@article{KieflFischerSchmitt, author = {Kiefl, Sophia and Fischer, Sophie and Schmitt, Jan}, title = {Self-employed and stressed out? The impact of stress and stress management on entrepreneurs' mental health and performance}, series = {Frontiers in Psychology}, volume = {15}, journal = {Frontiers in Psychology}, publisher = {Frontiers}, doi = {10.3389/fpsyg.2024.1365489}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-56040}, pages = {15}, language = {en} } @article{OchsWehnertHartmannetal., author = {Ochs, Dennis and Wehnert, Kira-Kristin and Hartmann, J{\"u}rgen and Schiffler, Andreas and Schmitt, Jan}, title = {Sustainable Aspects of a Metal Printing Process Chain with Laser Powder Bed Fusion (LPBF)}, series = {Procedia CIRP}, volume = {98}, journal = {Procedia CIRP}, publisher = {Elsevir}, pages = {613 -- 618}, abstract = {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.}, language = {en} } @inproceedings{RosiliusWirsingvonEitzenetal., author = {Rosilius, Maximilian and Wirsing, Benedikt and von Eitzen, Ingo and Wilhelm, Markus and Schmitt, Jan and Engelmann, Bastian and Br{\"a}utigam, Volker}, title = {Evaluation of Visual Requirements and Software-Design for Immersive Visibility in Industrial Applications}, series = {2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, booktitle = {2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, pages = {234 -- 239}, abstract = {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.}, language = {en} } @article{FischerRosiliusSchmittetal., author = {Fischer, Sophie and Rosilius, Maximilian and Schmitt, Jan and Br{\"a}utigam, Volker}, title = {A brief review of our agile teaching formats in entrepreneurship education}, series = {Sustainability}, volume = {14}, journal = {Sustainability}, number = {1}, doi = {https://doi.org/10.3390/su14010251}, pages = {251 -- 251}, abstract = {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.}, language = {en} } @inproceedings{MeyerPechtlBremeretal., author = {Meyer, Maximilian and Pechtl, Lin and Bremer, Peik and Schmitt, Jan}, title = {Towards position-based technologies for digitized process management on the shop floor}, series = {Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, W{\"u}rzburg}, booktitle = {Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, W{\"u}rzburg}, pages = {232 -- 241}, abstract = {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.}, language = {en} } @incollection{MillerSchmittKauppetal., author = {Miller, Eddi and Schmitt, Anna-Maria and Kaupp, Tobias and Batres, Rafael and Schiffler, Andreas and Schmitt, Jan}, title = {A Peak Shaving Approach in Manufacturing Combining Machine Learning and Job Shop Scheduling}, series = {Lecture Notes in Mechanical Engineering}, booktitle = {Lecture Notes in Mechanical Engineering}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031774287}, issn = {2195-4356}, doi = {10.1007/978-3-031-77429-4_59}, pages = {535 -- 543}, abstract = {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.}, language = {en} } @article{EngelmannSchmittMilleretal., author = {Engelmann, Bastian and Schmitt, Simon and Miller, Eddi and Br{\"a}utigam, Volker and Schmitt, Jan}, title = {Advances in machine learning detecting changeover processes in cyber physical production systems}, series = {Journal of Manufacturing and Materials Processing}, volume = {4}, journal = {Journal of Manufacturing and Materials Processing}, number = {4}, pages = {108 -- 108}, abstract = {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.}, language = {en} } @article{NeuberSchmittEngelmannetal., author = {Neuber, Till and Schmitt, Anna-Maria and Engelmann, Bastian and Schmitt, Jan}, title = {Evaluation of the Influence of Machine Tools on the Accuracy of Indoor Positioning Systems}, series = {Sensors}, volume = {22}, journal = {Sensors}, number = {24}, pages = {10015 -- 10015}, language = {en} } @inproceedings{SchmittMillerSchiffleretal., author = {Schmitt, Anna-Maria and Miller, Eddi and Schiffler, Andreas and Schmitt, Jan}, title = {Energy Prediction for CNC Machines Using G-Code Evaluation, Machine Learning and a Real-World Training Part}, series = {2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE)}, booktitle = {2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE)}, doi = {10.1109/ICMRE64970.2025.10976308}, pages = {340-347}, language = {en} } @article{FischerSchmitt, author = {Fischer, Sophie and Schmitt, Jan}, title = {Regionalstudie Auswirkungen des globalen Klimawandels in Mainfranken}, doi = {10.57714/fpkt-vt47}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-19959}, pages = {176}, abstract = {Mainfr{\"a}nkische Unternehmen und Handwerksbetriebe stehen aufgrund expandierender Wertsch{\"o}pfungsketten in einem starken Abh{\"a}ngigkeitsverh{\"a}ltnis zu ihren global verteilten Zulieferern. Dadurch ist die Wertsch{\"o}pfungskette anf{\"a}llig f{\"u}r externe St{\"o}rungen, die unter anderem durch den Klimawandel ausgel{\"o}st werden. Zugleich sind die Erw{\"a}rmungsraten in der bayerischen Region derzeit deutlich h{\"o}her als im bundesweiten Durchschnitt. Die Entwicklung von strategischen Maßnahmen zur Klimaanpassung ist demnach unerl{\"a}sslich, um die unternehmensspezifischen Risiken des Klimawandels zu antizipieren und zu minimieren. Die Klimaanpassung ist in vielen kommunalen, wirtschaftlichen und gesellschaftlichen Bereichen eine der gr{\"o}ßten Herausforderungen der Gegenwart. Die vorliegende Regionalstudie beabsichtigt daher eine Abgrenzung der Verh{\"a}ltnisse und Wechselwirkungen des globalen Klimawandels, der Auswirkungen in der bayerischen Region Mainfranken sowie der aufkommenden Ver{\"a}nderungsbedarfe f{\"u}r gesellschaftliche, politische und wirtschaftliche Akteure. Ein umfassender grundlagentheoretischer {\"U}berblick dient zun{\"a}chst der Einordnung wichtiger Ansatzpunkte aus politischer Perspektive und stellt Angebote f{\"u}r Wirtschaftsakteure dar. Ferner werden die wirtschaftlichen Auspr{\"a}gungen nach Handwerksbetrieben und Unternehmen differenziert, sowie deren Rolle f{\"u}r 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 Erh{\"o}hung der organisationalen Klimaresilienz beitragen. Um als wirtschaftliche Organisationen einen ad{\"a}quaten Umgang mit dem Klimawandel zu finden, sind bspw. zun{\"a}chst F{\"u}hrungskr{\"a}fte 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 klimasch{\"a}dlicher Treibhausgasemissionen, die Klimaanpassung ein unverzichtbarer Aspekt ist, um die wirtschaftliche Effizienz zu erhalten und sogar zu erh{\"o}hen, indem die ver{\"a}nderten Anforderungen als Entwicklungschancen wahrgenommen werden.}, language = {de} } @article{EngelmannSchmittTheilackeretal., author = {Engelmann, Bastian and Schmitt, Anna-Maria and Theilacker, Lukas and Schmitt, Jan}, title = {Implications from Legacy Device Environments on the Conceptional Design of Machine Learning Models in Manufacturing}, series = {Journal of Manufacturing and Materials Processing}, volume = {2024}, journal = {Journal of Manufacturing and Materials Processing}, language = {en} } @article{EngelmannSchmittHeusingeretal., author = {Engelmann, Bastian and Schmitt, Anna-Maria and Heusinger, Moritz and Borysenko, Vladyslav and Niedner, Niklas and Schmitt, Jan}, title = {Detecting Changeover Events on Manufacturing Machines with Machine Learning and NC data}, series = {Applied Artificial Intelligence}, journal = {Applied Artificial Intelligence}, publisher = {Taylor \& Francis}, language = {en} } @article{SchmittMillerEngelmannetal., author = {Schmitt, Anna-Maria and Miller, Eddi and Engelmann, Bastian and Batres, Rafael and Schmitt, Jan}, title = {G-code evaluation in CNC milling to predict energy consumption through Machine Learning}, series = {Advances in Industrial and Manufacturing Engineering}, volume = {2024}, journal = {Advances in Industrial and Manufacturing Engineering}, number = {8}, abstract = {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.}, language = {en} } @inproceedings{HartmannDzemkoEngelmannetal., author = {Hartmann, J{\"u}rgen and Dzemko, Mikita and Engelmann, Bastian and Schmitt, Jan}, title = {Toward Shifted Production Strategies Through Additive Manufacturing: A Technology and Market Review for Changing Value Chains}, series = {7th CIRP Global Web Conference (86)}, volume = {86}, booktitle = {7th CIRP Global Web Conference (86)}, doi = {10.1016/j.procir.2020.01.029}, pages = {228 -- 233}, abstract = {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 …}, language = {en} } @inproceedings{MillerSchmittKauppetal., author = {Miller, Eddi and Schmitt, Anna-Maria and Kaupp, Tobias and Schiffler, Andreas and Schmitt, Jan}, title = {Deep Reinforcement Learning for Adaptive Job Shop Scheduling in Robotic Cells: Handling Disruptions Effectively}, series = {2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE)}, booktitle = {2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE)}, language = {en} } @inproceedings{SchmittAntonovSchmittetal., author = {Schmitt, Anna-Maria and Antonov, Anna and Schmitt, Jan and Engelmann, Bastian}, title = {Classification of Production Process Phases with Multivariate Time Series Techniques}, series = {2024 22nd International Conference on Research and Education in Mechatronics (REM)}, booktitle = {2024 22nd International Conference on Research and Education in Mechatronics (REM)}, doi = {10.1109/REM63063.2024.10735481}, language = {en} } @article{FischerKeuppPaethetal., author = {Fischer, Sophie and Keupp, Luzia and Paeth, Heiko and G{\"o}hlich, Michael and Schmitt, Jan}, title = {Climate adaptation as organizational learning: a grounded theory study on manufacturing companies in a Bavarian Region}, series = {Education Sciences}, volume = {12}, journal = {Education Sciences}, number = {1}, pages = {22 -- 22}, language = {en} } @article{FischerGoehlichSchmitt, author = {Fischer, Sophie and G{\"o}hlich, Michael and Schmitt, Jan}, title = {Interrelationships of climate adaptation and organizational learning: Development of a measurement model}, series = {Journal of Pedagogical Research}, volume = {6}, journal = {Journal of Pedagogical Research}, number = {5}, pages = {130 -- 152}, language = {en} } @incollection{Schmitt, author = {Schmitt, Jan}, title = {Ein integriertes Vorgehensmodell zur Implementierung eines nachhaltigen Wertstoffmanagements}, series = {CSR in S{\"u}ddeutschland: Unternehmerischer Erfolg und Nachhaltigkeit im Einklang}, booktitle = {CSR in S{\"u}ddeutschland: Unternehmerischer Erfolg und Nachhaltigkeit im Einklang}, pages = {93 -- 105}, language = {de} } @inproceedings{BremerTsai, author = {Bremer, Peik and Tsai, Kune-muh}, title = {Smartness in picker-to-parts order picking: a socio-technical systems theory perspective}, publisher = {International Symposium on Logistics "Managing Supply Chains during Geopolitical Turbulence", Enschede, 9.-12. Juli}, pages = {11}, abstract = {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.}, language = {en} } @incollection{EngelmannSchmitt, author = {Engelmann, Bastian and Schmitt, Jan}, title = {Industrie 4.0 f{\"u}r Studierende des Wirtschaftsingenieurwesens}, series = {Kompetenzen f{\"u}r die digitale Transformation 2020: Digitalisierung der Arbeit-Kompetenzen-Nachhaltigkeit 1. Digitalkompetenz-Tagung}, booktitle = {Kompetenzen f{\"u}r die digitale Transformation 2020: Digitalisierung der Arbeit-Kompetenzen-Nachhaltigkeit 1. Digitalkompetenz-Tagung}, pages = {265 -- 273}, language = {de} } @article{WilhelmManghisiUvaetal., author = {Wilhelm, Markus and Manghisi, Vito Modesto and Uva, Antonello and Fiorentino, Michele and Br{\"a}utigam, Volker and Engelmann, Bastian and Schmitt, Jan}, title = {ErgoTakt: A novel approach of human-centered balancing of manual assembly lines}, series = {Procedia CIRP}, volume = {97}, journal = {Procedia CIRP}, doi = {https://doi.org/10.1016/j.procir.2020.05.250}, pages = {354 -- 360}, abstract = {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.}, language = {en} } @inproceedings{SchmittHillenbrandKranzetal., author = {Schmitt, Jan and Hillenbrand, Andreas and Kranz, Philipp and Kaupp, Tobias}, title = {Assisted human-robot-interaction for industrial assembly: Application of spatial augmented reality (sar) for collaborative assembly tasks}, series = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction}, booktitle = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction}, pages = {52 -- 56}, language = {en} } @inproceedings{SchmittKranzHillenbrandetal., author = {Schmitt, Jan and Kranz, Philipp and Hillenbrand, Andreas and Kaupp, Tobias}, title = {Assisted human-robot-interaction for industrial assembly: Video to assisted human-robot-interaction for industrial assembly}, series = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction}, booktitle = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction}, pages = {665 -- 667}, language = {en} } @inproceedings{VoglerKauppSchmittetal., author = {Vogler, N. and Kaupp, Tobias and Schmitt, Jan and Antelmann, H.}, title = {Maturity level models for the evaluation of the digitalization progress of assembly-intensive production processes}, series = {German Assembly Engineering 2019}, booktitle = {German Assembly Engineering 2019}, language = {en} } @article{MillerEngelmannKauppetal., author = {Miller, Eddi and Engelmann, Bastian and Kaupp, Tobias and Schmitt, Jan}, title = {Advanced Cascaded Scheduling for Highly Autonomous Production Cells with Material Flow and Tool Lifetime Consideration using AGVs}, series = {Journal of Machine Engineering}, journal = {Journal of Machine Engineering}, issn = {2391-8071}, language = {en} } @inproceedings{SeitzSchmittEngelmann, author = {Seitz, Philipp and Schmitt, Jan and Engelmann, Bastian}, title = {Evaluation of proceedings for SMEs to conduct I4.0 projects}, series = {Procedia Cirp}, volume = {86}, booktitle = {Procedia Cirp}, pages = {257 -- 263}, language = {en} } @inproceedings{SchirmerKranzSchmittetal., author = {Schirmer, Fabian and Kranz, Philipp and Schmitt, Jan and Kaupp, Tobias}, title = {Anomaly Detection for Dynamic Human-Robot Assembly: Application of an LSTM-based autoencoder to interpret uncertain human behavior in HRC}, series = {Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction}, booktitle = {Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction}, doi = {10.1145/3568294.3580100}, pages = {881 -- 883}, language = {en} } @inproceedings{MillerKauppSchmitt, author = {Miller, Eddi and Kaupp, Tobias and Schmitt, Jan}, title = {Cascaded Scheduling for Highly Autonomous Production Cells with AGVs}, series = {Manufacturing Driving Circular Economy: Proceedings of the 18th Global Conference on Sustainable Manufacturing, October 5-7, 2022, Berlin ; Lecture Notes in Mechanical Engineering}, booktitle = {Manufacturing Driving Circular Economy: Proceedings of the 18th Global Conference on Sustainable Manufacturing, October 5-7, 2022, Berlin ; Lecture Notes in Mechanical Engineering}, editor = {Kohl, Holger and Seliger, G{\"u}nther and Dietrich, Franz}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-28838-8}, doi = {https://doi.org/10.1007/978-3-031-28839-5_43}, pages = {383 -- 390}, abstract = {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.}, language = {en} } @article{MillerCeballosEngelmannetal., author = {Miller, Eddi and Ceballos, Hector and Engelmann, Bastian and Schiffler, Andreas and Batres, Rafael and Schmitt, Jan}, title = {Industry 4.0 and International Collaborative Online Learning in a Higher Education Course on Machine Learning}, series = {2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop}, journal = {2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop}, pages = {1 -- 8}, language = {en} } @article{SeitzScherdelReichenaueretal., author = {Seitz, Philipp and Scherdel, Christian and Reichenauer, Gudrun and Schmitt, Jan}, title = {Machine Learning in the development of Si-based anodes using Small-Angle X-ray Scattering for structural property analysis}, series = {Computational Materials Science}, volume = {218}, journal = {Computational Materials Science}, pages = {111984 -- 111984}, language = {en} } @article{ScherdelMillerReichenaueretal., author = {Scherdel, Christian and Miller, Eddi and Reichenauer, Gudrun and Schmitt, Jan}, title = {Advances in the Development of Sol-Gel Materials Combining Small-Angle X-ray Scattering (SAXS) and Machine Learning (ML)}, series = {Processes}, volume = {9}, journal = {Processes}, number = {4}, pages = {672 -- 672}, language = {en} } @inproceedings{WehnertSchaeferSchmittetal., author = {Wehnert, Kira-Kristin and Sch{\"a}fer, S and Schmitt, Jan and Schiffler, Andreas}, title = {C7. 4 Application of Laser Line Scanners for Quality Control during Selective Laser Melting (SLM)}, series = {SMSI 2021-System of Units and Metreological Infrastructure}, booktitle = {SMSI 2021-System of Units and Metreological Infrastructure}, pages = {298 -- 299}, language = {en} } @techreport{AsikainenEskolaSalinFischeretal., author = {Asikainen, Eveliina and Eskola-Salin, Nina and Fischer, Sophie and Giedraitien{\´e}, Vytautė and Beseckas, Povilas and Mairhofer, Stephanie and K{\"o}der, Lea and Schmitt, Jan and Walter, Holger and Guerrero-Perez, Olga and Bl{\´a}zquez-Parra, Elidia Beatriz and Bikuvien{\´e}, Ina and Lisina, Neringa and Tamulien{\´e}, Rasa and Liepinaitien{\´e}, Alina and M{\"a}kel{\"a}, Anne-Maria and Tahlo, Sanna and Selimaa, Hanna and Hager, Veronika and Ortega-Casanova, Joaquin and Mora-Segado, Patricia}, title = {Sustainability at HEIs: Mapping Good Practice}, doi = {10.57714/b75p-n548}, abstract = {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 f{\"u}r Agrar- und Umweltp{\"a}dagogik (HAUP, Austria), Universidad de M{\´a}laga (UMA, Spain) and Technical University of Applied Sciences W{\"u}rzburg 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.}, language = {en} } @article{WilhelmLotterScherdeletal., author = {Wilhelm, Markus and Lotter, Frank and Scherdel, Christian and Schmitt, Jan}, title = {Advancing Efficiency in Mineral Construction Materials Recycling: A Comprehensive Approach Integrating Machine Learning and X-ray Diffraction Analysis}, series = {buildings}, volume = {14}, journal = {buildings}, number = {2}, publisher = {MDPI}, issn = {2075-5309}, doi = {10.3390/buildings14020340}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-56030}, pages = {14}, abstract = {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.}, language = {en} } @inproceedings{GattulloDammaccoRuospoetal., author = {Gattullo, Michele and Dammacco, Lucilla and Ruospo, Francesca and Evangelista, Alessandro and Fiorentino, Michele and Schmitt, Jan and Uva, Antonio E}, title = {Design preferences on industrial augmented reality: a survey with potential technical writers}, series = {2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, booktitle = {2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, pages = {172 -- 177}, language = {en} } @article{MillerBorysenkoHeusingeretal., author = {Miller, Eddi and Borysenko, Vladyslav and Heusinger, Moritz and Niedner, Niklas and Engelmann, Bastian and Schmitt, Jan}, title = {Enhanced Changeover Detection in Industry 4.0 Environments with Machine Learning}, series = {Sensors}, volume = {21}, journal = {Sensors}, number = {17}, pages = {5896 -- 5896}, language = {en} } @article{SchusterEngelmannSponholzetal., author = {Schuster, Florian and Engelmann, Bastian and Sponholz, Uwe and Schmitt, Jan and Engineering, Institute Digital}, title = {Human acceptance evaluation of AR-assisted assembly scenarios}, series = {Journal of Manufacturing Systems}, volume = {61}, journal = {Journal of Manufacturing Systems}, pages = {660 -- 672}, language = {en} } @inproceedings{SchusterSponholzEngelmannetal., author = {Schuster, Florian and Sponholz, Uwe and Engelmann, Bastian and Schmitt, Jan}, title = {A user study on AR-assisted industrial assembly}, series = {2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, booktitle = {2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, pages = {135 -- 140}, language = {en} } @inproceedings{MuellerEberhardtWahyudietal., author = {M{\"u}ller, Jonas and Eberhardt, Lars and Wahyudi, Vincent and Storath, Martin and Dobhan, Alexander}, title = {Towards an Approach on Location Data Analysis for Reusable Small-load Carriers}, series = {Proceedings of the 58th Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 58th Hawaii International Conference on System Sciences}, pages = {5330 - 5339}, language = {en} } @article{WehnertOchsSchmittetal., author = {Wehnert, Kira-Kristin and Ochs, Dennis and Schmitt, Jan and Hartmann, J{\"u}rgen and Schiffler, Andreas}, title = {Reducing Lifecycle Costs due to Profile Scanning of the Powder Bed in Metal Printing}, series = {Procedia CIRP 98}, volume = {98}, journal = {Procedia CIRP 98}, publisher = {Elsevir}, pages = {684 -- 689}, abstract = {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.}, language = {en} } @article{SchmittEngelmann, author = {Schmitt, Anna-Maria and Engelmann, Bastian}, title = {A Series Production Data Set for Five-Axis CNC Milling}, series = {Data}, volume = {9}, journal = {Data}, number = {5}, publisher = {MDPI}, issn = {2306-5729}, doi = {10.3390/data9050066}, abstract = {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.}, language = {en} } @article{GeorgeBijuSchmittEngelmann, author = {George Biju, Vinai and Schmitt, Anna-Maria and Engelmann, Bastian}, title = {Assessing the Influence of Sensor-Induced Noise on Machine-Learning-Based Changeover Detection in CNC Machines}, series = {Sensors}, volume = {2024}, journal = {Sensors}, language = {en} } @misc{SchmidtSchmitHuelsmann, author = {Schmidt, Dirk and Schmit, Jan and H{\"u}lsmann, Dennis}, title = {Antriebseinrichtung mit einer Rotationswelle, einem Rotor und einer Wuchtscheibe [Patent, DE102017122466A1]}, language = {en} }