@article{FalkElGhayedvandeSandetal.2023, author = {Falk, Constantin and El Ghayed, Tarek and van de Sand, Ron and Reiff-Stephan, J{\"o}rg}, title = {A Data-Driven Approach Towards the Application of Reinforcement Learning Based HVAC Control}, series = {Journal of the Nigerian Society of Physical Sciences}, volume = {5}, journal = {Journal of the Nigerian Society of Physical Sciences}, number = {1}, publisher = {Department of Physics, Federal University Lafia Nasarawa State, Nigeria ; Nigerian Society of Physical Sciences}, issn = {2714-4704}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-17066}, year = {2023}, abstract = {Refrigeration applications consume a significant share of total electricity demand, with a high indirect impact on global warming through greenhouse gas emissions. Modern technology can help reduce the high power consumption and optimize the cooling control. This paper presents a case study of machine-learning for controlling a commercial refrigeration system. In particular, an approach to reinforcement learning is implemented, trained and validated utilizing a model of a real chiller plant. The reinforcement-learning controller learns to operate the plant based on its interactions with the modeled environment. The validation demonstrates the functionality of the approach, saving around 7\% of the energy demand of the reference control. Limitations of the approach were identified in the discretization of the real environment and further model-based simplifications and should be addressed in future research.}, language = {en} } @inproceedings{ElGhayedFalkWilbersetal.2023, author = {El Ghayed, Tarek and Falk, Constantin and Wilbers, Simon and van de Sand, Ron and Reiff-Stephan, J{\"o}rg}, title = {Modellansatz zur Prozessoptimierung beim hydroadh{\"a}siven Greifen}, series = {Tagungsband AALE 2023 : Mit Automatisierungstechnik gegen den Klimawandel}, booktitle = {Tagungsband AALE 2023 : Mit Automatisierungstechnik gegen den Klimawandel}, publisher = {Hochschule f{\"u}r Technik, Wirtschaft und Kultur}, address = {Leipzig}, isbn = {978-3-910103-01-6}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-17150}, pages = {1 -- 10}, year = {2023}, abstract = {Der Produktlebenszyklus von Kleidung ist vor allem durch lange Lieferketten von Niedriglohnl{\"a}ndern in Hochlohnl{\"a}nder gekennzeichnet. Die Eliminierung solcher Transportwege k{\"o}nnte dazu f{\"u}hren, dass der komplette Lebenszyklus von Kleidungsware nachhaltiger und umweltfreundlicher wird. Der Aufbau von Produktionsst{\"a}tten in Hochlohnl{\"a}ndern wird aktuell durch technische Herausforderungen des Produktionsprozesses von Kleidung bzw. allgemein biegeschlaffen Materialien verhindert. Aufgrund der Eigenschaften biegeschlaffer Materialien k{\"o}nnen die Entnahme bzw. definierte Ablage von Textilteilen heutzutage nur teilautomatisiert bzw. mit einem hohen Anteil manueller T{\"a}tigkeiten gel{\"o}st werden. Das Hydroadh{\"a}sive Greifen k{\"o}nnte eine L{\"o}sung sein, die oben genannten Prozesse zu automatisieren und die Produktion f{\"u}r Hochlohnl{\"a}nder zu verg{\"u}nstigen. Jedoch verf{\"u}gt das Verfahren noch {\"u}ber lange Zykluszeiten und die Haltekr{\"a}fte sind nicht reproduzierbar. Weiterhin ist die Findung von Einstellparametern sehr zeitaufwendig und komplex. Die L{\"o}sung k{\"o}nnte eine intelligente Steuerung sein, dessen Kernst{\"u}ck ein datengetriebenes Modell f{\"u}r die Parameteroptimierung und -findung ist. Im Rahmen der Forschungsarbeiten wird ein Modellansatz zur Optimierung der Taktzeit beim hydroadh{\"a}siven Greifen erarbeitet. Dabei wird die Gewinnung der Datengrundlage, das zu entwickelnde Modell sowie die eigentliche Validierung diskutiert.}, language = {de} } @inproceedings{vandeSandCorasanitiReiffStephan2020, author = {van de Sand, Ron and Corasaniti, Sandra and Reiff-Stephan, J{\"o}rg}, title = {Review of Condition Based Maintenance approaches for vapor compression refrigeration systems}, series = {Conference Proceedings : 1st German-West African Conference on Sustainable, Renewable Energy Systems SusRes : 1st July 2020 - Kara, Togo}, booktitle = {Conference Proceedings : 1st German-West African Conference on Sustainable, Renewable Energy Systems SusRes : 1st July 2020 - Kara, Togo}, doi = {10.15771/978-3-9819225-5-4_SI-2a}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-13369}, pages = {24 -- 33}, year = {2020}, abstract = {Vapor compression refrigeration systems are subject to performance degradation over time due to the presence of faults. However, latest work in the field of condition-based maintenance shows promising results in the automatic early detection of anomalous behaviour as well as in accurate machine diagnostics and can, therefore, increase the overall system reliability by simultaneously preventing machine downtimes. In this paper, the latest research works carried out within the last decade are reviewed and the approaches are classified regarding their working principles. Furthermore, the work at hand depicts the current research trend in this field and outlines current obstacles.}, language = {en} } @article{vandeSandSchulzRitzmannetal.2018, author = {van de Sand, Ron and Schulz, Sebastian and Ritzmann, Kay and Reiff-Stephan, J{\"o}rg}, title = {Vernetzung physischer und virtueller Entit{\"a}ten im CPPS : Augmented Reality als Mensch-Maschine Schnittstelle}, series = {atp magazin}, volume = {9}, journal = {atp magazin}, issn = {2190-4111}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-12739}, pages = {36 -- 43}, year = {2018}, abstract = {Konventionelle Fertigungsstrategien werden k{\"u}nftig zunehmend durch komplexe cyberphysische Produktionssysteme (CPPS) ersetzt. Es entstehen durchgehend verbundene Wertsch{\"o}pfungsnetzwerke mit großer Informationsdichte, die den Menschen mit einer signifikant gestiegenen Datenmenge konfrontieren, auf deren Basis er agieren muss. Daher nimmt die Mensch-Maschine-Schnittstelle einen wichtigen Stellenwert innerhalb des Produktionsprozesses ein, wobei sich neuartige Visualisierungsverfahren wie Augmented Reality (AR) vielversprechend zeigen. F{\"u}r entsprechende Anwendungen bedarf es einer durchg{\"a}ngigen Kommunikation aus dem Feld bis hin zur Applikation. Der Artikel beschreibt, wie existierende Kommunikationsstandards daf{\"u}r nutzbar gemacht werden k{\"o}nnen und zeigt eine beispielhafte Umsetzung. Zudem wird eine Kommunikationsarchitektur vorgeschlagen, die auf Grundlage der Verwaltungsschale den interoperablen Informationsaustausch zwischen physischen und virtuellen Entit{\"a}ten erm{\"o}glicht.}, language = {de} } @unpublished{vandeSandSchulzRitzmannetal.2018, author = {van de Sand, Ron and Schulz, Sebastian and Ritzmann, Kay and Reiff-Stephan, J{\"o}rg}, title = {Vernetzung von physischen und virtuellen Entit{\"a}ten im cyberphysischen Produktionssystem}, series = {atp magazin}, volume = {9}, journal = {atp magazin}, issn = {2190-4111}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-10611}, year = {2018}, abstract = {Konventionelle Fertigungsstrategien werden k{\"u}nftig zunehmend durch komplexe cyberphysische Produktionssysteme (CPPS) ersetzt. Es entstehen durchgehend verbundene Wertsch{\"o}pfungsnetzwerke mit großer Informationsdichte, die den Menschen mit einer signifikant gestiegenen Datenmenge konfrontieren, auf deren Basis er agieren muss. Daher nimmt die Mensch-Maschine-Schnittstelle einen wichtigen Stellenwert innerhalb des Produktionsprozesses ein, wobei sich neuartige Visualisierungsverfahren wie Augmented Reality (AR) vielversprechend zeigen. F{\"u}r entsprechende Anwendungen bedarf es einer durchg{\"a}ngigen Kommunikation aus dem Feld bis hin zur Applikation. Der Artikel beschreibt, wie existierende Kommunikationsstandards daf{\"u}r nutzbar gemacht werden k{\"o}nnen und zeigt eine beispielhafte Umsetzung. Zudem wird eine Kommunikationsarchitektur vorgeschlagen, die auf Grundlage der Verwaltungsschale den interoperablen Informationsaustausch zwischen physischen und virtuellen Entit{\"a}ten erm{\"o}glicht.}, 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{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} } @inproceedings{vandeSandCorasanitiReiffStephan2021, author = {van de Sand, Ron and Corasaniti, Sandra and Reiff-Stephan, J{\"o}rg}, title = {Positive-Unlabelled Learning based Novelty Detection for Industrial Chillers}, series = {2nd German-West African Conference on Sustainable, Renewable Energy Systems (SusRES2021)}, volume = {1}, 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-opus4-14965}, pages = {155 -- 164}, year = {2021}, abstract = {Chiller systems are used in many different applications in both the industrial and the commercial sector. They are considered major energy consumers and thus contribute a non-negligible factor to environmental pollution as well as to the overall operating cost. In addition, chillers, especially in industrial applications, are often associated with high reliability requirements, as unplanned system downtimes are usually costly. As many studies over the past decades have shown, the presence of faults can lead to significant performance degradation and thus higher energy consumption of these systems. Thus, data-driven fault detection plays an ever-increasing role in terms of energy efficient control strategies. However, labelled data to train associated algorithms are often only available to a limited extent, which consequently inhibits the broad application of such technologies. Therefore, this paper presents an approach that exploits only a small amount of labelled and large amounts of unlabelled data in the training phase in order to detect fault related anomalies. For this, the model utilizes the residual space of the data transformed through principal component analyses in conjunction with a biased support vector machine, which can be ascribed to the concept of semi-supervised learning, or more specifically, positive-unlabelled learning.}, language = {en} }