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 - 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 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 - 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 - 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 - 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 - 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 - 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 - 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. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56030 VL - 14 IS - 2 PB - MDPI 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 - 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 - 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 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 - 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 - 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 - 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/https://10.20378/irb-92408 SN - 2750-8277 SP - 107 EP - 122 PB - University of Bamberg Press ER -