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 - 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 - Erbe, Karin A1 - Brandmeier, Melanie A1 - Schmitt, Michael A1 - Donbauer, Andreas A1 - Liebscher, Jan-Andreas A1 - Kolbe, Thomas ED - Kersten, Thomas P. ED - Tilly, Nora T1 - Detektion von Fahrradständern in Luftbildern mittels Deep Learning T2 - 42. Wissenschaftlich-Technische Jahrestagung der DGPF. 5.-6. Oktober 2022 in Dresden Y1 - 2022 U6 - https://doi.org/10.24407/KXP:1795622415 SN - 0942-2870 VL - 30 SP - 27 EP - 39 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 - 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 -