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 - 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 - 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 - 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 - Stühm, Kai A1 - Tornow, Alexander A1 - Schmitt, Jan A1 - Grunau, Leonard A1 - Dietrich, Franz A1 - Dröder, Klaus T1 - A novel gripper for battery electrodes based on the Bernoulli-principle with integrated exhaust air compensation JF - Procedia CIRP Y1 - 2014 VL - 23 SP - 161 EP - 164 ER - TY - CHAP A1 - Schmitt, Jan A1 - Inkermann, David A1 - Stechert, Carsten A1 - Raatz, Annika A1 - Vietor, Thomas T1 - Requirement oriented reconfiguration of parallel robotic systems T2 - Robotic Systems-Applications, Control and Programming Y1 - 2012 SP - 387 EP - 410 ER - TY - JOUR A1 - Jan Schmitt, Kai Stühm, Annika Raatz, Klaus Dröder T1 - Simulating production effects on lithium-ion batteries JF - AABC Y1 - 2013 ER - TY - CHAP A1 - Cerdas, Felipe A1 - Gerbers, Roman A1 - Andrew, Stefan A1 - Schmitt, Jan A1 - Dietrich, Franz A1 - Thiede, Sebastian A1 - Dröder, Klaus A1 - Herrmann, Christoph T1 - Disassembly planning and assessment of automation potentials for lithium-ion batteries T2 - Recycling of Lithium-Ion Batteries: The LithoRec Way Y1 - 2018 SP - 83 EP - 97 ER - TY - JOUR A1 - Herrmann, Christoph A1 - Raatz, Annika A1 - Andrew, Stefan A1 - Schmitt, Jan T1 - Scenario-based development of disassembly systems for automotive lithium ion battery systems JF - Advanced Materials Research Y1 - 2014 VL - 907 SP - 391 EP - 401 ER - TY - JOUR A1 - Schmitt, Jan A1 - Raatz, Annika A1 - Dietrich, Franz A1 - Dröder, Klaus A1 - Hesselbach, Jürgen T1 - Process and performance optimization by selective assembly of battery electrodes JF - CIRP Annals Y1 - 2014 VL - 63 IS - 1 SP - 9 EP - 12 ER - TY - JOUR A1 - Schilling, Antje A1 - Schmitt, Jan A1 - Dietrich, Franz A1 - Dröder, Klaus T1 - Analyzing Bending Stresses on Lithium-Ion Battery Cathodes induced by the Assembly Process JF - Energy Technology Y1 - 2016 VL - 4 IS - 12 SP - 1502 EP - 1508 ER - TY - JOUR A1 - Schmitt, Jan A1 - Raatz, Annika T1 - Failure Mode Based Design and Optimization of the Electrode Packaging Process for Large Scale Battery Cells JF - Advanced Materials Research Y1 - 2014 VL - 907 SP - 309 EP - 319 ER - TY - THES A1 - Schmitt, Jan T1 - Untersuchungen zum Herstellungsprozess des Elektrode-Separator-Verbunds für Lithium-Ionen Batteriezellen Y1 - 2015 ER - TY - JOUR A1 - Schmitt, Jan A1 - Seitz, Philipp A1 - Scherdel, Christian A1 - Reichenauer, Gudrun T1 - Machine Learning in the development of Si-based anodes using Small-Angle X-ray Scattering for structural property analysis JF - Computational Materials Science N2 - Material development processes are highly iterative and driven by the experience and intuition of the researcher. This can lead to time consuming procedures. Data-driven approaches such as Machine Learning can support decision processes with trained and validated models to predict certain output parameter. In a multifaceted process chain of material synthesis of electrochemical materials and their characterization, Machine Learning has a huge potential to shorten development processes. Based on this, the contribution presents a novel approach to utilize data derived from Small-Angle X-ray Scattering (SAXS) of SiO_2 matrix materials for battery anodes with Neural Networks. Here, we use SAXS as an intermediate, high-throughput method to characterize sol–gel based porous materials. A multi-step-method is presented where a Feed Forward Net is connected to a pretrained autoencoder to reliably map parameters of the material synthesis to the SAXS curve of the resulting material. In addition, a direct comparison shows that the prediction error of Neural Networks can be greatly reduced by training each output variable with a separate independent Neural Network. KW - machine learning KW - neural network KW - autoencoder Y1 - 2023 UR - https://doi.org/10.1016/j.commatsci.2022.111984 SN - 1879-0801 N1 - Link zum Datensatz: https://gitlab.vlab.fm.fhws.de/philipp.seitz/machinelearningandsaxs VL - 218 ER - TY - CHAP A1 - Schmitt, Jan A1 - Bruhn, Matthias A1 - Raatz, Annika T1 - Comparative analysis of pneumatic grippers for handling operations of crystalline solar cells T2 - Proceedings of the IASTED Asian Conference on Power and Energy Systems, AsiaPES Y1 - 2012 SP - 386 EP - 392 ER - TY - CHAP A1 - Herrmann, Christoph A1 - Raatz, Annika A1 - Mennenga, Mark A1 - Schmitt, Jan A1 - Andrew, Stefan T1 - Assessment of automation potentials for the disassembly of automotive lithium ion battery systems T2 - Leveraging Technology for a Sustainable World: Proceedings of the 19th CIRP Conference on Life Cycle Engineering, University of California at Berkeley, Berkeley, USA, May 23-25, 2012 Y1 - 2012 SP - 149 EP - 154 ER - TY - CHAP A1 - Schmitt, Jan A1 - Treuer, F A1 - Dietrich, F A1 - Dröder, K A1 - Heins, T-P A1 - Schröder, U A1 - Westerhoff, U A1 - Kurrat, M A1 - Raatz, A T1 - Coupled mechanical and electrochemical characterization method for battery materials T2 - 2014 IEEE Conference on Energy Conversion (CENCON) Y1 - 2014 SP - 395 EP - 400 ER - TY - CHAP A1 - Schreiber, Frank A1 - Sklyarenko, Yevgen A1 - Schlüter, Kathrin A1 - Schmitt, Jan A1 - Rost, Sven A1 - Raatz, Annika A1 - Schumacher, Walter T1 - Tracking control with hysteresis compensation for manipulator segments driven by pneumatic artificial muscles T2 - 2011 IEEE international conference on robotics and biomimetics Y1 - 2011 SP - 2750 EP - 2755 ER - TY - CHAP A1 - Schmitt, Jan A1 - Haupt, Hannes A1 - Kurrat, Michael A1 - Raatz, Annika T1 - Disassembly automation for lithium-ion battery systems using a flexible gripper T2 - 2011 15th International Conference on Advanced Robotics (ICAR) Y1 - 2011 SP - 291 EP - 297 ER - TY - CHAP A1 - Schmitt, Jan A1 - Last, Philipp A1 - Lochte, Christian A1 - Raatz, Annika A1 - Hesselbach, Jürgen T1 - TRoBS - a biological inspired robot T2 - 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO) Y1 - 2009 SP - 51 EP - 56 ER - TY - CHAP A1 - Schmitt, Jan A1 - Grabert, Frank A1 - Raatz, Annika T1 - Design of a hyper-flexible assembly robot using artificial muscles T2 - 2010 IEEE International Conference on Robotics and Biomimetics Y1 - 2010 SP - 897 EP - 902 ER - TY - JOUR A1 - Schmitt, Jan A1 - Posselt, G A1 - Dietrich, F A1 - Thiede, S A1 - Raatz, A A1 - Herrmann, C A1 - Dröder, K T1 - Technical performance and energy intensity of the electrode-separator composite manufacturing process JF - Procedia CIRP Y1 - 2015 U6 - https://doi.org/10.1016/j.procir.2015.02.016 VL - 29 SP - 269 EP - 274 ER - TY - JOUR A1 - Schmitt, Jan A1 - Inkermann, D A1 - Raatz, A A1 - Hesselbach, J A1 - Vietor, T T1 - Dynamic reconfiguration of parallel mechanisms JF - New trends in mechanism science: analysis and design Y1 - 2010 SP - 557 EP - 565 ER - TY - JOUR A1 - Schmitt, Jan A1 - Engelmann, Bastian A1 - Manghisi, Vito Modesto A1 - Wilhelm, Markus A1 - Uva, Antonello A1 - Fiorentino, Michele T1 - Towards gestured-based technologies for human-centred smart factories JF - International Journal of Computer Integrated Manufacturing N2 - Despite the increasing degree of automation in industry, manual or semi-automated are commonly and inevitable for complex assembly tasks. The transformation to smart processes in manufacturing leads to a higher deployment of data-driven approaches to support the worker. Upcoming technologies in this context are oftentimes based on the gesture-recognition, − monitoring or – control. This contribution systematically reviews gesture or motion capturing technologies and the utilization of gesture data in the ergonomic assessment, gesture-based robot control strategies as well as the identification of COVID-19 symptoms. Subsequently, two applications are presented in detail. First, a holistic human-centric optimization method for line-balancing using a novel indicator – ErgoTakt – derived by motion capturing. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and the takt-time balancing. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-score and the cycle time of each assembly workstation with respect to the workers’ ability. The second application is gesture-based robot-control. A cloud-based approach utilizing a generally accessible hand-tracking model embedded in a low-code IoT programming environment is shown. KW - gesture-based monitoring KW - gesture-based control KW - manufacturing Y1 - 2023 UR - https://doi.org/10.1080/0951192X.2022.2121424 SN - 1362-3052 VL - 36 IS - 1 SP - 110 EP - 127 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 - 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 - 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 - 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 - 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 - GEN A1 - Jan, Schmitt 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 -