposed sensor area. Furthermore, influences caused by the complex optical path, such as inhomogeneous transmission properties of the galvanometer scanner as well as angle-dependent transmission properties of the f-theta lens were considered. A two-step fitting algorithm based on Planck's law of radiation was applied to best represent the correlation. With the presented procedure the calibrated thermography system provides the ability to measure absolute temperatures under real process conditions with high accuracy. Y1 - 2024 U6 - https://doi.org/10.1016/j.heliyon.2024.e28989 SN - 2405-8440 VL - 10 IS - 7 PB - Elsevier BV ER - TY - RPRT A1 - Riesel, Fabienne A1 - Bräutigam, Volker A1 - Wittmeier, Florian T1 - The Transformation of Work - Conducting and Aggregating Research on Human Resources in SMEs Facing Transformation Pressure N2 - Die Studie befasst sich mit den Herausforderungen und Chancen, die kleine und mittlere Unternehmen (KMU) in der Region Mainfranken, insbesondere in den Bereichen Maschinenbau und Automobilindustrie, im Zuge des Wandels der Arbeitswelt erleben. Ein zentrales Thema ist der Mangel an qualifizierten Arbeitskräften, der 89 % der befragten KMU betrifft. Die Unternehmen müssen attraktive Arbeitsbedingungen schaffen, um Talente zu gewinnen und zu halten, was zu einem "War for Talent" führt. Die Studie hebt die Notwendigkeit hervor, kreative Ansätze zur Mitarbeiterbindung und -gewinnung zu entwickeln, wie flexible Arbeitszeiten und Weiterbildungsmöglichkeiten. Zudem wird betont, dass eine enge Zusammenarbeit mit Bildungseinrichtungen und die Entwicklung maßgeschneiderter Schulungsprogramme entscheidend sind, um den Anforderungen des Marktes gerecht zu werden und die Wettbewerbsfähigkeit der Region zu sichern. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57352 ER - TY - JOUR A1 - Wilhelm, Markus A1 - Rosilius, Maximilian A1 - Bräutigam, Volker T1 - PlanAR – Planen mit Augmented Reality (AR) BT - Einsatz von AR bei Anlagenplanung und Materialflussoptimierung JF - FHWS Science Journal N2 - Die Weiterentwicklung von Endgeräten wie z.B. von NReal oder die Microsoft HoloLens 2 im Bereich Augmented Reality (AR) führt zu einem erweiterten Nutzungsfeld von AR außerhalb klassischer Entwicklungs- und »Gaming«-Umgebungen. Eine der sich intensivierenden Nutzungsoptionen ist der wertorientierte Einsatz im industriellen Umfeld. In diesem Bereich bedarf es noch einer weitreichenden Identifizierung und Evaluierung der Einsatzpotenziale und des -nutzens [1]. Naheliegender Vorteil der Technologie ist die Anwendung in integrativen Planungsprozessen z.B. in der Anlagenplanung. Durch die Visualisierung von virtuellen Inhalten in einer realen Umgebung, können zukünftige Veränderungen auf mögliche Störfaktoren bereits vor Umsetzung detailliert geprüft und optimiert werden. Dies führt zu Zeit- und Kostenersparnis in Planungsphasen, da nachträgliche Änderungen signifikant kostenintensiver und komplexer sind. Eine weitere Nutzungsmöglichkeit ist die Simulation von Fertigungsprozessen und deren Auswirkungen. Die Simulation kann insbesondere bei der Identifikation unternehmensunabhängiger Probleme helfen. Auch kann der zeitliche Faktor, der jedem Prozess zugrunde liegt, eingebettet in einem virtuell erweiterten Realszenario geprüft werden. Als Beispiel kann hier die Störungsbeseitigung in industriellen Fertigungsprozessen dienen, welche meistens einer notwendigen engen Taktung unterliegen. Störungen sind häufig durch die direkte Umwelt oder Probleme in Arbeitsabläufen begründet. An diesem Punkt können die möglichen Optimierungsoptionen unter den gegebenen Bedingungen eine erste Validierung erfahren, ohne direkten Eingriff in laufende Prozesse. Diese Anwendungsmöglichkeiten gilt es zu untersuchen und in eine gebrauchstaugliche Lösung für den Einsatz im wertschöpfenden Bereichen zu überführen. Ziel dabei ist es die noch hypothetischen Potenziale zu bewerten und in einsetzbare Applikationen zu transformieren, die den Anforderungen in einer industriellen Umgebung standhalten. Um eine nutzerorientierte Forschung zu gewährleisten, ist es notwendig den Bedarf der Industrie zu erfassen. An diesem Punkt setzt das Vorhaben PlanAR an und untersucht die interdisziplinären Auswirkungen der Anwendungsmöglichkeiten und Applikationen bei industrienahen Nutzungsanforderungen. KW - anlagenplanung KW - augmented reality Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20006 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 125 EP - 130 ER - TY - JOUR A1 - Wahyudi, Vincent A1 - Ziegler, Cedric C. A1 - Frieß, Matthias A1 - Schramm, Stefan A1 - Lang, Constantin A1 - Eberhardt, Lars A1 - Freund, Fabian A1 - Dobhan, Alexander A1 - Storath, Martin T1 - A computer vision system for recognition and defect detection for reusable containers JF - Machine Vision and Applications N2 - Abstract Small load carriers (SLCs) are standardized reusable containers used to transport and protect customer goods in many manufacturers. Throughout the life cycle of the SLCs, they will be collected, manually checked for defects (wear, cracks, and residue on the surface), and cleaned by specialized logistic companies. Human operators in small to medium-sized companies manually evaluate the defects due to the variety and degree of possible defects and varying customer needs. This manual evaluation is not scalable and prone to errors. This work aims to fill this gap by proposing a computer vision system that can recognize the SLC type for inventory management and perform defect detection automatically. First, we develop a camera portal, consisting of standard components, that capture the relevant surfaces of the SLC. A labeled dataset of 17,530 images of 34 different SLCs with their defect status was recorded using this camera portal. We trained a classification model (ConvNeXt) using our dataset to predict the different types of SLCs achieving 100% class prediction accuracy. For defect detection, we explore eight state-of-the-art (SOTA) anomaly detection models that achieved high rankings in the MVTec industrial anomaly detection benchmark. These models are trained using default hyperparameters and the two highest-scoring models were chosen and fine-tuned. The best-fine-tuned models based on “Area under the Receiver Operating Characteristic Curve (AUROC)” are PatchCore (0.811) and DRAEM (0.748). These results indicate that there is still potential for improvement in the automation of defect detection of SLCs. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57430 SN - 0932-8092 VL - 36 IS - 2 PB - Springer Science and Business Media LLC ER - TY - CHAP A1 - Müller, Jonas A1 - Eberhardt, Lars A1 - Wahyudi, Vincent A1 - Storath, Martin A1 - Dobhan, Alexander T1 - Towards an Approach on Location Data Analysis for Reusable Small-load Carriers T2 - Proceedings of the 58th Hawaii International Conference on System Sciences Y1 - 2025 UR - https://hdl.handle.net/10125/109488 ER - TY - RPRT A1 - Fischer, Sophie A1 - Walter, Holger A1 - Pfeuffer, Katharina A1 - Thalo, Sanna A1 - Mairhofer, Stephanie A1 - Juknevičienė, Živilė A1 - Mora Segado, Patricia T1 - 3 ECTS Blended Intensive Programme: Personal Green Skills N2 - Global climate change represents a cognitive challenge for many people and often evokes negative associations due to its complexity and its interactions with politics, social movements, and economic developments. Consequently, the development and possession of green skills have become central to addressing climate change. The European Council conclusions acknowledge this urgency and underline the need for a transition towards green skills. This recognition also extends to higher education, where institutions play a crucial role in tackling the climate crisis. Personal Green Skills in Higher Education (PeGSinHE) is an Erasmus+ KA2 project coordinated by Kauno Kolegija (KK, Lithuania), Tampere University of Applied Sciences (TAMK, Finland), Hochschule für Agrar- und Umweltpädagogik (HAUP, Austria), Universidad de Málaga (UMA, Spain), and the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS, Germany). The strategically designed project aims not only to promote green skills among students and encourage personal behavioural change in line with the Sustainable Development Goals, but also to foster a sense of social responsibility within the partner institutions. A particular focus lies on empowering lecturers at partner universities through innovative teaching and learning approaches to effectively impart green skills to students. This report documents the pilot implementation of an international 3 ECTS Blended Intensive Programme (BIP) developed within the EU project and delivered for the first time at the Technical University of Applied Sciences Würzburg-Schweinfurt in Germany. The programme is based on a curriculum co-created in focus groups and informed by a previously developed methodology, clearly defined learning objectives and learning outcomes, as well as the competencies of the participating lecturers. This report documents the pilot implementation of an international 3 ECTS Blended Intensive Programme (BIP) developed within the EU project and delivered for the first time at the Technical University of Applied Sciences Würzburg-Schweinfurt in Germany. The programme is based on a curriculum co-created in focus groups and informed by a previously developed methodology, clearly defined learning objectives and learning outcomes, as well as the competencies of the participating lecturers. The report provides an overview of the experiences gained during the BIP week in May 2025 and includes all relevant course descriptions, teaching materials, and learning content. It is intended to enable higher education institutions outside the project consortium to implement the BIP independently with individual adaptations. KW - Green Skills KW - Sustainable Development KW - Higher Education KW - GreenComps Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-63936 ER - TY - JOUR A1 - Volz, Stefan A1 - Storath, Martin A1 - Weinmann, Andreas T1 - Degrees-of-freedom penalized piecewise regression JF - Information and Inference: A Journal of the IMA N2 - Many popular piecewise regression models rely on minimizing a cost function on the model fit with a linear penalty on the number of segments. However, this penalty does not take into account varying complexities of the model functions on the segments potentially leading to overfitting when models with varying complexities, such as polynomials of different degrees, are used. In this work, we enhance on this approach by instead using a penalty on the sum of the degrees of freedom over all segments, called degrees-of-freedom penalized piecewise regression. We show that the solutions of the resulting minimization problem are unique for almost all input data in a least squares setting. We develop a fast algorithm that does not only compute a minimizer but also determines an optimal hyperparameter—in the sense of rolling cross validation with the one standard error rule—exactly. This eliminates manual hyperparameter selection. Our method supports optional user parameters for incorporating domain knowledge. We provide an open-source Python/Rust code for the piecewise polynomial least squares case which can be extended to further models. We demonstrate the practical utility through a simulation study and by applications to real data. A constrained variant of the proposed method gives state-of-the-art results in the Turing benchmark for unsupervised changepoint detection. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57846 SN - 2049-8772 VL - 14 IS - 1 PB - Oxford University Press ER - TY - JOUR A1 - Chaudhary, Renu A1 - Diethelm, Kai A1 - Hashemishahraki, Safoura T1 - On the separation of solutions to fractional differential equations of order α ∈ (1, 2) JF - Applied Numerical Mathematics N2 - Given a Caputo-type fractional differential equation with order between 1 and 2, we consider two distinct solutions to this equation subject to different sets of initial conditions. In this framework, we discuss nontrivial upper and lower bounds for the difference between these solutions. The main emphasis is on describing how such bounds are related to the differences of the associated initial values. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57338 VL - 203 SP - Article No. 38 ER - TY - JOUR A1 - Höfflin, Dennis A1 - Hartmann, Jürgen A1 - Rosilius, Maximilian A1 - Seitz, Philipp A1 - Schiffler, Andreas T1 - Opto-Thermal Investigation of Additively Manufactured Steel Samples as a Function of the Hatch Distance JF - Sensors N2 - Nowadays, additive manufacturing processes are becoming more and more appealing due to their production-oriented design guidelines, especially with regard to topology optimisation and minimal downstream production depth in contrast to conventional technologies. However, a scientific path in the areas of quality assurance, material and microstructural properties, intrinsic thermal permeability and dependent stress parameters inhibits enthusiasm for the potential degrees of freedom of the direct metal laser melting process (DMLS). Especially in quality assurance, post-processing destructive measuring methods are still predominantly necessary in order to evaluate the components adequately. The overall objective of these investigations is to gain process knowledge make reliable in situ statements about component quality and material properties based on the process parameters used and emission values measured. The knowledge will then be used to develop non-destructive tools for the quality management of additively manufactured components. To assess the effectiveness of the research design in relation to the objectives for further investigations, this pre-study evaluates the dependencies between the process parameters, process emission during manufacturing and resulting thermal diffusivity and the relative density of samples fabricated by DMLS. Therefore, the approach deals with additively built metal samples made on an EOS M290 apparatus with varying hatch distances while simultaneously detecting the process emission. Afterwards, the relative density of the samples is determined optically, and thermal diffusivity is measured using the laser flash method. As a result of this pre-study, all interactions of the within factors are presented. The process variable hatch distance indicates a strong influence on the resulting material properties, as an increase in the hatch distance from 0.11 mm to 1 mm leads to a drop in relative density of 57.4%. The associated thermal diffusivity also reveals a sharp decrease from 5.3 mm2/s to 1.3 mm2/s with growing hatch distances. The variability of the material properties can also be observed in the measured process emissions. However, as various factors overlap in the thermal radiation signal, no clear assignment is possible within the scope of this work. KW - additive manufacturing processes KW - material Y1 - 2021 U6 - https://doi.org/10.3390/s22010046 SN - 1424-8220 VL - 22 IS - 1 PB - MDPI ER - TY - JOUR A1 - Schiffler, Andreas A1 - Wehnert, Kira-Kristin A1 - Ochs, Dennis T1 - Einsatz einer maschinell gelernten Bildsegmentierung zur Pulverbettüberwachung im Metalldruck JF - FHWS Science Journal N2 - Der Schwerpunkt der folgenden Ausführungen ist auf eine schichtweise Erkennung von Abweichungen durch die automatisierte Analyse von Bilddaten aus pulverbettbasierten Metalldruckprozessen gelegt. Bei diesen Prozessen wird eine dünne Schicht im Bereich von 20 bis 100 μm aus pulverförmigem Metallpulver aufgetragen. Ein zweidimensionaler Querschnitt des gewünschten Bauteils wird dann entweder mit einer selektiven Wärmequelle aufgeschmolzen oder mit einem Bindemittel zusammengebunden. Anschließend wird das Substrat um die Höhe einer Pulverschicht abgesenkt und der Vorgang wiederholt, bis der Aufbau abgeschlossen ist. Nach dem Abschluss des Aufschmelzens einer Schicht wird ein Bild mittels einer Kamera im sichtbaren Wellenlängenbereich erstellt. Abbildung 1 zeigt zwei Beispiele solcher Bilder. Diese bilden die Eingangsgröße für die Erkennung von Abweichungen. Durch die gewählte Schichtdicke kann die Herstellung eines Bauteils mehrere tausend Bilder erzeugen. Die automatisierte und zeitnahe Auswertung ist daher Inhalt aktueller Forschungs- und Entwicklungsaktivitäten [1]. Nicht zuletzt da die notwendige Sensorik – eine Kamera – wirtschaftlich und robust einsetzbar ist. KW - bilddaten KW - bilderkennung KW - metalldruck Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20021 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 147 EP - 152 ER - TY - JOUR A1 - Miller, Eddi A1 - Barthelme, Christine A1 - Schiffler, Andreas A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Internationalisierung in Pandemiezeiten, technische Möglichkeiten, Lehr- und Forschungskonzepte mal anders gedacht JF - FHWS Science Journal N2 - Eines der zentralen strategischen Ziele unserer Hochschule ist die Internationalisierung, sowie der »internationalisation@home«. Als die weltweite Corona-Pandemie die Präsenzlehre und -forschung ebenso wie den internationalen Austausch von Studierenden und Forschenden zu Beginn 2020 quasi zum Erliegen brachte wurden die Rufe nach digitalen Angeboten im internationalen Bereich schnell laut. Vor diesem Hintergrund reagierte der »Deutsche Akademische Auslandsdienst (DAAD)« mit der kurzfristig ins Leben gerufenen Förderlinie »International Virtual Academic Collaboration« (IVAC), um internationale Hochschulkooperationen und weltweite Mobilität unter digitalen Vorzeichen strategisch zu gestalten und auszubauen [1]. KW - internationalisierung KW - covid KW - corona Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20035 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 143 EP - 146 ER - TY - JOUR A1 - Wehnert, Kira-Kristin A1 - Ochs, Dennis A1 - Schmitt, Jan A1 - Hartmann, Jürgen A1 - Schiffler, Andreas T1 - Reducing Lifecycle Costs due to Profile Scanning of the Powder Bed in Metal Printing JF - Procedia CIRP 98 N2 - First time right is one major goal in powder based 3D metal printing. Reaching this goal is driven by reducing life cycle costs for quality measures, to minimize scrap rate and to increase productivity under optimal resource efficiency. Therefore, monitoring the state of the powder bed for each printed layer is state of the art in selective laser melting. In the most modern approaches the quality monitoring is done by computer vision systems working with an interference on trained neural networks with images taken after exposure and after recoating. There are two drawbacks of this monitoring method: First, the sensor signals - the image of the powder bed - give no direct height information. Second, the application of this method needs to be trained and labeled with reference images for several cases. The novel approach presented in this paper uses a laser line scanner attached to the recoating machine. With this new concept, a direct threshold measure can be applied during the recoating process to detect deviations in height level without prior knowledge. The evaluation can be done online during recoating and feedback to the controller to monitor each individual layer. Hence, in case of deviations the location in the printing plane is an inherent measurement and will be used to decide which severity of error is reported. The signal is used to control the process, either by starting the recoating process again or stopping the printing process. With this approach, the sources of error for each layer can be evaluated with deep information to evaluate the cause of the error. This allows a reduction of failure in the future, which saves material costs, reduces running time of the machine life cycle phase in serial production and results in less rework for manufactured parts. Also a shorter throughput time per print job results, which means that the employee can spent more time to other print jobs and making efficient use of the employee’s work force. In summary, this novel approach will not only reduce material costs but also operating costs and thus optimize the entire life cycle cost structure. The paper presents a first feasibility and application of the described approach for test workpieces in comparison to conventional monitoring systems on an EOS M290 machine. Y1 - 2021 UR - 10.1016/j.procir.2021.01.175 VL - 98 SP - 684 EP - 689 PB - Elsevir ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Sauer, Christian A1 - Höfflin, Dennis A1 - Schiffler, Andreas T1 - Powder Bed Monitoring Using Semantic Image Segmentation to Detect Failures during 3D Metal Printing JF - Sensors N2 - Monitoring the metal Additive Manufacturing (AM) process is an important task within the scope of quality assurance. This article presents a method to gain insights into process quality by comparing the actual and target layers. Images of the powder bed were captured and segmented using an Xception–style neural network to predict the powder and part areas. The segmentation result of every layer is compared to the reference layer regarding the area, centroids, and normalized area difference of each part. To evaluate the method, a print job with three parts was chosen where one of them broke off and another one had thermal deformations. The calculated metrics are useful for detecting if a part is damaged or for identifying thermal distortions. The method introduced by this work can be used to monitor the metal AM process for quality assurance. Due to the limited camera resolutions and inconsistent lighting conditions, the approach has some limitations, which are discussed at the end. KW - additive manufacturing KW - metal printing KW - neural network KW - semantic segmentation KW - thermal distortion KW - in situ monitoring Y1 - 2023 U6 - https://doi.org/10.3390/s23094183 VL - 23 IS - 9 SP - 4183 EP - 4183 PB - MDPI ER - TY - CHAP A1 - Ziegler, Cedric C. A1 - Ising, Julia A1 - Dobhan, Alexander A1 - Storath, Martin T1 - Computer Vision in Reusable Container Management - Requirements, Conception, and Data Acquisition T2 - Logistik und Supply Chain Management N2 - In container management, the reuse of small load carriers is a business alternative to disposal carriers. Reusable container management is furthermore a solution to improve the environmental impact of the logistic industry. The sorting and stock management of small load carriers are today primarily manual work and have consequently a low level of automation. In order to increase the automation of returnable containers, it is crucial to establish a computer vision system that (i) classifies the containers and (ii) detects potential defects or stains. This paper provides an overview and a discussion of the applications that are already in use. Object detection is necessary for many actions in the container management business processes, such as inventory and stock management. Detection of defects on the small load carrier is required for scrapping the carriers to ensure a smooth process in any business process involving the carrier and to decide whether additional process steps, e.g., cleaning, are required. The literature review in this paper establishes the demand for computer vision detection and shows the project setup necessary to conduct research in this area. The comparison with other applications of defect and anomaly detection supports the applicability and shows the need for further research in this specific academic field. This leads to a project outline and the research provides the technical implementation of the detections in container management. Accordingly, the research provides a work- flow guide from data acquisition to a high-quality dataset of labeled anomalies of small load carriers. Y1 - 2023 SN - 9783863099411 U6 - https://doi.org/10.20378/irb-92408 SN - 2750-8277 SP - 107 EP - 122 PB - University of Bamberg Press ER - TY - JOUR A1 - Lehmann, Lisa A1 - Wilke, Winfried T1 - Neuer Studiengang Wasserstofftechnik BT - HS Würzburg-Schweinfurt holt H2-Experten ins Boot JF - HZwei - Das Magazin für Wasserstoff und Brennstoffzellen N2 - Die Fakultät Maschinenbau der Hochschule für angewandte Wissenschaften Würzburg-Schweinfurt (FHWS) greift das Thema Energiewende aus der Hightech Agenda Bayern auf und entwickelt einen neuen Studiengang Wasserstofftechnik. Ab Oktober 2021 soll es Studierenden dort möglich sein, sich vertieft mit Wasserstoff zu befassen, um sich später auch beruflich diesem bedeutenden Bestandteil der Energiewende zu widmen. Im neuen Studiengang stehen vor allem die Entwicklung von H2-Anlagen, deren laufender Betrieb sowie die entsprechende Anlagen- und Arbeitssicherheit im Mittelpunkt. Zur Studiengangentwicklung und -gestaltung sollen maßgeblich ein ständiger Austausch sowie spätere Projektkooperationen mit Unternehmen und deren Fachexperten beitragen. KW - Wasserstoff KW - Wasserstofftechnik KW - Maschinenbau KW - Wasserstoffanlagen Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-47878 SN - 1862-393X VL - 21. IS - 2 SP - 45 EP - 47 ER - TY - JOUR A1 - Kaupp, Tobias T1 - Lehre, Forschung und Transfer am Beispiel der Robotik BT - vom RoboCup@Work zur autonomen Warenkommissionierung JF - FHWS Science Journal N2 - Das IDEE ist mit vier Forschungsprofessoren besetzt, die durch eine Lehrentlastung Freiräume für den Auf- und Ausbau von interdisziplinären Forschungsaktivitäten nutzen können. Das Center Robotik (CERI) ist eines der Aufgabengebiete des IDEEs mit den beiden Schwerpunkten »Robotergestützte Arbeitsplätze der Zukunft« sowie »Intralogistik in der Smart Factory«. Dieser Artikel beschäftigt sich mit dem zweiten Schwerpunkt. Anhand der CERI Aktivitäten im Bereich der fahrerlosen Transportsysteme wird aufgezeigt, wie der »Dreiklang« Forschung, Lehre und Transfer in der Praxis umgesetzt wird und die drei Bestandteile sich gegenseitig befruchten können. KW - robotik Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20065 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 109 EP - 116 ER - TY - CHAP A1 - Fichtel, Lars A1 - Erbacher, Dominik A1 - Heller, Leon A1 - Frühwald, Alexander A1 - Hösch, Leonhard A1 - Bachmeir, Christian T1 - Analysis of Object Detection Datasets for Machine Learning with Small and Tiny Objects T2 - Proceedings of the Eleventh International Conference on Engineering Computational Technology N2 - Deep Learning models are trained to detect humans, cars, and other large objects which are centered in the images. The same models struggle with detecting small and tiny objects because of architecture design decisions that reduce the entropy of small and tiny objects during training. These small and tiny objects are essential for damage identification and maintenance including inspection and documentation of aeroplanes, constructions, offshore structures, and forests. Our work defines the terms tiny and small in context of deep learning models to evaluate possible approaches to resolve the issue of low accuracy in detecting these objects. We analyse the currently applied common datasets Common Objects in Context, ImageNet and Tiny Object Detection Challenge dataset. In addition we compare these datasets and present the differences in terms of object instance size. The COCO dataset, ImageNet dataset and TinyObjects dataset are analysed regarding size categorization and relative object size. The results show the large differences between the size ratios of the three chosen datasets, with ImageNet having by far the largest object instances, COCO being in the middle and TinyObjects having the smallest objects as its name would indicate. Since the objects themselves are larger in terms of total pixel width and height, they therefore make up a bigger percentage on the superordinate picture. Looking at the size categories of the COCO dataset and our extension of the tiny and very small category, the results confirm the size hierarchy of the datasets. With ImageNet having most of its objects in the large category, COCO respectively in the medium category and TinyObjects in the very small category. By taking these results into account, the reader is able to choose a fitting dataset for their tasks.We expect our analysis to help and improve future research in the area of small and tiny object detection. KW - machine learning KW - damage identification KW - object detection KW - inspection KW - tiny obejcts KW - small objects KW - maintenance KW - dataset Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-24895 ER - TY - JOUR A1 - Kaupp, Tobias A1 - Schmitt, Jan A1 - Hillenbrand, Andreas A1 - Kranz, Philipp T1 - Das hybride Team: ein Leitfaden zur systematischen Planung von assistierten, kollaborativen Mensch-Roboter-Arbeitsplätzen in der Montage JF - FHWS Science Journal N2 - Im Zuge der fortschreitenden Globalisierung und zunehmenden Digitalisierung der Arbeitswelt, ergeben sich gerade für kleine und mittelständische Unternehmen Herausforderungen im Bereich der Produktion und insbesondere in der Montage. Steigende Komplexität der Produkte, kürzer werdende Produktlebenszyklen bei kleinen Losgrößen mit hoher Variantenvielfalt und großem Wettbewerbsdruck zwingen Unternehmen bereits vorhandene Montagestrategien zu überarbeiten. Gerade bei komplexeren Baugruppen ist eine Hochautomatisierung der Montage in der Serienfertigung aufgrund der Produktstruktur nur schwer realisierbar und oftmals nicht wirtschaftlich. In der industriellen Produktion ist ein klarer Trend von der Massenproduktion hin zur »Massenspezialanfertigung« zu erkennen. Die Leistungsfähigkeit eines Industriebetriebes hängt entscheidend von den angewandten Produktionsverfahren, den eingesetzten Produktionsmitteln und der eingeführten Produktionsorganisation ab. Aber auch das Zusammenspiel von Mensch, Organisation und Technik trägt dazu bei Potenziale für den Erfolg eines Unternehmens auszuschöpfen. Aufgrund sich ständig ändernder Marktbedingungen und der kostengünstigen Herstellung von Produkten in Niedriglohnländern bei gleichzeitig steigendem Qualitätsniveau müssen Produktionsstrukturen ständig neu überdacht und weiterentwickelt werden. Die Montage ist im Vergleich zur klassischen Fertigung (wie z.B. Drehen, Fräsen oder Schleifen) ein eher niedrig automatisierter Bereich der industriellen Produktion, indem allerdings eine hohe Wertschöpfung am Produkt stattfindet. Die manuelle Montage ist daher auch zukünftig ein wichtiger Bestandteil der industriellen Produktion. Um am Markt bestehen zu können, müssen Unternehmen nach Möglichkeiten suchen, um manuelle Arbeit produktiver und damit kosteneffizienter zu gestalten ohne dabei Abstriche bei der Qualität hinzunehmen. Zur Unterstützung manueller Tätigkeiten sind in den vergangenen Jahren verschiedene Innovationen in den Fokus der Unternehmen gerückt. Das Ziel muss es sein, den (Montage-)Standort Deutschland durch innovative Konzepte wie kollaborative Mensch-Roboter-Arbeitsplätze zu sichern. KW - mensch-roboter KW - montage KW - arbeitsplatz Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19972 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 12 EP - 72 ER - TY - JOUR A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Involvierende Bildungskomponenten zur Ableitung von Anpassungskonzepten für (produzierende) Unternehmen im Projekt MainKlimaPLUS JF - FHWS Science Journal N2 - Es gilt, auf diverse Szenarien des Klimawandels vorbereitet zu sein, potenziell negativen Einflüssen vorzubeugen und Chancen (bspw. hinsichtlich Absatz- und Beschaffungsmarkt) zu ergreifen. Diese Ausprägungen regen dazu an, maßgeschneiderte Bildungskomponenten zu konzeptualisieren, um (produzierende) Unternehmen zukünftig sowohl in ihrer Verantwortungsfunktion zu sensibilisieren, als auch sie lernend zu befähigen, individuelle Klimaanpassungsmaßnahmen abzuleiten. KW - klima KW - klimawandel KW - mainklimaplus Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20050 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 101 EP - 108 ER - TY - JOUR A1 - Horn, Andreas A1 - Schmitt, Jan T1 - Roboterbasierte Koordinatenmesstechnik BT - wie präzise kann ein Roboter Bauteile vermessen? JF - FHWS Science Journal N2 - Das [...] Spannungsfeld aus Flexibilität, Bauraum, Kosten, Genauigkeit und automatisierter Messung soll in diesem Vorhaben mit der Realisierung einer größenangepassten, roboterbasierten Koordinatenmesstechnik begegnet werden. Als Herausforderung wird hierbei das Verfahren zur Optimierung der Genauigkeit (Kalibrierung) aus den gegebenen Randbedingungen (Kinematik, Steifigkeit) insbesondere des Roboters gesehen. KW - roboter KW - messen Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20077 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 93 EP - 100 ER - TY - GEN A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Planspiel MainKassandra BT - Klimaanpassung und Grundbegriffe spielerisch lernen N2 - Planspiel zur Klimaanpassung für Unternehmen, die mehr über die Wechselwirkungen des Klimawandels erfahren und zur strategischen und nachhaltigen Weiterentwicklung beitragen möchten. Mit einem spielerischen Ansatz werden direkte und indirekte Auswirkungen des Klimawandels simuliert und einzelne Teams aufgefordert, mit einem interaktiven Maßnahmenkatalog zielgerichtete Anpassungsstrategien zu entwickeln. Dabei gilt es Klimaereignisse und vorhandene Ressourcen zu beachten, denn der Spielsieg wird nur durch eine Balance zwischen ökonomischen und ökologischen Interessen erreicht. Die erworbenen Erfahrungen können dann direkt in die berufliche Praxis geführt und innerhalb von Arbeitsteams diskutiert werden. Beginnen Sie heute mit dem Umdenken und werden Sie kreativ, um Ihr Unternehmen vor den Folgen des Klimawandels zu schützen. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-22271 ER - TY - JOUR ED - Schmitt, Jan T1 - FHWS Science Journal (5, 2) BT - Sonderausgabe zur Forschung am Institut Digital Engineering N2 - Mit dieser Sonderausgabe des FHWS Science Journals möchten wir Sie [...] auf das Institut Digital Engineering (IDEE) aufmerksam machen sowie Einblicke in die aktuellen Forschungsarbeiten in ihrer Breite und Tiefe ermöglichen. Ganz besonders freut uns, dass die Entwicklung in Bezug auf die Teilnahme und den Erfolg bei öffentlichen Förderaufrufen des Landes und Bundes das Institut nach einer Startphase bereits sehr positiv zu bewerten ist. Dies zeigt sich an der Anzahl der eingeworbenen Projekte und den Drittmittelumsatz, der 2020 schon rund 1 Mio. € betrug und in 2021 auf 2 Mio € gesteigert werden konnte. Ausgangspunkt dieser Sonderausgabe ist die Präsentation eines Leitfadens zur Mensch-Roboter- Interaktion aus dem Projekt InKoMo der Bayerischen Forschungsstiftung heraus. Neben diesem Leitartikel finden sich weitere Beiträge, die den Stand der Forschungen am IDEE wiedergeben. Von 3D-Metalldruck bis Klimaanpassung wird aus vielen (nicht allen) Projekten berichtet und wir hoffen so Ihr Interesse an den Forschungsarbeiten an der Hochschule für angewandte Wissenschaften Würzburg Schweinfurt zu wecken. T3 - FHWS Science Journal - 5.2021, 2 KW - engineering KW - digital engineering KW - Mensch-Roboter-Interaktion KW - 3D-Druck KW - Additive Fertigung KW - Klimawandel KW - Klimaanpassung KW - augmented reality KW - Prozessoptimierung KW - Internationalisierung Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 (2021) IS - 2 CY - Würzburg ER - TY - JOUR A1 - Lehmann, Lisa A1 - Nowak, Elisabeth A1 - Engelhardt, Doris A1 - Müller, Detlef A1 - Wilke, Winfried T1 - Entwicklung eines Kompetenzfeststellungsverfahrens auf Basis eines Kompetenzprofils für den Bachelorstudiengang Maschinenbau JF - FHWS Science Journal N2 - Die Feststellung und Entwicklung von Kompetenzen ist ein diskutables und hoch komplexes Forschungsfeld. Wissenschaftlich beschäftigen sich insbesondere die Erziehungswissenschaften, die Pädagogik und die Psychologie sowie die disziplinenübergreifende empirische Bildungsforschung mit der Kompetenzerfassung, sowohl im sekundären als auch im tertiären Bildungssystem. In einem massiven Ausmaß steigt seit der Jahrtausendwende die Fokussierung auf Kompetenzen, insbesondere deren Feststellung und Weiterentwicklung. Die Bedeutung dieser Themenfelder reicht mittlerweile weit über den Bereich von Schulen und Hochschulen hinaus... Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19245 VL - 5 IS - 1 SP - 67 EP - 81 ER - TY - JOUR A1 - Bachmeir, Christian T1 - Mikrologistik der Zukunft mit dezentral organisierten boden- und luftgebundenen autonomen Fördereinheiten JF - FHWS Science Journal N2 - Geprägt durch den Einzug der Digitalisierung in Wirtschaft und Industrie sieht sich die Logistikbranche heute zunehmend damit konfrontiert, immer kleinere Stückmengen und Losgrößen transportieren zu müssen. Heutige, konventionelle Logistiksysteme sind für diese zukünftigen Anforderungen nicht ausgelegt. Deshalb bringt der Transport kleiner Losgrößen hohe Kosten mit sich. Darüber hinaus sind heutige Logistiksysteme nicht flexibel genug. Auch die praktizierte Ansammlung von kleinen Losgrößen zu größeren Einheiten erfüllt die Anforderungen nicht. Der Warentransport wird aus Sicht des steigenden Anspruchs an den Zeitfaktor teuer. Darüber hinaus entstehen zusätzliche Lagerkosten. Neue Technologien wie fahrerlose Transportsysteme und Transportdrohnen können in ihrer aktuellen Entwicklung dem Bedarf der Mikromobilität nur in stark abgegrenzten Bereichen gerecht werden und somit ihr Potenzial noch nicht ganzheitlich entfalten. Im Projekt wird die kollaborative Zusammenarbeit verschiedener Transporteinheiten wie fahrerlose Transportsysteme (FTS), Multicopter- und Flächendrohnen aufbauend auf einem KI-Service entwickelt, was einem heterogenen Netzwerk die Überwindung der einzelnen, technologischen Systemgrenzen und zweckdienlichen Einsatz ermöglicht. Die Auslegung von logistischen Systemen erfolgt immer nach dem Prinzip des minimalsten Aufwandes. Das Projekt FlowPro entwickelt ein auf KI-Verfahren basierendes Logistiknetzwerk, welches sich selbstständig organisiert und in Industrieparks die Intralogistik sowie darüber hinaus unternehmensübergreifend auf dem Land- und Luftweg die Mikromobilität von Waren ermöglicht und optimiert. KW - mikrologistik KW - autonom Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-20086 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 117 EP - 124 ER - TY - JOUR A1 - Bachmeir, Christian T1 - Das Projekt KI-Inspektionsdrohne JF - FHWS Science Journal N2 - Das Verbundvorhaben KI-Inspektionsdrohne, im Rahmen des Luftfahrtforschungsprogramms V [1], hat als Ziel Maintenance-, Repair- und Overhaul-(MRO-)Prozesse in der Luftfahrtindustrie zu beschleunigen, und damit die MRO-Industrie noch wettbewerbsfähiger zu machen. Im Vorhaben wird ein sicheres System zur Schadensdetektion und -bewertung von äußeren Flugzeugstrukturen unter Berücksichtigung aktueller Instandhaltungs-Anforderungen der Luftfahrtbranche entwickelt. Der entwickelte Prototyp integriert vernetzte UAV (Unmanned Aerial Vehicles – Unbemannte Flugsysteme), autonome Navigation und Schadensaufnahme und KI-gestützte Auswertung und stellt ein Decision Support System zur Verfügung bzw. fällt eigenständig Entscheidungen. Forschungsschwerpunkt der FHWS ist, bzw. Forschungsschwerpunkte sind industriespezifische Ende-zu-Ende-Security, KI, Safety, und insbesondere die Absicherung der mobilen, mit Cloud oder Edge verbundenen Einheiten gegen Cyberattacken. KW - drohne KW - künstliche intelligenz Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19994 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-19389 SN - 2196-6095 VL - 5 IS - 2 SP - 131 EP - 134 ER - TY - JOUR A1 - Fischer, Sophie A1 - Göhlich, Michael A1 - Schmitt, Sophie T1 - Adapting to climate change through play? Didactically effective elements of a business simulation game JF - Frontiers in Education N2 - Introduction: The negative consequences of climate change are widespread and have a global impact. An industrialized region of Germany must adapt to the effects of climate change and comply with political regulations. Previous studies indicate that economic actors who are not directly affected by climate change approach climate change mitigation and adaptation primarily based on legal requirements and often feel discouraged by the absence of data-based reports. Addressing this challenge, game-based learning emerges as a promising pathway. Methods: To examine game-based learning’s applicability and potential for climate adaptation, we developed a business simulation game, simultaneously identifying didactically effective elements for managers who would participate in it. Using expert interviews and focus groups, we conducted a qualitative study with three HR developers from larger companies and nine managers and founders of startups to develop a business simulation game on climate adaptation. Based on the Grounded Theory methodology, theoretical coding was used to analyze the qualitative data. Results: The derived core categories indicate that personnel development in companies is evolving in response to economic changes. Individual resources such as motivation (especially for managers), personnel and time play a crucial role in establishing a business game as an educational offering. The identified game elements can also be used theoretically and practically in the development of other educational games. Discussion: We discussed common human resource development measures in companies and compared them with more innovative approaches such as a simulation game. The study underscores the importance of innovative approaches, such as game-based learning, in fostering climate adaptation efforts among economic actors. By integrating theoretical insights with practical applications, our findings provide valuable guidance for the development of educational games aimed at addressing complex challenges like climate change. Further research and implementation of such approaches are essential for promoting proactive climate adaptation strategies within industrialized regions and beyond. KW - Climate adaptation KW - Game-based learning KW - Serious game KW - Human resource development KW - Business game KW - Corporate social responsibility Y1 - 2024 U6 - https://doi.org/10.3389/feduc.2024.1303107 VL - 2024 IS - 9 SP - 01 EP - 17 ER - TY - CHAP A1 - Selig, Tim A1 - Bauer, Patrick A1 - Frikel, Jürgen A1 - März, Thomas A1 - Storath, Martin A1 - Weinmann, Andreas T1 - Two-stage Approach for Low-dose and Sparse-angle CT Reconstruction using Backprojection T2 - Informatik aktuell Y1 - 2025 SN - 9783658474218 U6 - https://doi.org/10.1007/978-3-658-47422-5_67 SN - 1431-472X SP - 286 EP - 291 PB - Springer Fachmedien Wiesbaden CY - Wiesbaden ER - TY - CHAP A1 - Storath, Martin A1 - Weinmann, Andreas T1 - Solving higher-order Mumford-Shah models T2 - INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: ICNAAM2022 Y1 - 2024 U6 - https://doi.org/10.1063/5.0210598 SN - 0094-243X PB - AIP Publishing ER - TY - CHAP A1 - Hofmann, Alexander A1 - Heusinger, Marc T1 - Neues Sensorkonzept für magnetostriktive Kraftmessung in kostenorientierten Anwendungen T2 - 22. GMA/ITG-Fachtagung Sensoren und Messsysteme 2024 N2 - Der Beitrag stellt ein neuartiges, kostenorientiertes Konzept zur Kraftmessung basierend auf dem magnetostriktiven Wandlungsprinzip vor. Kernelement ist ein scheibenförmiger Sensor, der remanent magnetisiert ist und unter Last eine äußerlich durch Sekundärsensoren messbare Magnetfeldänderung erzeugt. Die magnetischen Eigenschaften eines marktüblichen Kaltarbeitsstahls werden hinsichtlich der sensorischen Eignung für dieses Konzept diskutiert und erste Ergebnisse bezüglich der Korrelation von Sekundärsensorsignalen zur aufgebrachten Last dargestellt. Y1 - 2024 SN - 978-3-910600-01-0 U6 - https://doi.org/10.5162/sensoren2024/A2.1 ER - TY - JOUR A1 - Storath, Martin A1 - Weinmann, Andreas T1 - Smoothing Splines for Discontinuous Signals JF - Journal of Computational and Graphical Statistics Y1 - 2023 U6 - https://doi.org/10.1080/10618600.2023.2262000 SN - 1061-8600 VL - 33 IS - 2 SP - 651 EP - 664 PB - Informa UK Limited ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian T1 - A Series Production Data Set for Five-Axis CNC Milling JF - Data N2 - The described data set contains features from the machine control of a five-axis milling machine. The features were recorded during thirteen series productions. Each series production includes a changeover process in which the machine was set up for the production of a different product. In addition to the timestamps and the twenty recorded features derived from Numerical Control (NC) variables, the data set also contains labels for the different production phases. For this purpose, up to 23 phases were assigned, which are based on a generalized milling process. The data set consists of thirteen .csv files, each representing a series production. The data set was recorded in a production company in the contract manufacturing sector for components with real series orders in ongoing industrial production. Y1 - 2024 U6 - https://doi.org/10.3390/data9050066 SN - 2306-5729 VL - 9 IS - 5 PB - MDPI ER - TY - JOUR A1 - George Biju, Vinai A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian T1 - Assessing the Influence of Sensor-Induced Noise on Machine-Learning-Based Changeover Detection in CNC Machines JF - Sensors Y1 - 2024 UR - https://doi.org/10.3390/s24020330 VL - 2024 ER - TY - JOUR A1 - Hofmann, Alexander A1 - Heusinger, Marc T1 - Cost-oriented sensor concept for magnetostrictive force measurement and its material requirements JF - Journal of Sensors and Sensor Systems N2 - Ferromagnetic materials change their magnetic properties under load, enabling the implementation of a force sensor. The magnetic field emerging from such a sensor can be measured by secondary sensors to approximate the load acting on the sensor. A test setup simulating a potential application environment is described and its measurement results are presented. Furthermore, relevant magnetic material properties of an exemplarily chosen cold working steel are discussed. Y1 - 2025 U6 - https://doi.org/10.5194/jsss-14-47-2025 VL - 14 IS - 1 SP - 47 EP - 54 ER - TY - CHAP A1 - Lehmann, Lisa A1 - Engelhardt, Doris A1 - Wilke, Winfried ED - Lehmann, Lisa ED - Engelhardt, Doris ED - Winfried, Wilke T1 - Entwicklung eines digitalen Instruments zur Feststellung relevanter Kompetenzen im Maschinenbau BT - Vom ideellen Kompetenzprofil zur praxistauglichen Messung T2 - Kompetenzen für die digitale Transformation 2020 KW - Kompetenz KW - Maschinenbau Y1 - 2021 SN - 978-3-662-62865-2 SP - 107 EP - 123 PB - Springer Vieweg CY - Berlin ER - TY - BOOK A1 - Lehmann, Lisa A1 - Engelhardt, Doris A1 - Wilke, Winfried ED - Lehmann, Lisa ED - Engelhardt, Doris ED - Wilke, Winfried T1 - Kompetenzen für die digitale Transformation 2020 BT - Digitalisierung der Arbeit - Kompetenzen - Nachhaltigkeit KW - Digitalisierung KW - Digitalkompetenzen KW - Arbeit Y1 - 2021 SN - 978-3-662-62865-2 PB - Springer Vieweg CY - Berlin ER - TY - GEN A1 - Schmidt, Dirk A1 - Schmit, Jan A1 - Hülsmann, Dennis T1 - Antriebseinrichtung mit einer Rotationswelle, einem Rotor und einer Wuchtscheibe [Patent, DE102017122466A1] Y1 - 2019 ER -