@inproceedings{GuentherPrellReiffStephan2022, author = {G{\"u}nther, Norman and Prell, Bastian and Reiff-Stephan, J{\"o}rg}, title = {Industrie 5.0 : von der Vision des menschzentrierten Ansatzes zu soziocyberphysischen Produktionssystemen f{\"u}r die Praxis}, series = {Tagungsband AALE 2022}, booktitle = {Tagungsband AALE 2022}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-15787}, pages = {257 -- 266}, year = {2022}, abstract = {Industrie 4.0 Ans{\"a}tze haben sich in der fertigenden Industrie vielerorts etabliert. Big Data, IIoT und K{\"u}nstliche Intelligenz (KI) erm{\"o}glichen neue Gesch{\"a}ftsmodelle und wirken sich dadurch auch ver{\"a}ndernd auf Produktionssysteme aus. Mit dem Begriff der Industrie 5.0 formuliert sich ein menschzentrierter Ansatz. Die Praxisrelevanz dieser und {\"a}hnlicher Innovationen h{\"a}ngt maßgeblich davon ab, wie derartige Einsatzm{\"o}glichkeiten neuer, digitaler Technologien in die bestehenden Unternehmensstrukturen Einzug halten. Hierbei kommt es also auf Transfer und Akzeptanz neuer Technologien an. Digitalisierung gestaltet sich somit als sozio-technisches Problem. Dieser Beitrag gibt Einblick in aktuell verfolgte Transferans{\"a}tze f{\"u}r Digitalisierung im Mittelstand und leistet einen Teil zu Theoriebildung, als dass er auch einen Ausblick auf weitere Aktivit{\"a}ten in dem Umfeld liefert.}, language = {de} } @article{ReinhardtMahdaviaslPrelletal.2024, author = {Reinhardt, Heiner and Mahdaviasl, Mahtab and Prell, Bastian and Mauersberger, Anton and Klimant, Philipp and Reiff-Stephan, J{\"o}rg and Ihlenfeldt, Steffen}, title = {Efficient data acquisition for traceability and analytics}, series = {Procedia CIRP}, volume = {122}, journal = {Procedia CIRP}, publisher = {Elsevier}, issn = {2212-8271}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-19232}, pages = {73 -- 78}, year = {2024}, abstract = {Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management.}, language = {en} } @article{PrellReiffStephan2023, author = {Prell, Bastian and Reiff-Stephan, J{\"o}rg}, title = {A Use Case for Digital Tools in Crafts: Simulation and Virtual Reality for Carpentries}, series = {Simulation Notes Europe}, volume = {33}, journal = {Simulation Notes Europe}, number = {4}, issn = {2305-9974}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-19326}, pages = {191 -- 198}, year = {2023}, abstract = {This paper presents an integrated approach to explore human factors in the craft sector. The embedded use case consists of craft workshops being 3D-modelled and simulated so that different scheduling rules can be deployed. The connected VR visualization allows craft professionals to experience scheduling rules and their impact on different performance measurements in an environ-ment intuitively resembling their actual workshops. The lessons learned from the simulation modelling are collected and presented. A modular approach appears to be beneficial for simulation modelling, offering flexibility and pragmatism but detail when needed. Apart from this anecdotal evidence, the study is accompanied by interviews. These are analyzed based on abduction grounded theory which combines a strong focus on the actual corpus of qualitative data but considers theoretical foundations, when appropriate. This paper presents the study design, and how it interties with the research approach and the use case of simulation and virtual reality for carpentries.}, language = {en} } @article{PrellReinhardtMauersbergeretal.2023, author = {Prell, Bastian and Reinhardt, Heiner and Mauersberger, Anton and Rauscher, Alexander and Reiff-Stephan, J{\"o}rg and Ihlenfeldt, Steffen}, title = {A survey on sustainability approaches in manufacturing}, series = {Procedia CIRP}, volume = {116}, journal = {Procedia CIRP}, publisher = {Elsevier}, issn = {2212-8271}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-17527}, pages = {101 -- 106}, year = {2023}, abstract = {Awareness about climate change has led to policies and regulations but also customer preferences favoring sustainable production. Thus, producing businesses are confronted by this, as they consume a large share of resources. Therefore, when producing, additional dimensions beyond commercial feasibility ought to be considered. Here, literature on sustainability from the field of engineering science is systematically searched and analyzed for approaches leading to actual recommendations for action. Hence, this bottom-up approach, incorporating the production engineers' point of view, represents an inside view of how the topic of sustainability has arrived at production companies. The focus on commercial feasibility ensures high relevance to practice, as production needs to become both sustainable and competitive. Even though exemplary collections of different approaches addressing the topic of sustainability in production can be found in literature, novelty is provided by the structured manner literature was collected and the special focus on approaches leading to practice-relevant recommendations for action. Thus, a comprehensive overview of approaches applicable to the manufacturing domain is presented.}, language = {en} } @inproceedings{GuentherBenninDeubleetal.2025, author = {G{\"u}nther, Norman and Bennin, Julius and Deuble, Andreas and Huq, Mahmudul and Wilbers, Simon and Reiff-Stephan, J{\"o}rg}, title = {Predictive Maintenance am Beispiel einer Lehr- und Trainingsanlage}, series = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, booktitle = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Reichelt, Dirk}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20181}, pages = {309 -- 319}, year = {2025}, abstract = {Im Kontext der fortschreitenden Digitalisierung und Automatisierung hat die vorausschauende Wartung, auch Predictive Maintenance (PdM) genannt, insbesondere in industriellen Produktionslinien an Bedeutung gewonnen [1]. Wirtschaftliche Faktoren wie steigende Energiekosten, geringe Stillstand- und Instandhaltungszeiten aber auch die M{\"o}glichkeit des Monitorings unterst{\"u}tzen diesen Trend [2]. Diese erfordern im Umkehrschluss neben der technischen Expertise auch eine bedarfsorientierte Qualifizierung sowie ein system{\"u}bergreifendes Verst{\"a}ndnis. Um diesen Bedarf gerecht zu werden, kann das Thema theoretisch sowie praxisnah behandelt werden. Da nicht f{\"u}r jeden Bildungsbetrieb entsprechende Produktionslinien zur Qualifizierung und Erprobung von (neuen) Ans{\"a}tzen im Bereich des PdM zur Verf{\"u}gung stehen, ben{\"o}tigt es Lehr- und Trainingsanlagen, die der Ausbildung von Fachkr{\"a}ften dienen. Solche Anlagen erm{\"o}glichen es, Produktionsprozesse abstrakt aber trotzdem in einem realit{\"a}tsnahen Umfeld zu simulieren, wodurch sich Instandhaltungsstrategien wie PdM praxisnah anhand von Kennzahlen erlernen und erproben lassen. Der vorliegende Beitrag erl{\"a}utert den Aufbau einer Lehr- und Trainingsanlage zur Simulation von PdM Anwendungen f{\"u}r die Qualifizierung von Auszubildende und Ingenieure und die dabei zu beachtenden Herausforderungen.}, language = {de} } @inproceedings{WilbersGuenthervandeSandetal.2025, author = {Wilbers, Simon and G{\"u}nther, Norman and van de Sand, Ron and Prell, Bastian and Reiff-Stephan, J{\"o}rg}, title = {Components of reusable prompts for humanity-centered automation}, series = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, booktitle = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Reichelt, Dirk}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20148}, pages = {71 -- 78}, year = {2025}, abstract = {The increasing integration of large language models (LLMs) into cyber-physical production systems, necessitating solutions that are both efficient and aligned with human values and needs. Designing effective and reusable prompts is crucial for creating cyber-physical systems(CPS) that are effective, flexible, reliable, user-friendly and aligned with Humanity-centered Automation. This paper introduces essential components of reusable prompts: Versioning, Model Selection, Purpose Definition, Variables, Examples, and Output Structuring. By applying the proposed components, developers might enable CPS employing LLMs to operate with more predictable inputs and outputs, enabling better control over results and facilitating the chaining of multiple prompts or collaboration between different LLMs. These components emerged from extensive experimentation with various LLMs and prompt configurations. The resulting framework supports the maintenance of prompt collections similar to codebases and thus enhances traceability, maintainability, and human oversight. Such structured components for prompt design supports humanity-centered automation by ensuring that technological advances serve human values and improve interaction with complex systems.}, language = {en} } @inproceedings{GuentherPrellvandeSandetal.2024, author = {G{\"u}nther, Norman and Prell, Bastian and van de Sand, Ron and Reiff-Stephan, J{\"o}rg}, title = {Industrie 5.0 Lernumgebung am Beispiel der Wildauer Smart Production}, series = {Tagungsband AALE 2024}, booktitle = {Tagungsband AALE 2024}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and St{\"o}cker, Christian}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-18538}, pages = {365 -- 372}, year = {2024}, abstract = {Die Industrie 5.0 fordert neue Lernans{\"a}tze und zeitgleich auch passende Lernumgebungen. Parallel m{\"u}ssen diese neben den didaktischen Herausforderungen auch den Transfer- und {\"U}bertragungsgedanken auf die industriellen Anwendungen gerecht werden. Durch die t{\"a}glich steigende Anzahl vielf{\"a}ltiger KI-Tools insbesondere textgenerierenden Tools, braucht es Systeme mit einem breiten Anwendungsbereich. Im Rahmen des vorliegenden Beitrags geben die Autoren einen Einblick in die Wildauer Smart Production, welche den transdisziplin{\"a}ren Gedanken von Lern- und Transferumgebungen Rechnung tr{\"a}gt, M{\"o}glichkeiten der Gestaltung komplexer Produktionssysteme widerspiegelt, die Integration menschzentrierter Ans{\"a}tze erm{\"o}glicht und als Forschungsumgebung eingesetzt wird.}, language = {de} } @inproceedings{WilbersKupperGuentheretal.2025, author = {Wilbers, Simon and Kupper, Stefan and G{\"u}nther, Norman and van de Sand, Ron and Prell, Bastian and Speck, Sandy and Reiff-Stephan, J{\"o}rg}, title = {Unveiling automation potential through a better understanding of ideal cycle time}, series = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, booktitle = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Reichelt, Dirk}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20205}, pages = {223 -- 230}, year = {2025}, abstract = {This publication demonstrates that determining the maximum speed or Ideal Cycle Time (ICT) of machinery or cyber-physical systems is crucial for uncovering the limits of automation in a given system. Possibly increasing Overall Equipment Effectiveness (OEE) and identify opportunities for further digitization, automation, and AI integration. Based on literature review and expert interviews, methods for establishing ICT, mentioned in literature were identified and crosscheck with what practitioners in operation actually use and how they apply them. The identified methods were: Empirical Measurement and Data Analysis, Time Studies, Statistical Process Control (SPC), Benchmarking, Simulation and Modeling, Expert Judgment, and Continuous Improvement Practices we. We contrast these with insights obtained from interviews conducted with experts from companies in the German federal State of Brandenburg, representing diverse industries and sectors. Findings suggest that while companies recognize somewhat their ICT or maximum operational speeds, they often lack a structured method for determining them. They frequently use combinations of established methods inconsistently. We deduce that a formalized approach to defining ICT can better reveal system limitations and potential for expanding them through advanced automation and. We argue that a well-defined ICT is essential for pushing the boundaries of automated systems, contributing to more effective and Humanity-Centered Automation (HCA) solutions.}, language = {en} } @inproceedings{FiebelkornKugelGuentheretal.2025, author = {Fiebelkorn, Richard and Kugel, Rafael and G{\"u}nther, Norman and Reiff-Stephan, J{\"o}rg}, title = {Predictive Maintenance in der Baumpflege - TreeAngel}, series = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, booktitle = {Tagungsband AALE 2025 : menschenzentrierte Automation im digitalen Zeitalter}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Reichelt, Dirk}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20193}, pages = {251 -- 259}, year = {2025}, abstract = {Die Gew{\"a}hrleistung der Verkehrssicherheit von B{\"a}umen stellt eine zentrale Herausforderung f{\"u}r St{\"a}dte und Gemeinden dar. Traditionelle, manuelle Inspektionsmethoden sind zeit- und ressourcenintensiv sowie anf{\"a}llig f{\"u}r menschliche Fehler. Der folgende Artikel pr{\"a}sentiert ein innovatives System zur automatisierten Baumzustandsbewertung, welches moderne Kameratechnologien und K{\"u}nstliche Intelligenz (KI) nutzt. Im Rahmen einer Machbarkeitsstudie wurden Bilddaten, welche durch verschiedene Kamerasysteme erzeugt wurden, analysiert. Basierend auf diesen Daten wurde ein YOLOv8-Modell trainiert, welches eine pr{\"a}zise Detektion von B{\"a}umen und Sch{\"a}den, wie beispielsweise Totholz, erm{\"o}glicht. Die Ergebnisse des vorgestellten Prototypensystems sind vielversprechend hinsichtlich Genauigkeit und Effizienz. Es zeigt das Potenzial, manuelle Inspektionen durch automatisierte Verfahren zu erg{\"a}nzen oder zu ersetzen. Die pr{\"a}sentierten Resultate legen den Grundstein f{\"u}r nachhaltige und skalierbare Ans{\"a}tze in der Baumpflege und k{\"o}nnen zur Steigerung der {\"o}ffentlichen Sicherheit und Effizienz im urbanen Management beitragen.}, language = {de} } @inproceedings{PrellGuentherReiffStephan2021, author = {Prell, Bastian and G{\"u}nther, Norman and Reiff-Stephan, J{\"o}rg}, title = {Cyber-Physical Production Systems in Settings with Limited Infrastructure}, series = {2nd German-West African Conference on Sustainable, Renewable Energy Systems (SusRES2021)}, booktitle = {2nd German-West African Conference on Sustainable, Renewable Energy Systems (SusRES2021)}, publisher = {TIB Open Publishing}, address = {Hannover}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-14993}, pages = {229 -- 238}, year = {2021}, abstract = {During the last decade production innovation was mainly focused on connectivity aspects. The vision of smart factories running on software, that uses collected machine data, has become true but foremost for leading industrial companies in highly developed countries. Apart from these, production can also be found in non-industrialized craft professions as well as in less developed countries. As digitalization does not necessarily require an industrial or developed setting the latter could possibly benefit from it as well. Socio-cyber-physical production systems have been used to describe the interdependencies of linked production systems but usually focus on highly developed regions as well as for industrial applications. This paper lines out similarities and differences for each case, introduces the concept of cyber-physical production systems (CPPS) and its extension to socio-CPPS (SCPPS), which emphasizes the role of human workers in the production environment. The relation between industrial, non-industrial production and innovations is examined. Furthermore, the widening of SCCPS concepts for non-industrial production is discussed.}, language = {en} } @inproceedings{FalkvandeSandCorasanitietal.2021, author = {Falk, Constantin and van de Sand, Ron and Corasaniti, Sandra and Reiff-Stephan, J{\"o}rg}, title = {A Comparison Study of Data-Driven Anomaly Detection Approaches for Industrial Chillers}, series = {2nd German-West African Conference on Sustainable, Renewable Energy Systems (SusRES2021)}, booktitle = {2nd German-West African Conference on Sustainable, Renewable Energy Systems (SusRES2021)}, publisher = {TIB Open Publishing}, address = {Hannover}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-14970}, pages = {165 -- 174}, year = {2021}, abstract = {Faults in industrial chiller systems can lead to higher energy consumption, increasing wear of system components and shorten equipment life. While they gradually cause anomalous system operating conditions, modern automatic fault detection models aim to detect them at low severity by using real-time sensor data. Many scientific contributions addressed this topic in the past and presented data-driven approaches to detect faulty system states. Although many promising results were presented to date, there is lack of suitable comparison studies that show the effectiveness of the proposed models by use of data stemming from different chiller systems. Therefore this study aims at detecting a suitable data-driven approach to detect faults reliable in different domains of industrial chillers. Thus, a unified procedure is developed, to train all algorithms in an identical way with same data-basis. Since most of the reviewed papers used only one dataset for training and testing, the selected approaches are trained and validated on two different datasets from real refrigeration systems. The data-driven approaches are evaluated based on their accuracy and true negative rate, from which the most suitable approach is derived as a conclusion.}, language = {en} }