TY - CHAP A1 - Winkler, Herwig A1 - Schmid, Stefan ED - Tang, Loon-Ching T1 - Empirical Findings on the Status Quo of Industrial Production Management Systems in the Context of Advancing Digitalization T2 - Proceedings of the 10th International Conference on Industrial Engineering and Applications (ICIEA 2023), April 4–6, 2023, Phuket, Thailand Y1 - 2023 SN - 978-1-64368-408-6 SN - 978-1-64368-409-3 U6 - https://doi.org/10.3233/ATDE230029 SN - 2352-751X SN - 2352-7528 SP - 44 EP - 54 PB - IOS Press CY - Berlin ER - TY - GEN A1 - Küpper, Christoph A1 - Rösch, Janina A1 - Porada, Andreas A1 - Loidl, Karin A1 - Seitz, Jochen A1 - Winkler, Herwig ED - Kaiser, Susanna ED - Franke, Norbert ED - Mutschler, Christopher T1 - Use Case Driven Feasibility Study on the Technical Capabilities of 5G Indoor Positioning in the Automotive Production T2 - 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN-WiP 2023), September 25 - 28, 2023, Nuremberg, Germany N2 - The digitalization and automation of processes are essential for successful industrial production systems. Real-time positioning data is crucial for intelligent, automated, and quality-assured production. However, the lack of standardization in current real-time locating systems leads to high costs, inoperability, and limited multi-vendor availability. On the other hand, 5G technology offers in theory opportunities for high-accuracy positioning beyond mobile communication. Local 5G networks in industrial settings could leverage existing infrastructure for positioning. Although previous research demonstrates the theoretical capabilities of 5G positioning, practical trials cannot be performed due to hardware still being in early research developmental stages. This research aims to close the gap between research and industrial use by assessing the technical feasibility of 5G indoor positioning in an automotive production environment. To achieve this, use cases from research and industry are categorized into different scenarios based on distinct requirements. Representative use cases are analyzed considering system requirements and their feasibility. For this, first the overall concept of 5G positioning is tested in a research lab, followed by simulations of 5G positioning in an industrial environment. This is performed to determine the technical capability and expected accuracy. The simulations show that sub-meter accuracies can be achieved when combining 5G positioning with line� of-sight filtering. This study highlights the promising role of 5G as a real-time locating system in industrial settings. However, further research is needed to evaluate its accuracy and reliability in complex practical scenarios. Real industrial piloting will contribute to the validation and optimization of 5G positioning systems, facilitating widespread adoption across industries. KW - 5G Positioning KW - Feasibility KW - Automotive Production1 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0074-3581-3 UR - https://ceur-ws.org/Vol-3581/177_WiP.pdf UR - http://ceur-ws.org/Vol-3581/ SN - 1613-0073 PB - RWTH CY - Aachen ER - TY - GEN A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - Blockchain Adoption in Product Lifecycle Management: Challenges and Potential Directions T2 - Procedia CIRP N2 - Blockchain is a leading-edge technology that has received great public attention in the past few years. Due to its eccentric features i.e. transparency, immutability and decentralization, blockchain intends to targets any domain that deals with transactional data. In production sectors, significant efforts are in progress to make use of this disruptive technology for efficient collaboration among stakeholders and management of their products lifecycles. However, despite positive feedback and great aspiration, certain challenges still exist over which the executive level management has great concern. In this regard, this study tries to highlight and focus on what are the potential challenges in blockchain technology adoption? and provide recommendations for how organization can address those challenges? Initially, we elaborate and classify the potential challenges into two categories i.e. key challenges specific to blockchain adoption in PLM and some further challenges that are generic in nature and applicable to most of the applications of blockchain. The study then scientifically argues for potential directions and solutions to address the key challenges. Afterward, the general-purpose challenges are explored and broken down into four different aspects i.e. technical, organizational, environmental & social, and financial challenges. It is emphasized that both internal and external level decisions are need of the day to address these challenges. Finally, the evolution of a new era i.e. blockchain 5.0, its aims and capabilities to overcome the existing technical concerns has been discussed. Multiple Industrial sectors can follow the recommendation presented in this paper to setup their own secure and full-fledged blockchain-based PLM systems. KW - Blockchain Technology KW - Product Lifecycle Management KW - Potential Challenges KW - Blockchain 5.0 Y1 - 2023 U6 - https://doi.org/10.1016/j.procir.2023.08.022 SN - 2212-8271 VL - 120 SP - 117 EP - 122 ER - TY - GEN A1 - Bartsch, Devis A1 - Winkler, Herwig T1 - A new Instrument for Production Control: The Smart Order Concept T2 - Procedia CIRP N2 - Production control is an essential component of a production system used to monitor and manage production orders. Centrally controlled production systems rely on basic data management, such as storing the bill of materials and required work schedules. Components of customer orders are added to generate the corresponding production orders. However, this type of production control can pose serious problems in case of unforeseen events such as machine failure or changing customer requirements during production. In such scenarios, costly and time-consuming re-scheduling becomes necessary, which endangers the company's competitive position and leads to data retention issues. This paper introduces a new method of production control based on the concept of smart orders. Smart orders use smart contracts for autonomous routing based on programmed information in the source code, enabling self-control through the production system. Smart contracts are transaction programs that work with ‘if-then logic”, allowing for partially flexible process schedules and reducing the need for human intervention. The smart order uses the functionalities of blockchain technology, such as security, transparency, and immutability, to ensure the integrity of production data. The paper concludes by presenting the expected value propositions of smart order-based production control on the production system. Depending on the production control system used, companies can integrate the results presented in this paper into their own blockchain implementation strategy. KW - Smart Order KW - Production Control KW - Blockchain KW - Smart Contract Y1 - 2023 U6 - https://doi.org/10.1016/j.procir.2023.09.037 SN - 2212-8271 VL - 120 SP - 559 EP - 564 ER - TY - GEN A1 - Winkler, Herwig A1 - Hayat, Mubashir T1 - Blockchain-Based Decentralized Product Lifecycle Management: A Framework for Production Network T2 - IEEE International Conference on Industry Applications N2 - The current global trade wars, rising logistics costs, and the impact of the Covid-19 pandemic have compelled companies to re-evaluate their production strategies. An increasingly popular approach to address these issues is decentralized production, which involves manufacturing products near to the customers to reduce logistics and warehousing expenses, improve lead times, and decrease carbon emissions. However, the decentralized nature of the production network necessitates a secure communication platform for stakeholders to access authentic data in real-time. In this regard, blockchain technology is identified as a promising solution due to its characteristics, which make it suitable for product data management across its lifecycle, especially in a decentralized production network. Therefore, this work proposes a conceptual framework for a blockchainbased product lifecycle management (PLM) system to ensure data provenance, security, authenticity, and trusted traceability in a decentralized production network. Moreover, this study highlights that there is currently no such practical model available for decentralized production scenario. Consequently, we argue that successful deployment of a blockchain-based network would require a collaborative approach that involves close interaction and cooperation among all stakeholders in the network. KW - Blockchain Technology, Decentralized Product Lifecycle Management, Production Network, Conceptual Framework. Y1 - 2023 U6 - https://doi.org/10.1109/INDUSCON58041.2023.10374585 ER - TY - GEN A1 - Berneis, Moritz A1 - Winkler, Herwig T1 - Matching supply chain management challenges with blockchain applications T2 - Supply Chain Management: An International Journal N2 - Purpose This study aims to explore the potential of blockchain technology in the field of supply chain management (SCM). The research is motivated by the emerging significance of blockchain as a disruptive technology that can potentially address a range of challenges faced by SCM professionals globally. Design/methodology/approach In our approach, this paper utilized a knock-out criteria approach to break down 150 identified challenges in SCM to a more manageable number of 12. The Analytic Hierarchy Process (AHP) was then used to prioritize these challenges in order of their relative importance and suitability for resolution through blockchain. Findings The analysis identified key challenges to be addressed by blockchain technology in SCM. Most notably, it highlighted concerns related to price stability and global financial flows, which closely intertwine. Another significant group of issues pertains to tracking, tracing and the demonstration of sustainability, thus suggesting a substantial potential for bl Y1 - 2024 U6 - https://doi.org/10.1108/SCM-12-2023-0615 SN - 1359-8546 VL - 29 IS - 6 SP - 1063 EP - 1077 PB - Emerald ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - Transition Towards a Green Future: Upgrading a Digital Decarbonization Maturity Model T2 - Procedia Computer Science N2 - Successful digital transformation, driven by structural changes resulting from climate change mitigation, requires a strategic approach to help organizations assess their current position in both digitalization and decarbonization efforts. Through expert focus groups, the “Digital Decarbonization Maturity Model” we developed in a previous study, has been upgraded. Additionally, measures and approaches have been identified within each dimension of the model. This model covers nine dimensions: decarbonization goals, business model innovation, customers and suppliers, products and services, employees, collaboration, processes and activities, data, and IT-infrastructure, -security and -technology, that present a holistic approach to reduce CO2 emissions in organizations. These dimensions are assessed against five maturity levels: beginner, adopter, integrator, innovator, and transformer, indicating various degrees of maturity within each dimension. These levels provide a pathway from beginner to more advanced level with respect to adopting digital technologies for the decarbonization goal. KW - Digital Decarbonization KW - Maturity Model KW - Digital Transformation Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1016/j.procs.2025.01.192 SN - 1877-0509 VL - 253 SP - 1303 EP - 1312 ER - TY - GEN A1 - König, Mathias A1 - Winkler, Herwig T1 - Montage im Wandel : empirische Ergebnisse der Digitalisierung T2 - Industry 4.0 Science N2 - Die Montage bildet einen zentralen Bestandteil der industriellen Fertigung und ist traditionell von einem hohen Anteil manueller Arbeit geprägt. Unternehmen sehen in der Digitalisierung eine große wirtschaftliche Chance. Im Fokus steht dabei, die Produktivität der Mitarbeitenden zu steigern und gleichzeitig die Lohnstückkosten stabil zu halten. Die Nutzung innovativer Technologien wird deshalb immer wichtiger, um diese Ziele in der Montage umzusetzen KW - 3D-Druck, Assistenzsysteme, Augmented Reality, Cyber-Physische Systeme, digitaler Zwilling, Digitalisierung, Maschinelles Lernen, Montage, predictive maintenance Y1 - 2025 UR - https://industry-science.com/artikel/montage-im-wandel/ SN - 2942-6154 VL - 41. Jahrgang IS - 1 SP - 42 EP - 49 ER - TY - CHAP A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - A conceptual framework for digital twin lifecycle management in a blockchain-based environment T2 - Digital Twin and Blockchain for Sensor Networks in Smart Cities Y1 - 2025 SN - 9780443300769, 9780443300776 SP - 177 EP - 210 PB - Elsevier CY - u.a. ET - 1st Edition ER - TY - GEN A1 - Lamann, Arian A1 - Winkler, Herwig A1 - Abdelkafi, Nizar A1 - Lange, Hans Rüdiger T1 - Software Architecture for Co-Innovation Projects T2 - 2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD) N2 - Purpose Innovation is essential for competitive advantage and business growth and can be driven by approaches like open innovation (OI) and co-innovation (COI). Because of the complexity of innovation, traditional project management principles cannot be implemented to innovation projects. To deal with the complexity of innovation, software solutions can be used, especially to coordinate co-innovation projects (COIP). However, current software options only cover a few project phases and fail to address COI challenges comprehensively. Consequently, this study aims to develop a software architecture that addresses these gaps. Methodology The architecture was developed using requirement engineering. A focus group of ten industry experts used a canvas to determine specific requirements for producing companies. A systematic literature review was conducted to identify international requirements and global challenges. Finally, existing software solutions were analyzed to identify further gaps in requirements. These m Y1 - 2025 UR - https://ieeexplore.ieee.org/document/10878172/authors#authors SN - 979-8-3503-6736-2 U6 - https://doi.org/10.1109/ICTMOD63116.2024.10878172 SN - 2372-7268 SP - 1 EP - 6 ER - TY - CHAP A1 - Winkler, Herwig A1 - Kunath, Martin ED - Obermaier, Robert T1 - Adaptive Assistenzsysteme zur Entscheidungsunterstützung für die dynamische Auftragsabwicklung : konzeptionelle Überlegungen und Anwendungsszenarien unter Berücksichtigung des Digitalen Zwillings des Produktionssystems T2 - Handbuch Industrie 4.0 und Digitale Transformation : betriebswirtschaftliche, technische und rechtliche Herausforderungen N2 - Der Auftragsabwicklungsprozess ist in produzierenden Unternehmen durch eine erhöhte Komplexität infolge der zunehmenden Variantenvielfalt und der steigenden Anforderungen an individualisierte Produkte gekennzeichnet. Diese Komplexität führt zu Intransparenz bei Entscheidungen im Produktionsvollzug. Weiterhin verursachen verschiedene Prozessdynamiken, z. B. unvorhergesehene Störungen, kurzfristige und unregelmäßige Bestellungen sowie nachträgliche Kundenänderungswünsche Störungen in der Auftragsabwicklung. KW - Assistenzsysteme, Entscheidungsunterstützung, Auftragsabwicklung, Digitaler Zwilling, Produktionssystem Y1 - 2025 SN - 978-3-658-24576-4 U6 - https://doi.org/10.1007/978-3-658-36874-6_16-1 SP - 1 EP - 25 PB - Springer Gabler CY - Wiesbaden ET - 2. Auflage ER - TY - GEN A1 - Bartsch, Devis A1 - Winkler, Herwig T1 - Produktionssteuerungsumgebungen und ihre (technischen) Probleme BT - Welches Potenzial bietet die Blockchain-Technologie? T2 - Zeitschrift für wirtschaftlichen Fabrikbetrieb N2 - Technological development is leading to the emergence of new decentralized applications, such as decentralized production systems. Production systems require efficient production control for goal-oriented and resource-saving order processing. The environment in which the production control is implemented contributes significantly to its task fulfilment. This paper examines and analyses centralized and decentralized databases as well as edge and cloud computing as environments for production control. It additionally examines the potential of blockchain technology to solve the various problems of the presented production control environment KW - Blockchain; Database; Cloud Computing; Edge Computing; Production Control Y1 - 2024 U6 - https://doi.org/10.1515/zwf-2024-1145 SN - 2511-0896 VL - 119 IS - 10 SP - 710 EP - 719 PB - Walter de Gruyter GmbH ER - TY - GEN A1 - Lamann, Arian A1 - Winkler, Herwig A1 - Lange, Hans Rüdiger A1 - Abdelkafi, Nizar T1 - Co-innovation tools, mechanisms and methods : status quo and potentials T2 - Procedia CIRP N2 - Co-innovation and open innovation are approaches to innovation management that are designed to stimulate innovation in organizations. This study analyzes technical offline and online support tools that can aid co-innovation projects by identifying appropriate functionalities. A systematic literature review and analysis of co-innovation tools reveals a lack of support, particularly in the areas of (i) intellectual property management, (ii) compliance and legal management, (iii) planning and analysis management, and (iv) performance and monitoring management. Physical toolkits show advanced development in meeting the criteria, while software solutions lag behind. The findings highlight the need for comprehensive innovation support tools. KW - Innovation projects; Innovation management; Support tools Y1 - 2025 UR - https://www.sciencedirect.com/science/article/pii/S2212827125005360 U6 - https://doi.org/10.1016/j.procir.2025.02.165 SN - 2212-8271 VL - 134 SP - 514 EP - 519 PB - Elsevier CY - Amsterdam ER - TY - RPRT A1 - Hoffmann, Stefanie A1 - Thomas, Kevin A1 - Winkler, Herwig T1 - Der Design Thinking Ansatz : Fallstudien zum Prototyping von Komponenten und Systemen der dezentralen Energietechnik N2 - Diese Studie entstand im Kontext des Forschungsprojekts „SpreeTecneXt“. Ziel war es, durch den Design Thinking Ansatz innovative und nachhaltige Lösungen für die dezentrale Energietechnik zu entwickeln. Drei konkrete Fallstudien wurden auf Basis der Design Thinking-Methode durchgeführt: ein Reinigungssystem für PV-Module, ein nachsteuerndes Floating-PV-System und eine nachhaltige mobile Parkbox. Die Methode Design Thinking zeichnet sich durch ihren nutzerzentrierten, iterativen und kreativen Prozess aus, der besonders in unsicheren und dynamischen Marktumfeldern geeignet ist, komplexe Herausforderungen zu bewältigen. Im Rahmen der durchgeführten Projekte wurde der Design Thinking Ansatz nach Hasso Plattner angewendet. Der Design Thinking Prozess wurde in jeder Fallstudie durchlaufen. In der ersten Phase („Verstehen“) erfolgte eine intensive Auseinandersetzung mit den jeweiligen Design Challenges. Anschließend wurden in der zweiten Phase („Beobachten“) Nutzerbedürfnisse durch Interviews identifiziert. Die dritte Phase („Standpunkt definieren“) diente der systematischen Verdichtung dieser Erkenntnisse zu spezifischen Problemperspektiven. In der vierten Phase („Ideen finden“) wurden zahlreiche kreative und innovative Lösungskonzepte generiert. Diese wurden in der fünften Phase („Prototyp entwickeln“) zu greifbaren und testfähigen Prototypen ausgearbeitet. Die erfolgreiche Anwendung der Design Thinking Methode manifestierte sich in den Ergebnissen aller drei Projektgruppen. Das Team des PV Reinigungssystems entwickelte einen Funky Prototyp eines Reinigungsroboters. Die Gruppe des Floating PV Systems realisierte ein Modell eines funktionalen Prototypen mit intelligenter, sensorgesteuerter Sonnenstandsnachführung zur Optimierung der Energieausbeute und Reduzierung des Wartungsaufwands. Das Team der nachhaltigen mobilen Parkbox präsentierte ein modulares Design mit integrierter Ladefunktion, das sowohl Sicherheits- als auch Komfortbedürfnisse adressierte. Die Anwendung dieser Methode in komplexen Entwicklungsprojekten erweist sich als besonders wertvoll, da sie theoretische Konzepte durch praktische Erfahrung vermittelt. Die Ergebnisse dieses Projekts liefern sowohl praktische Erkenntnisse als auch methodische Anregungen für zukünftige Forschungs- und Entwicklungsarbeiten im Bereich der Energietechnik Innovationen und fördern gleichzeitig den Wissensaustausch zwischen akademischer Forschung und industrieller Praxis. KW - Design Thinking; Produktinnovation; Energietechnik; Erneuerbare Energien KW - Design Thinking; Erneuerbare Energien; Produktionswirtschaft; Energy technology; Production management; Renewable energies Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-70592 PB - Brandenburgische Technische Universität Cottbus-Senftenberg CY - Cottbus ; Senftenberg ER - TY - CHAP A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - A conceptual model for the artificial intelligence-driven transformation of the circular economy T2 - Innovations in communication networks : sustainability for societal and industrial impact : proceedings of 5th International Conference on Data Engineering and Communication Technology (ICDECT 2024) N2 - The integration of digital technologies, in particular artificial intelligence (AI), into the circular economy (CE) is critical for promoting sustainable development. This paper aims to investigate the role of AI in CE through a systematic literature review, resulting in the development of a conceptual model. Key enablers, including multiple stakeholders such as policymakers, industry, researchers, technology providers and consumers, are identified and AI models used in CE are outlined. In addition, challenges such as the quality and availability of data, skills gaps, integration with existing systems and coordination between various stakeholders are addressed. The benefits of integrating AI are explored at micro, meso and macro levels, demonstrating major improvements in environmental, economic and social sustainability. This work highlights the key role that AI can play in increasing resource efficiency, improving waste management and driving innovative business models, thereby contributing to a better sustainable future. Y1 - 2025 SN - 978-981-96-5223-5 U6 - https://doi.org/10.1007/978-981-96-5223-5_7 VL - 4 SP - 69 EP - 83 PB - Springer Nature CY - Singapore ET - 1. Auflage ER - TY - GEN A1 - Eichenseer, Patrick A1 - Winkler, Herwig T1 - Data-oriented shopfloor management : an inductively developed holistic conceptual model T2 - The international journal of advanced manufacturing technology N2 - Data plays a fundamental role in shopfloor management in order to make better decisions and increase efficiency throughout the production system. The idea of data-oriented shopfloor management has been discussed in the literature as an innovative concept, but unlike traditional or digital shopfloor management, it has not been conceptualised from a holistic perspective. For this reason, this paper used qualitative research in the form of expert interviews to collect holistic conceptual requirements for data-oriented shopfloor management. The data were analysed using the Gioia Methodology and transferred into a data structure to derive conceptual requirements at different levels of aggregation. On the basis of the empirical data, data-oriented shopfloor management was modelled, consisting of the system elements shopfloor, management approach with four subsystems and information system. Specifically, two conceptual models were developed for data-oriented shopfloor management as a distinction was made between episodic configuration and strategic adaptation and the persistent operating mode. Both conceptual models represent the reciprocal relationships and interdependencies of the system elements within data-oriented shopfloor management. Looking to the future, this paper provides the basis for further research to refine the conceptual models based on the empirically collected conceptual requirements with a higher level of detail. KW - Data · Shopfloor · Production · Management concept · Industry 4.0 · Empirical study Y1 - 2025 UR - https://link.springer.com/article/10.1007/s00170-025-15571-2 U6 - https://doi.org/10.1007/s00170-025-15571-2 SN - 1433-3015 VL - 2025 SP - 1 EP - 23 PB - Springer CY - Wiesbaden ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - A SWOT analysis approach for assessing the sustainable transition in the coal energy sector in Germany T2 - Procedia computer science N2 - The coal energy sector plays a significant role within the German economy, providing a key source of growth and energy supply. However, it is also a major contributor to climate change. In order to address this issue, Germany has adopted a policy to phase-out coal by 2038 at the latest. This paper employs a SWOT (strengths, weaknesses, opportunities, and threats) analysis approach to evaluate the sustainable transition of Germany's coal energy sector. A case study using semi-structured interviews with key actors was conducted in the second largest mining region in Germany, the Lusatia region. The analysis shows that the strengths of the area include its energy expertise, existing infrastructure with renewable energy potential, and availability of land for industrial development and settlement. However, dependence on lignite, internal resistance to change, lack of competence in digital technologies, and complex bureaucracy for implementing new projects represent some of the key weaknesses that companies must address in order to succeed. Some opportunities arise from the structural changes currently occurring, highlighting the potential of a growing renewable energy market and the development of innovative business models, as well as the creation of new employment opportunities and the enhancement of the region's attractiveness for global corporations. Nevertheless, a number of factors present a threat to the sustainable transition, including concerns about energy security, high green fuel costs, social resistance, a shortage of skilled labor, labor migration, and the loss of cooperation partners. KW - Sustainable Transition KW - Sustainability KW - Energy Sector KW - Coal Phase-out KW - Decarbonization KW - SWOT Analysis KW - Energy Value Chain Y1 - 2025 U6 - https://doi.org/10.1016/j.procs.2025.07.010 SN - 1877-0509 VL - 263 SP - 76 EP - 81 PB - Elsevier BV CY - Amsterdam ER - TY - CHAP A1 - Winkler, Herwig A1 - Seebacher, Gottfried ED - Bungartz, Oliver T1 - Verbesserung der Robustheit von Supply Chains durch Einsatz eines hierarchischen Flexibilitätsmanagements T2 - Risikomanagement in Supply Chains : Compliance und resiliente Lieferketten – Realisierung von Chancen durch Risikosteuerung N2 - Das aktuelle Unternehmensumfeld weist eine hohe Volatilität bei vielen Faktoren auf, gepaart mit Technologiesprüngen und erheblichen Diskontinuitäten in den Kunden- und Lieferantenbeziehungen. Dies führt zu vielfältigen Risiken entlang der gesamten Wertschöpfungskette. Die auftretenden Risiken verursachen bei den Unternehmen einer bestimmten Supply Chain beträchtliche Probleme zur Aufrechterhaltung der geplanten Performance. Aufgrund verketteter Prozesse in Produktion und Logistik führen Probleme bei den Wertschöpfungsaktivitäten einzelner Partner zu starken Beeinträchtigungen im gesamten Betriebsgeschehen. In dieser Situation erlangt die Robustheit der Supply Chain eine zentrale Bedeutung. Robustheit kann allgemein als eine Fähigkeit angesehen werden, die dazu beiträgt, dass durch Störungen von innen oder außen, keine oder nur geringe Abweichungen bei der geplanten Performance entstehen. Die Robustheit ist eine komplexe Größe in der sich Flexibilität, Agilität, Resistenz und Resilienz vereinen. Nach unserem Verständnis spielt vor allem die Flexibilität eine besondere Rolle für Supply Chains, um eine hohe Robustheit zu erlangen. Wir wollen in diesem Beitrag schwerpunktmäßig den konzeptionellen Aufbau eines hierarchischen Flexibilitätsmanagement von der Supply Chain über die einzelnen Unternehmen bis in die Produktionssysteme vorstellen, mit dem die Robustheit ganzheitlich verbessert werden kann. KW - Supply Chain Management KW - Risikomanagement KW - Robustheit Y1 - 2025 UR - https://esv-elibrary.de/book/99.160005/9783503240692 SN - 978-3-503-24068-5 SN - 978-3-503-24069-2 U6 - https://doi.org/10.37307/b.978-3-503-24069-2 SP - 268 EP - 291 PB - Erich Schmidt Verlag CY - Berlin ET - 3., völlig neu bearbeitete Auflage ER - TY - GEN A1 - Thomas, Kevin A1 - Winkler, Herwig ED - Mourtzis, Dimitris T1 - Extended reality for process visualization in cloud manufacturing : a systematic review T2 - Procedia CIRP N2 - The advent of cloud-based processes represents a novel opportunity within the manufacturing industry. However, a lack of common understanding of integration persists. The virtualization of manufacturing and logistics processes provides the foundation for subsequent stages of visualization. Conversely, the visualization of processes facilitates a deeper comprehension of the value streams involved, thereby enabling improvements to be made. In this regard, the objective of this research is to assess process virtualization techniques in cloud manufacturing, with a particular focus on existing academic literature in the field. Consequently, this investigation also encompasses an exploration of immersive visualization techniques in cloud manufacturing environments. For the purpose of this research, a systematic literature review is conducted in the SCOPUS, Web of Science, and Science Direct databases. Various methods and implications for the virtualization of cloud manufacturing processes available in the literature are identified, analyzed, and summarized. Furthermore, the potential for visualizing data related to cloud manufacturing processes in extended reality is also investigated. The findings of this research offer scientists the prospect of further investigation into the cloud manufacturing paradigm, for example in the context of virtual learning factories. KW - Cloud manufacturing KW - Web-based manufacturing KW - Virtualization KW - Extended reality KW - Literature review Y1 - 2025 U6 - https://doi.org/10.1016/j.procir.2025.08.111 SN - 2212-8271 VL - 136 SP - 648 EP - 653 PB - Elsevier B.V. CY - Amsterdam ER - TY - RPRT A1 - Winkler, Herwig A1 - Hayat, Mubashir A1 - Rüster, Moritz T1 - KI-basierte Instandhaltungsplanung und –steuerung im öffentlichen Verkehr: Status quo und konzeptionelle Überlegungen N2 - Durch eine sorgfältige Instandhaltung von Zügen, Bussen und Flugzeugen lässt sich die Verfügbarkeit, Betriebssicherheit und Wirtschaftlichkeit dieser Verkehrsmittel maßgeblich sichern. Bislang wurden die dafür relevanten planungsintensiven Prozesse in Zugwerkstätten mit herkömmlichen statischen Planungssystemen durchgeführt. Diese Systeme bilden zwar eine Grundlage für die Organisation der Instandhaltungsarbeiten, sind jedoch nicht in der Lage, optimierte Instandhaltungsprogramme zu erstellen. Infolgedessen treten während der tatsächlichen Durchführung der Instandhaltungsmaßnahmen häufig ungeplante Zusatzaufgaben auf, die den Arbeitsablauf in den Instandhaltungswerkstätten stören und sowohl die wirtschaftliche als auch die betriebliche Effizienz beeinträchtigen. Es hat sich gezeigt, dass solche Störungen häufig zu erhöhten Instandhaltungskosten, längeren Durchlaufzeiten und einer verminderten Anlageneffizienz führen. Daher besteht ein wachsender Bedarf, bei der Instandhaltungsplanung und -steuerung im öffentlichen Verkehrssektor von statischen zu dynamischeren, datengesteuerten Ansätzen überzugehen. Künstliche Intelligenz (KI) bietet in dieser Hinsicht ein erhebliches Potenzial, da sie die Entwicklung von Vorhersagefähigkeiten, dynamischer Planung und intelligenter Ressourcenzuweisung erleichtert. Zu diesem Zweck werden in dieser Studie bestehende Forschungsarbeiten zu KI Ansätzen für die Wartungsplanung und -steuerung in diesen Bereichen des öffentlichen Verkehrs systematisch untersucht und bewertet. Anhand einer deskriptiven Analyse werden neue Forschungstrends vorgestellt, während eine detaillierte Inhaltsanalyse die Ergebnisse der relevantesten Artikel in diesem Bereich zusammenfasst. Die Analyseergebnisse zeigen, dass sich die meisten Forschungsarbeiten isoliert auf bestimmte Aspekte wie die Vorhersage der verbleibenden Nutzungsdauer und die Fehlerdiagnose konzentrieren. In der Praxis umfasst die Wartungsplanung und -steuerung jedoch eine komplexe Koordination vieler Aktivitäten (z B Inspektion, Ressourcenzuweisung und Personal und Aufgabenplanung usw.). Daher sind die Autoren der Ansicht, dass noch holistischere Lösungen erforderlich sind, die Instandhaltungsaktivitäten und Werkstattbeschränkungen integrieren und über Einzelkomponentenvorhersagen hinaus zu einer Optimierung der Instandhaltung auf Systemebene führen, die in realen Instandhaltungsbetrieben validiert werden kann. Darüber hinaus wird in diesem Studienbericht ein konzeptioneller Rahmen vorgestellt der die Planung und Steuerung von Instandhaltungsaufträgen in Instandhaltungswerkstätten des öffentlichen Nahverkehrs verbessern soll. Der vorgeschlagene Rahmen dient als Grundmodell für den Einsatz von KI Technologien zur Reduzierung von Ineffizienzen, zur Verbesserung der Terminplanung und letztlich zur Unterstützung einer zeitnahen und kosteneffizienten Instandhaltungsplanung und -steuerung für Züge. N2 - Maintenance of public transport assets e.g., trains, buses, and airplanes has a major impact on their availability, safety and cost-effectiveness. To date, planning-intensive processes in train maintenance workshops have been carried out with traditional static planning systems. While these systems have provided a foundation for organizing maintenance work, they are unable to generate optimized maintenance programs. As a result, unplanned additional tasks frequently arise during the actual execution of the maintenance operations, thereby disrupting workflows in maintenance workshops and reducing both economic and operational efficiency. It has been demonstrated that such disruptions often lead to increased maintenance costs, longer lead times, and reduced plant efficiency. Therefore, there is a growing need to shift from static to more dynamic, data-driven approaches for maintenance planning and control in public transport sectors. Artificial Intelligence (AI) offers significant potential in this regard, as it facilitates the development of predictive capabilities, dynamic scheduling, and intelligent resource allocation. To this aim, this study therefore systematically reviews and examines existing research on AI approaches for maintenance planning and control across these public transport sectors. Descriptive analysis is performed to present emerging research trends, while detailed content analysis synthesizes the findings of the most relevant articles in the domain. The analysis results show that most of the research focuses on the specific aspects such as predicting the remaining useful life and faults diagnoses, etc., in isolation. However, in practice, maintenance planning and control involves a complex coordination of many activities (e.g., inspection, resource allocation, and workforce & tasks scheduling, etc.). Therefore, the authors believe that there is still need for more holistic solutions that can integrate maintenance activities and shopfloor constraints, moving beyond single-component predictions to system-level maintenance optimization that could be validated in real maintenance facilities. Furthermore, this study report presents conceptual framework designed to enhance maintenance order planning and control in public transport maintenance workshops. The proposed framework serves as a foundational model for utilizing the AI technologies to reduce inefficiencies, improve scheduling, and ultimately support timely and cost-effective maintenance planning and control strategies for trains. T2 - AI-based maintenance planning and control of public transport : status quo and conceptual considerations KW - Instandhaltungsplanung KW - Instandhaltungssteuerung KW - KI KW - Öffentliche Verkehrsmittel KW - AI KW - Maintenance control KW - Maintenance planning KW - Public transportation Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-71612 PB - Brandenburgische Technische Universität Cottbus-Senftenberg CY - Cottbus ER - TY - GEN A1 - Ahatsi, Emmanuel A1 - Winkler, Herwig A1 - Olanrewaju, Oludolapo T1 - Modified teaching-learning based optimisation for resilience and sustainability in the renewable energy industry T2 - 2025 IEEE 13th International Conference on Smart Energy Grid Engineering (SEGE) N2 - Renewable energy sector resilience ensures sustainability and reliability together with cybersecurity features for present-day power networks. Growing wind and solar and hybrid distributed generation (RHDG) systems create numerous network problems, including power system instability, cyber security risks, and operational efficiency problems. The implementation of Modified Teaching-Learning Based Optimisation (MTLBO) serves as an improvement method for resolving power flow management issues and enhancing fault tolerance while ensuring energy security. MTLBO serves to maximize renewable energy deployment while minimizing power losses and improving resistance against cyber-physical security threats. The integration of decentralized microgrid design, realtime monitoring, and artificial intelligence to identify anomalies enhances system resilience. Multiple smart grid security measures are implemented through Blockchain technology to combat potential cyberattacks which endanger grid operations. The research demonstrates how implementing MTLBO and advanced cybersecurity strategies for OPF enables sustainable development of renewable energy infrastructure. The proposed method delivers secure, efficient, and adaptive power management that enables a resilient renewable energy power infrastructure for future readiness. KW - Optimal Power Flow (OPF) KW - RHDG KW - Particle Swarm Optimisation (PSO) KW - Modified TLBO (MTLBO) KW - Distributed Energy Resources (DER) KW - Teaching-Learning Based Optimisation (TLBO) Y1 - 2025 U6 - https://doi.org/10.1109/SEGE65970.2025.11203381 SP - 225 EP - 230 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - Piscataway, NJ ER - TY - CHAP A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - Artificial intelligence as a driver for the digital transformation of business models T2 - Smart production for sustainability : proceedings of the International Conference for Production Research Asia Pacific Region 2025 N2 - Digital transformation is forcing companies to adapt their existing business mod-els to new technological developments and market requirements. A significant challenge is the effective application of innovation digital technologies to enhance operational efficiency and achieve competitive advantage. This paper investigates the impact of digitalization and artificial intelligence (AI) on business models, highlighting the key success factors for transformation and addressing the chal-lenges arising throughout the process. Empirical insights from semi-structured in-terviews with relevant actors from the research and practice are presented in this paper. The Gioia method was used to analyse the interview data in order to obtain a meaningful data structure. The findings identify three primary aggregate dimen-sions that influence the transformation of business models, namely operational ef-ficiency and technological feasibility, organizational culture change, and strategic competitiveness and future security. Digital technologies have the potential to in-crease efficiency and facilitate the transformation of existing business models. However, challenges related to data management, process optimization and cost concerns are faced by companies. In addition, the digital transformation process is frequently accompanied by a cultural shift that is often accompanied by unreal-istic expectations, resistance to change, and identified skills gaps. This necessi-tates effective leadership and change management to facilitate the navigation of these obstacles. Moreover, AI can serve as a powerful competitive advantage, fa-cilitating scalable innovation. These technological, cultural and strategic factors require addressing in order to facilitate the successful integration of AI in a com-pany's transformation strategy. KW - Artificial intelligence KW - Digital transformation KW - Business model Y1 - 2026 SN - 978-981-95-5819-3 U6 - https://doi.org/10.1007/978-981-95-5819-3_11 SN - 2731-4170 SP - 78 EP - 83 PB - Springer Nature CY - Singapore ET - 1 ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - Assessing the maturity of digital decarbonization in the manufacturing sector T2 - LogForum : scientific journal of logistics N2 - Organizations face the challenge of making strategic decisions to build a carbon-neutral and competitive future through the adoption of digital technologies. This pressure arises from rapidly evolving global market conditions and the need to achieve required emission reductions. For a successful deployment of Industry 4.0 technologies to support decarbonization, it is crucial for organizations to assess their competencies and establish a clear path forward. Digital maturity models are effective frameworks for measuring an organization's digital capabilities, and several such models have been developed. However, existing models often overlook environmental dimensions, focusing primarily on profit-driven growth. To address this gap, a Digital Decarbonization Maturity Model has been developed. This paper aims to evaluate the model’s effectiveness and applicability by assessing the current state of digital decarbonization within organizations and identifying opportunities for advancement, drawing on empirical insights from a focus group. KW - Digital decarbonization KW - Maturity model KW - Manufacturing sector KW - Case study Y1 - 2026 U6 - https://doi.org/10.17270/J.LOG.001282 SN - 1734-459X VL - 22 IS - 1 SP - 15 EP - 27 PB - Wyzsza Szkola Logistyki CY - Poznan ER -