TY - GEN A1 - Jeglinsky, Vinzenz A1 - Winkler, Herwig T1 - Untersuchungen von Entscheidungsprozessen im Zuge der Digitalisierung T2 - Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) N2 - Die Digitalisierung produzierender Unternehmen schreitet voran. Dennoch bestehen entlang des Entscheidungsprozesses zur Umsetzung von Digitalisierungsvorhaben zahlreiche Hindernisse. Zum zielgerichteten Auflösen der vorhandenen Hindernisse ist ein auf den Besonderheiten des Entscheidungsprozesses fokussierter Ansatz notwendig, der die Umsetzung der Vorhaben beschleunigt, Ressourcen schont und die Entscheidungsqualität verbessert. KW - Entscheidungsprozesse KW - Digitalisierung Y1 - 2019 U6 - https://doi.org/10.3139/104.112116 VL - 114 IS - 7-8 SP - 488 EP - 495 ER - TY - GEN A1 - Tangour, Cyrine A1 - Gebauer, Marc A1 - Fischer, Luise A1 - Winkler, Herwig T1 - Digital Business Model Patterns of Big Pharmaceutical Companies - A Cluster Analysis T2 - DIGITAL ECONOMY. Emerging Technologies and Business Innovation 4th International Conference, ICDEc 2019 Beirut, Lebanon, April 15-18, 2019 Proceedings Y1 - 2019 UR - https://link.springer.com/content/pdf/10.1007%2F978-3-030-30874-2.pdf SN - 978-3-030-30874-2 SP - 397 EP - 412 PB - Springer ER - TY - GEN A1 - Kunath, Martin A1 - Winkler, Herwig T1 - Interaktionsorientierte Organisationsgestaltung T2 - Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) Y1 - 2020 UR - https://www.hanser-elibrary.com/doi/10.3139/104.112247 U6 - https://doi.org/10.3139/104.112247 SN - 0947-0085 VL - 115 IS - 3 SP - 115 EP - 118 ER - TY - RPRT A1 - Jeglinsky, Vinzenz A1 - Winkler, Herwig T1 - Untersuchung von Hindernissen zur Digitalisierung in der industriellen Produktion Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-51588 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senftenberg ER - TY - GEN A1 - Bartsch, Devis A1 - Winkler, Herwig ED - Kersten, Wolfgang ED - Blecker, Thorsten ED - Ringle, Christian M. T1 - Blockchain technology in Germany: an excerpt of real use cases in logistics industry T2 - Data Science and Innovation in Supply Chain Management : How Data Transforms the Value Chain N2 - Purpose: Due to the large number of intermediaries in logistics networks there is avariety of possible failures, frictions and waste of time and money among the logisticsprocess chain. With the ability to provide data securely in near real-time, liketrack and tracing data of goods to every participant, the Blockchain-Technology(BCT) can help to solve these problems. Methodology: A structured literature analysis has been executed by using the databasesWeb of Science and Science Direct to find out current intermediary´s functionsand real use cases. In addition, available other sources, like manufacturer websites,blog entries or whitepapers are searched for specific blockchain-based applicationsinvented and used by German companies. The identified use cases are then qualitativelyanalyzed. Findings: The first results showed that most of the business cases are still in the conceptphase or are merely ideas how the BCT could solve existing problems. Additionally,we got results on the distribution of applications and economic benefits alongthe logistics chain. Furthermore, important conclusions on implementation problemscan be derived from this. Originality: In order to maintain Germany´s top economic position, it is necessaryto push ahead with the adaption of the BCT. Our analysis contains first results in thearea of real blockchain use cases of German companies. Initial comparisons betweencurrently used and blockchain-based logistics networks are also possible. KW - Logistics ; Industry 4.0 ; Digitalization ; Innovation ; Supply Chain Management ; Artificial Intelligence ; Data Science Y1 - 2020 SN - 978-3-753123-46-2 U6 - https://doi.org/10.15480/882.3111 SN - 2365-5070 SP - 699 EP - 735 PB - epubli CY - Berlin ER - TY - GEN A1 - Stockmann, Christian A1 - Winkler, Herwig T1 - Bedeutung der Robustheit von Produktionssystemen T2 - ZWF Y1 - 2021 U6 - https://doi.org/10.1515/zwf-2021-0028 SN - 0947-0085 VL - 116 IS - 3 SP - 144 EP - 148 ER - TY - GEN A1 - Berneis, Moritz A1 - Bartsch, Devis A1 - Winkler, Herwig T1 - Applications of Blockchain Technology in Logistics and Supply Chain Management—Insights from a Systematic Literature Review T2 - Logistics Y1 - 2021 U6 - https://doi.org/10.3390/logistics5030043 SN - 2305-6290 VL - 5 IS - 3 ER - TY - RPRT A1 - Stockmann, Christian A1 - Winkler, Herwig T1 - Robustheit in Produktionssystemen aus Sicht der industriellen Praxis KW - Industrielle Praxis KW - Produktion KW - Produktionssysteme KW - Robustheit KW - Umfrage KW - Industrial Practice KW - Manufacturing KW - Production KW - Production Systems KW - Robustness KW - Survey Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-52414 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senftenberg ER - TY - GEN A1 - Berneis, Moritz A1 - Winkler, Herwig T1 - Value Proposition Assessment of Blockchain Technology for Luxury, Food, and Healthcare Supply Chains T2 - Logistics N2 - Background: In relevant research, blockchain technology (BCT) is credited with great potential for supply chain management (SCM). However, even after more than 10 years of the technology’s existence, it is barely used for any self-sustaining applications. This raises the question of why BC cannot prevail against its alternatives. With this paper we want to identify criteria by which the added value of BCT can be measured. Furthermore, we want to evaluate how well the different supply chains (SC) exploit the added values of BCT. Methods: For this, we identified real-world examples and case studies for luxury, food, and healthcare SCs. These examples are described in detail and then analyzed for their added value compared to possible alternatives. Results: The results show that in the clusters of food and healthcare SCs, no general added value of BC over current best-practice solutions could be verified. Luxury SCs manage valuable products that are typically traded in small quantities. It is within this cluster that the implementation of BC can be justified best. Conclusions: In conclusion, this study shows that the application of BCT is especially beneficial for goods with a high value and low trade volume. In addition, the interface between reality and the digital twin should be as secure as the database or BC solution itself. Furthermore, the demand for transparency and immutability of data should be more important than the need to protect sensitive data. Finally, SC participants, especially the end customer, must also be able to appreciate the advantages of BCT. KW - blockchain technology KW - Smart Contracts KW - logistics KW - supply chain management KW - value proposition assessment Y1 - 2021 U6 - https://doi.org/10.3390/logistics5040085 SN - 2305-6290 VL - 5 IS - 4 SP - 1 EP - 18 ER - TY - GEN A1 - Berneis, Moritz A1 - Winkler, Herwig T1 - Fallstudie zur Fabrikplanung im Greenfield T2 - WiSt Wirtschaftswissenschaftliches Studium Y1 - 2022 UR - https://rsw.beck.de/zeitschriften/wist/das-aktuelle-heft SN - 0340-1650 VL - 51 IS - 1 SP - 58 EP - 63 ER - TY - GEN A1 - Kuteyi, Damilola A1 - Winkler, Herwig T1 - Logistics Challenges in Sub-Saharan Africa and Opportunities for Digitalization T2 - Sustainability N2 - Improvements in logistics performance are considered to be a significant driver of economic growth. Digitalization in logistics, which includes enhanced tracking systems, digitized flows of information, artificial intelligence and automation, has further enabled globalized trade. However, Sub-Saharan African (SSA) economies, majorly export-commodity-dependent, still lag behind, grappling with inadequate policy frameworks, huge infrastructure deficits and trade barriers which result in a broken supply chain that negatively impacts growth. This study aims to investigate existing challenges in Sub-Saharan Africa, the potentials for the region to leapfrog traditional supply chain practices and adopt digital technologies, by evaluating previous findings in a systematic manner and augmenting these findings through semi-structured interviews. Systematic literature analysis conducted on published academic literature within a specific period and based on predefined criteria resulted in 287 articles being used for the final analysis. The most common logistics challenges and potential solutions have been identified. Semi-structured interviews with logistics service providers in the region have been conducted to establish the findings highlighted in the systematic literature review. The interviews showed that human capital training is a major factor when adopting digital technologies, and a focus on infrastructure investments, regulatory and institutional framework improvements will boost economic growth in Sub-Saharan Africa. KW - digitalization KW - industry 4.0 KW - logistics KW - sub-Saharan Africa Y1 - 2022 UR - https://www.mdpi.com/2071-1050/14/4/2399/htm U6 - https://doi.org/10.3390/su14042399 SN - 2071-1050 VL - 14 IS - 4 ER - TY - GEN A1 - Stockmann, Christian A1 - Winkler, Herwig T1 - Robustness of production systems: Evidence from the German manufacturing industry T2 - Journal of Engineering and Technology Management Y1 - 2022 UR - https://www.sciencedirect.com/science/article/pii/S0923474822000029 U6 - https://doi.org/10.1016/j.jengtecman.2022.101672 SN - 0923-4748 VL - Vol. 63 ER - TY - CHAP A1 - Jeglinsky, Vinzenz A1 - Winkler, Herwig ED - Baumann, Sabine T1 - Improved decisions for digitalization projects in digital business ecosystems T2 - Handbook on Digital Business Ecosystems. Strategies, Platforms, Technologies, Governance and Societal Challenges Y1 - 2022 UR - https://www.elgaronline.com/view/edcoll/9781839107184/9781839107184.00028.xml SN - 978-1-83910-719-1 SN - 978-1-83910-718-4 U6 - https://doi.org/10.4337/9781839107191.00028 SP - 307 EP - 326 PB - Edward Elgar Publishing Ltd (Verlag) CY - Chaltenham ER - TY - CHAP A1 - Winkler, Herwig A1 - Mielke, Jonas ED - Roth, Stefan ED - Corsten, Hans T1 - Adaptive Assistenzsysteme zur Entscheidungsunterstützung im Produktionsumfeld T2 - Handbuch Digitalisierung Y1 - 2022 SN - 978-3-8006-6562-4 SP - 651 EP - 672 PB - Vahlen CY - München ER - TY - GEN A1 - Berneis, Moritz A1 - Winkler, Herwig T1 - Fallstudie zur Fabrikplanung im Greenfield. Teil 2: Lösungshinweise T2 - WiSt Wirtschaftswissenschaftliches Studium Y1 - 2022 U6 - https://doi.org/10.15358/0340-1650-2022-2-3-63 SN - 0340-1650 VL - 51 IS - 2-3 SP - 63 EP - 71 ER - TY - GEN A1 - Küpper, Christoph A1 - Rösch, Janina J. A1 - Winkler, Herwig T1 - Empirical findings for the usage of 5G as a basis for real time locating systems (RTLS) in the automotive industry T2 - Procedia CIRP Y1 - 2022 U6 - https://doi.org/10.1016/j.procir.2022.05.146 SN - 2212-8271 VL - 107 SP - 1287 EP - 1292 ER - TY - GEN A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - From Traditional Product Lifecycle Management Systems to Blockchain-Based Platforms T2 - Logistics N2 - Abstract: Background: Several product lifecycle management systems (PLMs) have been implemented in the industrial sector for managing the data of the product from the design up to the disposal or recycling stage. However, these PLMs face certain challenges in managing the complex and decentralized product lifecycles. Methods: To this aim, this work investigates the currently implemented PLMs used in industries through the exploration of various software reviews and selection websites. Accordingly, these existing PLMs are quantitatively compared and analyzed. Results: The analysis shows that most of the existing PLMs do not contain all the required features; therefore, industries integrate different software to create a full-fledged PLM system. However, this practice results in reducing the overall system efficiency. In this context, this paper assesses and recommends a blockchain-based innovative solution that overcomes the challenges of existing PLMs, hence increasing the overall system efficiency. Furthermore, this work argues, in a logical way, that the recommended blockchain-based platform provides a secure and connected infrastructure for data handling, processing, and storage at different stages of the product lifecycle. Conclusions: This work can be considered among the first to compare the currently implemented PLMs with a novel blockchainbased method. Thus, the stakeholders can utilize the outputs of this research in their analysis and decision-making processes for implementing the blockchain in their organizations. KW - product lifecycle management KW - blockchain technology KW - product development KW - decentralization KW - production system Y1 - 2022 U6 - https://doi.org/10.3390/logistics6030040 SN - 2305-6290 VL - 6 IS - 3 ER - TY - GEN A1 - Mielke, Jonas A1 - Winkler, Herwig T1 - Machine-Learning-Ansatz zur Produktionsauftragsplanung T2 - Zeitschrift für wirtschaftlichen Fabrikbetrieb N2 - Maschinelle Lernalgorithmen sind leistungsstarke Werkzeuge, um Muster und Wechselwirkungen in Datenstrukturen zu erkennen. Diese Fähigkeiten werden im Rahmen dieses Beitrags zur Optimierung der Auftragsplanung eines Produktionssystems genutzt. Dabei wird ein praxisnahes Vorgehen zur schnellen Evaluierung neuer Auftragssituationen vorgestellt. Die Datengrundlage bildet dabei ein Simulationsmodell eines realen Produktionssystems. Y1 - 2022 U6 - https://doi.org/10.1515/zwf-2022-1077 SN - 0947-0085 SN - 2511-0896 VL - 117 IS - 6 SP - 384 EP - 389 ER - TY - GEN A1 - Eberlein, Simeon A1 - Winkler, Herwig T1 - Die Blockchain Technologie (BCT) zur Verbesserung von Transaktionsprozessen in der Logistik T2 - Logistics Journal N2 - Blockchain-Technologie ist die Zukunft im Bereich sicherer Datenspeicherung und -nachverfolgung. Dabei wird diese Technologie schon lange nicht mehr nur bei Kryptowährungen eingesetzt. Viele Unternehmen arbeiten und entwickeln Lösungen, um mit der Blockchain-Technologie Prozessverbesserung in der Industrie zu realisieren. Vor allem Transaktionsprozesse in der Logistik können durch den Einsatz dieser Technologie optimiert werden. Demnach ist das Ziel dieses Artikels die Grundzüge der Blockchain Technologie darzulegen und aufzuzeigen, wo die Blockchain bereits genutzt wird und wie dadurch Logistikprozesse verbessert werden. Der Fokus dieses Beitrags liegt auf Blockchain-Anwendungen, die sich bereits in der Industrie etabliert haben. Es wird analysiert, wie diese Systeme aufgebaut sind, wie sie in der Praxis eingesetzt werden und welchen Verbesserungen mit ihnen zu realisieren sind. KW - Blockchain KW - Logistics KW - Smart Contracts KW - TradeLens KW - IBM Food Trust Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0009-14-55242 UR - https://www.logistics-journal.de/not-reviewed/2022/05/5524 SN - 1860-5923 SP - 1 EP - 11 ER - TY - GEN A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - An Analytic Hierarchy Process for Selection of Blockchain-Based Platform for Product Lifecycle Management T2 - Sustainability N2 - Blockchain technology has disrupted traditional business processes and hence gained significant attention and popularity in recent years. Consequently, a number of blockchain-based platforms are available today that offer vast applications across multiple sectors and industries. Implementing these blockchain-based platforms as an alternative to traditional product lifecycle management systems (PLMs) is one of the applications. However, before any platform is adopted, its nature, functionalities, and adaptability need to be clearly defined, evaluated, and verified. In this context, the proposed work explores the available blockchain-based platforms that can be used for the purpose of product lifecycle management. We then apply one of the multi-criteria decision-making techniques, i.e., the analytic hierarchy process (AHP), to select the best possible blockchain-based platform for PLM. As transaction speed, data privacy, and scalability are our prime concerns in PLM, we only considered the permissioned (private) blockchain platforms as available alternatives in the final selection process. Results achieved on the basis of considered criteria show that Hyperledger Fabric is the top-ranked among available alternatives to be used for PLM. Furthermore, as blockchain is a new technology, a clear comparison of the available platforms based on the performancebased metrics and key performance indicators is not completely matured and is still in the development stage. However, our proposed approach can be considered an attempt to create a procedure for evaluating blockchain-based platform implementation in any sector. KW - blockchain platforms KW - product lifecycle management KW - analytic hierarchy process industry 4.0 Y1 - 2022 U6 - https://doi.org/10.3390/su142113703 SN - 2071-1050 VL - 14 IS - 21 SP - 1 EP - 19 ER - TY - GEN A1 - Bartsch, Devis A1 - Winkler, Herwig T1 - Smart Order as a new Instrument for Production Control T2 - Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management : Innovative Approaches for the Shift to a New Era Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:830-882.0200550 SN - 978-3-756541-95-9 SP - 149 EP - 175 PB - epubli GmbH CY - Berlin ER - TY - GEN A1 - Küpper, Christoph A1 - Rösch, Janina J. A1 - Winkler, Herwig T1 - Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature review T2 - Journal for Production & Manufacturing N2 - Numerous challenges in automotive production lead to an increased need for transparency and optimization. Real-Time-Location-Systems (RTLS) is a key tool for achieving this goal. They enable intelligent and automated production processes. Existing solutions such as Ultra-Wideband, Bluetooth-Low-Energy, or Radio-Frequency-Identification have drawbacks in costs, range, or accuracy. 5G is a newly developing standard, recently including high-accuracy positioning. It is unclear, however, if 5G positioning has reached industrial maturity. This contribution aims to determine the state-of-the-art of 5G positioning by performing a systematic literature review and comparing its findings to industrial positioning requirements. 143 articles were analyzed and categorized as: the fundamentals of radio-frequency positioning, an overview of existing solutions, the state-of-the-art, and the maturity of 5G as an industrial positioning system. Results show that, theoretically, centimeter-level accuracies are pursued. However, practical tests are rarely conducted. Concluding, 5G positioning shows great potential, but industrial pilots are required to validate the theoretical characteristics. Y1 - 2022 U6 - https://doi.org/10.1080/21693277.2022.2144522 SN - 2169-3277 VL - 10 IS - 1 SP - 840 EP - 874 ER - TY - GEN A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - Exploring the Basic Features and Challenges of Traditional Product Lifecycle Management Systems T2 - 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) N2 - Product lifecycle management (PLM) is the strategic process of managing all the data of the product from the design up to its disposal or recycling stage. In product development, the PLM data is the key source for better decision-making at different stages of the product lifecycle. To this aim, several PLMs have been implemented in industrial sectors. Among these PLMs, each carries some common as well as certain distinct features and characteristics over its counterparts. However, due to the complex and decentralized nature of today’s product lifecycles, all of the currently implemented PLMs face certain challenges. In this context, various software reviews and selection websites have been explored to investigate the core functionalities as well as the challenges associated with the currently implemented PLMs. Moreover, this study analyzed that most of the existing PLMs do not contain all the required features and therefore, industries usually integrate different software to make a full-fledged PLM system. However, this practice results in reducing the overall system efficiency. Therefore, this study emphasizes that it is the need of the day to adopt a novel technology i.e. blockchain to overcome the PLM challenges and its consequences in the production industries. Y1 - 2022 SN - 978-1-6654-8687-3 SN - 978-1-6654-8688-0 U6 - https://doi.org/10.1109/IEEM55944.2022.9989978 SP - 0762 EP - 0766 ER - TY - GEN A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Hybrid Production Management System in the Context of Industry 4.0 T2 - 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) N2 - In our contribution, we consider how the Digital Twin of the production system can be combined with Artificial Intelligence methods. The result of these considerations should be a hybrid production management system, which can be used for decision support as well as for self-control. On the one hand, the Digital Twin is providing information and simulation for the optimal decision-making to the decision support system (human interaction). On the other hand, Artificial Intelligence is taking over some elements and tasks with automatic control (independent of human interaction). If the result is out of tolerance or if a random sample of the result is audited, the decision support system is validating the Artificial Intelligence result for execution (by human interaction). The hybrid production management system is to be used to control production processes and generates learning effects. The extension by methods of Artificial Intelligence opens possibilities to process and to master certain tasks independently of human interaction. The presented approach should relieve and support decision makers in production. By performing various actions automatically and achieving partial auto-control, the reactivity of linked processes can increase. The provision of decisive information favors decision quality and time-effectiveness. Y1 - 2022 SN - 978-1-6654-8687-3 SN - 978-1-6654-8688-0 U6 - https://doi.org/10.1109/IEEM55944.2022.9990000 SP - 1573 EP - 1577 ER - TY - RPRT A1 - König, Mathias A1 - Winkler, Herwig T1 - Digitalisierung in der Montage mit dem Schwerpunkt des Einsatzes von Assistenzsystemen Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-62121 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senfteberg ER - TY - GEN A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Empirical Findings on the Need of Industrial Production Management Systems in the Context of Enhanced Digitalization T2 - 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) N2 - Since the framework conditions of manufacturing companies change dynamically, production control must react to this and be adaptive and dynamically designed. Our article addresses the need of industrial production management systems in the course of enhanced digitization. The aim is to examine the extent to which traditional systems for controlling and optimizing production systems have been supplemented by Industry 4.0 concepts. In the course of the scarcity of resources and the shortage of labor, the human factor is once again coming to the fore. Against this background, the interaction between users / humans and artificial intelligence applications will be the main focus. The result should give an indicator how this connection must be considered in the future and what should artificial intelligence do in the context of production control. The findings will be the basis for future considerations of a smart production management system, which can be used for decision support as well as for auto-control. KW - Production Management System KW - Production Control KW - Manufacturing Control KW - Production KW - Industry 4.0 Y1 - 2023 SN - 979-8-3503-2315-3 SN - 979-8-3503-2316-0 U6 - https://doi.org/10.1109/IEEM58616.2023.10406474 SP - 1406 EP - 1410 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Empirical Findings on the Current State of Industrial Production Management Systems in the Context of Increasing Digitalization T2 - Industrial Engineering and Applications – Europe : 11th International Conference, ICIEA-EU 2024, Nice, France, January 10–12, 2024 N2 - Increasing digitization and automation are currently bringing a revolution to many processes and sectors of the economy. The industry of production in particular is undergoing a fundamental transformation through the implementation of digital and networked system elements. In production control, traditionally based on established methods and experience, advanced technologies such as artificial intelligence are opening up entirely new options. Artificial intelligence’s ability to analyze large amounts of data in real time and make instant decisions from it brings fresh perspectives to production control. Until now, there have been only a few surveys that examine the current status as well as future requirements for production control. Our research focuses on the current state of IT systems used to support decision-makers in production control. It also sheds light on the requirements needed to improve these systems, especially in light of advancing technological developments and increasing digitalization. The article is dedicated to the results and provides an overview of future expectations. Y1 - 2024 SN - 9783031581120 U6 - https://doi.org/10.1007/978-3-031-58113-7_3 SN - 1865-1348 SP - 23 EP - 34 PB - Springer Nature Switzerland CY - Cham ER - TY - GEN A1 - Berneis, Moritz A1 - Winkler, Herwig A1 - Abdelkafi, Nizar T1 - Insights from interviews with German supply chain managers: a study of supply chain transformations and emerging issues T2 - Procedia Computer Science N2 - To investigate current trends and challenges related to supply chain management in Germany, we conduct an interview-based study involving 16 experts. The study focuses on three areas: supply chain transformations, software challenges, and the adoption of emerging technologies. Supply chain transformations are influenced by increasing supply chain complexity, the growing prevalence of e-commerce, and the increased importance allocated by customers to trust and transparency. Complexity is, in part, due to disruptions caused by policy responses to the pandemic and to software challenges in terms of the adaptability of ERP systems and the cybersecurity of cloud-based solutions. This study is relevant for practitioners, as it sheds light on pressing issues in supply chain management, and for researchers as it uncovers potential topics that require further research in the future. KW - Supply Chain Management (SCM) Interviews KW - Emerging Technologies KW - German Companies KW - Digitalization KW - Trends KW - Interviews Y1 - 2024 UR - https://authors.elsevier.com/sd/article/S1877-0509(24)00106-6 U6 - https://doi.org/10.1016/j.procs.2024.01.106 SN - 1877-0509 VL - Vol. 232 SP - 1079 EP - 1088 ER - TY - CHAP A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Überlegungen zur Konzeption eines smarten Produktionsleitsystems T2 - Handbuch Industrie 4.0 und Digitale Transformation Y1 - 2024 SN - 978-3-658-36874-6 U6 - https://doi.org/10.1007/978-3-658-36874-6_17-1 PB - Springer Gabler CY - Wiesbaden ER - TY - GEN A1 - Singh, Amita A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - Deriving principles from participatory modelling to augment circularity and sustainability in EV battery lifecycle T2 - Procedia CIRP N2 - Very often circularity and sustainability go hand-in-hand. This paper is focused on understanding the key criteria of how circularity and hence sustainability can be increased in the field of electric vehicle (EV) batteries. Literature shows that only 2-5% of Lithium Ion Batteries (LIB) are recycled resulting in a huge number of not properly disposed batteries. This is harmful not only to the environment but also has adverse effects on the population of the area where the minerals are mined disturbing the triple bottom line of sustainability. Through this paper, we propose a holistic approach to tackle the problem by not only using technology but also including systematic input from different stakeholders through the lifecycle. We, thus, combine principles from participatory modelling and blockchain technology to bring transparency and accountability in the process. This approach is a step-by-step guideline for including circularity and sustainability through a continuous process of input collection from real life and validation in the real world thereby resulting in a practical and technologically adept solution yielding better results when compared to a solution developed in an isolated laboratory environment. In this paper, we discuss the guidelines for the process together with input data collection, method, process validation, and resulting document in each step. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/j.procir.2024.10.120 SN - 2212-8271 IS - 130 SP - 498 EP - 503 ER - TY - GEN A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Evaluation of Future Enhancement Requirements in Production Control with Regard to the Deployment of Artificial Intelligence T2 - Proceedings of the 11th International Conference on Industrial Engineering and Applications N2 - In an age when digitization and the integration of artificial intelligence in production processes are becoming increasingly important, the selection and prioritization in the enhancement of production control functions has become a key challenge for companies. This article is dedicated to the application of the Analytic Hierarchy Process for the systematic selection and prioritization of enhancement options in production control, based on findings and data from empirical studies that examined the status quo and future needs. The focus is on structuring and weighting future enhancements. The findings are used for future considerations of a smart production management system that can be used for decision support as well as for auto-control. Y1 - 2024 SN - 978-981-9764-92-1 U6 - https://doi.org/10.1007/978-981-97-6492-1_7 SN - 2195-4356 SP - 79 EP - 91 PB - Springer Nature Singapore CY - Singapore ER - TY - GEN A1 - König, Mathias A1 - Winkler, Herwig T1 - Investigation of assistance systems in assembly in the context of digitalization: a systematic literature review T2 - Journal of Manufacturing Systems N2 - Assistance systems play a crucial role in enhancing working conditions and efficiency in industrial assembly. In the context of Industry 4.0, it is important to determine the types of assistance systems that contribute to assembly goals as well as their economic benefits. First, the significance of the topic will be introduced, and the research questions will be presented. Second, the basic technical terms will be defined, and third, the research methodology of a structured literature review (SLR) will be delineated. The fourth section presents an overview of the ergonomic and information assistance systems used in operational practice and academic test set-ups. It further explains the reasons for using assistance systems in assembly and their economic benefits, particularly in terms of reducing assembly times and errors. In the fifth section, the research perspectives of the respective publications are evaluated and summarized in both a qualitative and quantitative way. The present mixed-methods study is not generalizable due to its limitations such as a small sample size, the geographical scope of the study, type of databanks, time of publication and language of the reviewed articles, and methods of data collection. It does, however, identify potential areas for future research and provide recommendations for further investigation. KW - AssemblyIndustry 4.0Assistance systemsDigitalization Y1 - 2025 U6 - https://doi.org/10.1016/j.jmsy.2024.11.015 SN - 0278-6125 VL - 78 SP - 187 EP - 199 PB - Elsevier BV ER - TY - GEN A1 - Mielke, Jonas A1 - Winkler, Herwig T1 - A reference architecture for the application of machine leaning algorithms in production planning and control T2 - Procedia CIRP N2 - The organization of complex production systems in enterprises poses major challenges for decision-makers in production planning and control (PPC). Especially the volatility of planning scenarios and the associated demand for short-cycle adaptation of decisions requires methods that enable fast and reliable evaluations. This article presents a system architecture that addresses these challenges holistically. The system architecture uses real production data to generate scenario-based value stream simulations, which are subsequently used to train machine learning algorithms. The trained models enable a holistic evaluation of new production scenarios. Finally, decisions can be made for the real production environment based on reliable knowledge. KW - Production planningcontrolmachine learningvalue stream simulationproduction datasystem architecturefast decision-making processes Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2024.10.059 VL - 130 SP - 79 EP - 85 PB - Elsevier BV ER - TY - GEN A1 - Mielke, Jonas A1 - Winkler, Herwig T1 - Application of machine learning algorithms for the evaluation of employee qualification matrices in complex production systems T2 - Procedia CIRP N2 - Machine learning (ML) methods are powerful tools for the rapid and targeted evaluation of large data volumes. Especially in the area of production planning and control (PPC), there is huge potential for making the operational and strategic organization of production systems more efficient. However, in order to achieve these objectives, practical research contributions are required that focus on the actual boundary conditions of PPC. This article presents the practical evaluation of qualification matrices using the gradient boosting method and cross-validation to determine the influence of data splitting and selection on prediction accuracy to demonstrate the usability of the system. KW - machine learningproduction planningcontrolpersonnel qualificationcontrol systemcomplex production systemsproduction data Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2024.10.058 SN - 2212-8271 VL - 130 SP - 72 EP - 78 PB - Elsevier BV ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig A1 - Abdelkafi, Nizar A1 - Lange, Hans-Rüdiger T1 - Paving the Green Path: a Maturity Model for Digital Decarbonization T2 - Procedia CIRP N2 - Digital transformation has been employed across all industries to enhance business operations. Its potential lies in optimising existing business models and creating innovative ones based on various technologies, making them fit for the future by reducing greenhouse gas emissions and fulfilling future decarbonization goals. In order to ensure a successful digital transformation towards decarbonization, managers have to assess the capabilities of their organisation and competently oversee their journey by defining a clear path employing digital maturity models. For this purpose, the analysis focused on published literature concerning digital maturity models developed to guide organisations in navigating their digital transformation journey. A systematic literature review of 36 selected digital maturity models is presented in this paper. These models overlook decarbonisation measures and focus solely on demonstrating digital capabilities, efficiency and profit growth. Therefore, a maturity model for digital decarbonization encompassing dimensions of decarbonization goals, business model innovation, customers and suppliers, products and services, employees, collaboration, processes and activities, data, and IT-infrastructure, -security and -technology has been developed. It assists organisations in reducing their carbon footprint by strategically and effectively leveraging digital technologies. The proposed model has five maturity levels: assess and align, engage and refine, innovate and collaborate, optimize and personalize, and transform and decarbonize. This paper aims to assess the current level of digital decarbonization and determine the position of the organizations. Additionally, it endeavours to identify the specific opportunities for growth that digitalization presents, thereby enabling the creation of a new digital carbon-free existence. KW - Maturity Model KW - Digital Decarbonization KW - Digital Transformation KW - Review Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/j.procir.2024.10.201 SN - 2212-8271 VL - 130 SP - 1020 EP - 1027 ER - TY - GEN A1 - Hayat, Mubashir A1 - Winkler, Herwig T1 - Blockchain-based Order Management Process in Decentralized Production Networks: A Conceptual Framework T2 - Procedia CIRP N2 - In today's world of decentralized production, original equipment manufacturers (OEMs) are facing more than ever an increasing complexity in their order management processes. On the one hand, they deal with issues related to data transparency, traceability, and security in constant back-and-forth communication exchange between customers and sub-contractors having to confirm the order status. On the other hand, there are significant obstacles when it comes to integrating their traditional order management systems with the partner organization's information systems within the production network. These complexities tend to decrease the ability of OEMs to remain flexible and profitable. Therefore, they are constantly looking for feasible solutions to overcome these issues and improve their order management processes. To this aim, this work proposes a novel blockchain-based conceptual framework for order management that intends to establish a secure environment for efficient communication and data integrity. The decentralized and immutable nature of blockchain makes it capable of providing real-time data as well as ensuring data security and transparency. Furthermore, this work also set up basic level SQLite3 databases and design prototypical on-chain and off-chain smart contract logics that can be used to automate various operations and decisions making in order management, thereby, improving the overall order processing efficiency. According to the authors knowledge, there is no such framework available in research. Therefore, it is suggested that organization can utilize the proposed framework to develop their own blockchain based order management systems. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/j.procir.2024.10.218 SN - 2212-8271 IS - 130 SP - 1137 EP - 1143 ER - TY - GEN A1 - Eichenseer, Patrick A1 - Winkler, Herwig T1 - Predicting picking and workforce planning for internal shopfloor material logistics – a simulative, data-driven forecasting model T2 - Journal of Modelling in Management N2 - Purpose With increasing demands for competitiveness, demand fulfilment and cost efficiency, the need to optimise workforce planning in logistics has become crucial. This applies not only to external customer demands, but also to internal customers, i.e. production. For this reason, the purpose of this paper is to develop a simulative, data-driven model that predicts the internal shopfloor material logistics demands. Design/methodology/approach It is a hybrid approach that includes both deterministic and probabilistic components and is an alternative to advanced but data and knowledge-dependent machine learning algorithms. Inductive, self-developed procedures, heuristic calculation rules and consideration of real-world factors form the basis of the prediction of the number of picks. The number of picks predicted in the first step forms the basis for deriving the number of employees required in the second step, and thus the basis for optimised workforce planning. The developed approach was then validated in a case study in a real company. Findings The results show that the model significantly optimises not only the planning efficiency, but also the forecasting effectiveness through better decision making in demand prediction and workforce planning in internal shopfloor material logistics compared to the status quo on a weekly basis (95.5% accuracy in the case study). This improved decision making leads to increased efficiency throughout the intralogistics/production system. Originality/value A structured approach is described for systematically predicting the number of internal picks, which is highly relevant in practice and cannot be found in the existing literature (from the data model to the calculation rules, including statistical influencing factors, to the prediction). In terms of future research, the model has the potential to be used and validated in additional companies. KW - Data KW - Logistics KW - Workforce planning KW - Forecast KW - Picking KW - Shopfloor Y1 - 2024 U6 - https://doi.org/10.1108/jm2-09-2024-0288 SN - 1746-5664 VL - 2024 PB - Emerald ER - TY - GEN A1 - Eichenseer, Patrick A1 - Hans, Lukas A1 - Winkler, Herwig T1 - A data-driven machine learning model for forecasting delivery positions in logistics for workforce planning T2 - Supply Chain Analytics N2 - Workforce planning in logistics is a major challenge due to increasing demands and a dynamic environment. The number of delivery positions is a key factor in determining staffing requirements. This is often predicted subjectively based on employee assessments. To improve decision making and increase both the efficiency of this important forecasting process and the use of resources in the production system, i.e. shopfloor logistics, a data-driven machine learning model with a forecasting horizon of 5 working days was developed and validated in a practical case study in a company. The results show that the novel and specifically developed model outperforms both the manual forecasting approach in practice and auto machine learning models in terms of accuracy. The outperformance is particularly strong in the short term. Based on the predicted delivery positions, an optimised workforce planning was subsequently carried out in the case study company. Limitations of the model include the fact that it was validated in only one company and that the number of picks may need to be derived for more accurate scheduling. These two aspects also represent potential for future research. KW - Delivery Positions KW - Forecasting KW - Logistics KW - Workforce Planning KW - Machine Learning KW - Picks Y1 - 2025 U6 - https://doi.org/10.1016/j.sca.2024.100099 SN - 2949-8635 VL - 9 (2025) PB - Elsevier BV ER - TY - GEN A1 - Lamann, Arian A1 - Winkler, Herwig A1 - Lange, Hans-Rüdiger A1 - Abdelkafi, Nizar T1 - Identification and analysis of barriers in co-innovation projects in the manufacturing and energy industry T2 - Procedia CIRP N2 - Innovation is critical to a company’s growth in today’s competitive environment. Co-innovation projects, where companies pool resources, represent a promising way to achieve this goal. This study, based on a focus group of industry experts from the manufacturing and energy sectors, aims to identify the challenges of such collaborations and propose suitable solutions. The study relies on the innovation phase model and identifies several obstacles such as short technology lifecycles, data management overload, and organizational shortcomings in co-innovation projects. Effective management, communication and intellectual property (IP) can be a significant challenge in co-innovation projects, particularly due to uncertainties surrounding the release of sensitive data and inadequate contractual support. Uncoordinated communication can also result in project delays or failure. Furthermore, the absence of access protocols for online applications presents risks such as unauthorized access and document change tracking issues, further complicating complex engineering projects. Despite the availability of digital providers, many of them still require physical platforms for efficient innovation projects due to insufficient support for e.g., data management and caused by communication limitations. In conclusion, this study emphasizes the urgent need for research on co-innovation projects and recommends a collaborative framework to address the complexities triggered by this kind of projects and increase collaboration effectiveness. Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2024.10.248 SN - 2212-8271 VL - 130 (2024) SP - 1334 EP - 1339 PB - Elsevier BV ER - TY - CHAP A1 - Winkler, Herwig A1 - Tomenendal, Matthias A1 - Abdelkafi, Nizar A1 - Lange, Hans-Rüdiger ED - Zhang, Michael T1 - Managing the coal exit in a mining region - Strategic landscape design and niche management for a sustainable socio-technical regime in Lusatia T2 - Strategic management and sustainability transitions - Theory and Practice N2 - In the course of the European Green Deal, which defines the goal of “no net emissions of greenhouse gases in 2050” (European Commission, 2019, p. 2) and a supply of “clean, affordable and secure energy” (p. 3), the European energy sector needs a rapid and significant sustainability transition. In Germany, the federal government has accordingly decided to phase out energy production from lignite-fired power plants by 2038 at the latest. Most affected regional ecosystems in Germany are the Lusatia mining region (Lausitzer Revier), the Rhenish mining region (Rheinisches Revier) and the Middle German mining region (Mitteldeutsches Revier). In these regions, fundamental sustainability transitions have to take place. Y1 - 2024 SN - 9781003329909 U6 - https://doi.org/10.4324/9781003329909-7 SP - 83 EP - 118 PB - Routledge CY - New York ET - 1st Edition ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - Unlocking the power of digital technology for fostering sustainability T2 - IEEE Student Conference on Research and Development N2 - In the pursuit of economic, social and environmental sustainability, digital technologies have the potential to become powerful tools that provide innovative solutions for the reduction of greenhouse gas emissions and the mitigation of the effects of climate change. Therefore, it is essential to understand how digital technologies can drive or inhibit the sustainability endeavors of firms. For this purpose, we systematically analyze the literature published during the last five years to feature how digitalization could contribute to the achievement of a more sustainable future. The study provides key findings on the potential applications of digital technologies in promoting and contributing to sustainability and presents a roadmap for adopting digital technologies. It also highlights the challenges and barriers faced by different industries in realizing the full potential of these technologies as drivers of sustainable development as well as identifies future directions. KW - Sustainability KW - Digitalization KW - Digital Technology KW - Industry 4.0 KW - A Systematic Literature Review Y1 - 2024 UR - https://ieeexplore.ieee.org/document/10563721 SN - 979-8-3503-1882-1 U6 - https://doi.org/https://doi.org/10.1109/SCOReD60679.2023.10563721 SP - 57 EP - 64 ER - TY - GEN A1 - Abdulghani, Tamer A1 - Winkler, Herwig T1 - Managing the decarbonization of coal-based energy value chain: empirical findings from Lusatia, Germany T2 - IEEE Student Conference on Research and Development N2 - Decarbonization is causing structural changes that exert pressure not only on the companies and their employees in the lignite industry, but also on other companies along the value chain across multiple sectors. As a result, companies have an urgent need for change. They are challenged to take action to build a sustainable new existence as the markets collapse. For this purpose, we investigate the structural changes due to decarbonization and what factors can be part of a successful business transformation to manage the decarbonization of the coal-based energy value chain. This paper presents empirical insights from several semi-structured interviews with the key actors i.e., energy companies, service providers, logistics companies, suppliers, etc. in the Lusatia mining region as well as a conceptual model for a successful business transformation in the region. We used the Gioia method to analyze the interview data in order to obtain a meaningful data structure. This resulted in a conceptual model that shows how success factors have to be combined to manage the decarbonization measures within a region. KW - Decarbonization KW - Coal Phase-out KW - Energy Value Chain KW - Structural Change KW - Case Study KW - Digitalization Y1 - 2024 UR - https://ieeexplore.ieee.org/document/10563936 U6 - https://doi.org/https://doi.org/10.1109/SCOReD60679.2023.10563936 SP - 307 EP - 315 ER - TY - GEN A1 - Eichenseer, Patrick A1 - Winkler, Herwig T1 - A data-oriented shopfloor management in the production context: a systematic literature review T2 - The International Journal of Advanced Manufacturing Technology N2 - AbstractData not only plays an essential role in traditional shopfloor management, but it is also becoming even more important in Industry 4.0, particularly due to the increasing possibilities offered by new digital and data technologies and developments. In this context, the literature often refers to digital shopfloor management, the next generation shopfloor or other evolutionary synonyms. This raises the question of how to differentiate the content of data-oriented shopfloor management from digital shopfloor management. This paper discusses the state of the art — in terms of both data and digital perspectives — using a systematic literature review. Due to the complexity of the topic, three different levels of consideration — technology, organisation and people — are examined and discussed. Existing conceptual approaches are analysed in terms of conclusions and research gaps. It was found that the area of technology, including dedicated applications, is very well represented and researched in the literatur Y1 - 2024 U6 - https://doi.org/10.1007/s00170-024-14238-8 SN - 0268-3768 VL - 134 SP - 4071 EP - 4097 PB - Springer Science and Business Media LLC ER - TY - RPRT A1 - Berneis, Moritz A1 - Winkler, Herwig T1 - Untersuchung von aktuellen Trends und Herausforderungen im Supply Chain Management in Deutschland N2 - ▪Im Zeitraum von November 2022 bis Januar 2023 wurde am Lehrstuhl für Produktionswirtschaft der BTU Cottbus-Senftenberg die Studie mit dem Titel „Untersuchung von aktuellen Trends und Herausforderungen im SCM deutscher Unternehmen“ durchgeführt. Es wurden dazu Interviews mit über 20 Experten durchgeführt. 16 Interviews wurden ausgewertet. ▪ Im ersten Themenkomplex wurden aktuelle Ereignisse untersucht. Die häufigsten Herausforderungen sind demnach die Ressourcenverfügbarkeit, lange Lieferzeiten, der Fachkräftemangel und preisgetriebene Themen. Experten wurden zu aktuellen Ereignissen befragt, wie Rohstoffpreisschwankungen, der Zero-Covid-Strategie von China und Knappheiten in der Logistik. Preisschwankungen betrafen die meisten Unternehmen, während Krieg und Sanktionen nur indirekt wirkten. Die Zero-Covid-Strategie führte zu Vertrauensverlust in China und Knappheiten in der Logistik zu höheren Transportkosten. Der Fachkräftemangel wurde auch als aktuelles Ereignis genannt. ▪ Der zweite Themenkomplex ist Veränderungen im SCM gewidmet. Dabei wurde insbesondere der Wandel in komplexere Netzwerke, der Aufstieg des E-Commerce und die Bedeutung von Vertrauen und Transparenz angeführt als wesentliche Veränderungen. Supply Chains sind gewachsen und komplexer geworden, aber auch die Qualität der Vernetzung hat sich verbessert. E-Commerce für Standardprodukte wird weiter an Relevanz gewinnen. Kein Trend zur Deglobalisierung wurde festgestellt. Die Experten sind sich einig, dass Supply Chains "too lean" geworden sind und das Risikomanagement wichtiger ist. Das oberste Ziel sollte sein, die Produktion und Lieferfähigkeit sicherzustellen. ▪ Der dritte Themenkomplex befasst sich mit Nachhaltigkeit, einschließlich des Lieferkettengesetzes (LkSG), Dekarbonisierung und Nachhaltigkeitsnachweisen. Die meisten Unternehmen erfüllen die Anforderungen des LkSG und nehmen das Gesetz als Klausel in Verträgen auf. Bürokratie in Deutschland führt zu hohen Kosten, besonders für kleine Unternehmen. Kosteneinsparungen sind der größte Treiber bei der Dekarbonisierung. Nachhaltigkeit wird immer wichtiger und kann über Zertifikate nachgewiesen werden. ▪ Im vierten Themenkomplex Software wurde die Anpassungsfähigkeit von ERP-Systemen bemängelt und automatische Bestellungen wurden kontrovers betrachtet. Die meisten Experten verzichten aus Sicherheitsgründen auf Cloud-basierte Lösungen aufgrund des hohen Risikos für Cyberangriffe und möglicher Gefahren für die Supply Chain. ▪ In Themenkomplex fünf wurden neue Technologien im SCM besprochen. AR wird für die Wartung von Maschinen eingesetzt und VR für Simulation und Planung. IoT wird für predictive Maintenance genutzt, Treiber der Automatisierung ist der Fachkräftemangel. Big Data & AI sollen die Vorhersage der Nachfrage verbessern. Additive Fertigung hat Potenzial für Automatisierung und sinkende Kosten. Die Blockchain gilt als komplex und kann als geteilte Datenbank, Zahlungssystem und zur Rechnungsteilung dienen. ▪ Im sechsten Themenkomplex Sichtbarkeit halten Experten Transparenz für wichtig, sie ist noch zu gering aber bietet Potenzial zur Erkennung von Risiken. Tracking und Tracing ist intern verbreitet, international gibt es noch Probleme. Eine höhere Zahlungsbereitschaft der Kunden für Sichtbarkeit besteht nicht, diese entsteht nur für einen besseren Service. KW - Herausforderungen KW - Logistik KW - Logistics KW - Supply Chain Management KW - Trends KW - Challenges KW - Interview Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-62950 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senftenberg ER - TY - GEN A1 - Huber, Tobias A1 - Winkler, Herwig T1 - Fehlerprognose in der Automobilmontage. Einsatz eines überwachten Lernalgorithmus zur fahrzeug- und stationsbezogenen Fehlerprognose T2 - Zeitschrift für wirtschaftlichen Fabrikbetrieb N2 - Die Automobilmontage ist aktuell von der Produktvarianz und dem Faktor Mensch geprägt, sodass diese bisher – trotz zahlreicher präventiver Maßnahmen – nicht gänzlich fehlerfrei gestaltet werden konnte. Mit dem Ziel, jene Fehler prognostizieren zu können, wurde ein Klassifikationsmodell aus dem Bereich des überwachten maschinellen Lernens trainiert und über einen dreimonatigen Zeitraum validiert. Während dieses Zeitraums konnten rund 60 Prozent der relevanten Fehler korrekt vorhergesagt werden. KW - Automobilindustrie KW - Automobilmontage KW - Maschinelles Lernen KW - Klassifikation KW - Montagefehler KW - Fehlervorhersage Y1 - 2022 U6 - https://doi.org/10.1515/zwf-2022-1042 SN - 0947-0085 SN - 0932-0482 VL - 117 IS - 4 SP - 192 EP - 199 ER - TY - GEN A1 - Stockmann, Christian A1 - Winkler, Herwig T1 - Robustness in production systems – findings from a systematic literature review T2 - International Journal of Services and Operations Management N2 - In production systems, the concept of robustness is widespread due to various applications, purposes, and interpretations. However, little is known about the conceptual characteristics of robustness in production settings and even less about its distinctions from other related terms – such as flexibility or agility. That is why this paper systematically reviews production literature to identify the contexts in which robustness is mostly applied and to analyse existing concepts. It is found that despite a vast literature body addressing robustness in varying forms, few studies cover it on a conceptual basis. Within this small sample, a rather general agreement on the meaning of robustness in production systems is found. However, details, interpretations, mentioned interlinkages to related terms differ across the identified literature. Based on the findings of the review and with the help of established literature on adjacent concepts, a comprehensive understanding of robustness in production systems is developed. KW - robustness KW - production management KW - production systems KW - operations management KW - flexibility KW - resilience KW - resistance KW - changeability Y1 - 2023 UR - https://www.inderscienceonline.com/doi/10.1504/IJSOM.2023.129462 U6 - https://doi.org/10.1504/IJSOM.2023.129462 SN - 1744-2370 SN - 1744-2389 VL - 44 IS - 3 SP - 368 EP - 389 ER - TY - RPRT A1 - Hoffmann, Stefanie A1 - Thomas, Kevin A1 - Winkler, Herwig T1 - Technologische Trends und Entwicklungen bei alternativen Energiesystemen Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-64847 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senftenberg ER - TY - RPRT A1 - Schmid, Stefan A1 - Winkler, Herwig T1 - Die Produktionssteuerung im digitalen Zeitalter aus Sicht der industriellen Praxis N2 - -Im Zeitraum von März bis Juni 2023 wurde vom Lehrstuhl für Produktionswirtschaft der BTU Cottbus Senftenberg die Studie mit dem Titel „Die Produktionssteuerung im digitalen Zeitalter“ als Online Umfrage durchgeführt. 125 Personen mit operativen, planerischen und strategischen Funktionen in der Produktion oder des produktionsnahen Umfeldes beantworteten den Fragebogen - Die Studie zeigt, dass bei vielen Praktikern ein sehr klares Bild vorherrscht, was die Produktionssteuerung der Zukunft leisten muss - Die Erweiterung der Produktionssteuerung um Künstliche Intelligenz wird in sehr starkem Maße als sinnvoll erachtet, um die Effizienz am Shop Floor bei hoher Komplexität der Leistungsprozesse auch in Zukunft aufrechtzuerhalten. - Die ausgewerteten Daten zeigen, dass die aktuellen Systeme der Produktionssteuerung die Nutzer nicht in dem Ausmaß unterstützen, wie es erwartet wird. Die Nutzer sind gefordert, ihr Wissen und ihre Kompetenzen einzusetzen, um funktionale Defizite der Anwendungen zu kompensieren - Die Kooperation von Mensch und KI in der Produktionssteuerung wird als sinnvoll angesehen. Dabei wird eine Kombination aus menschlicher Arbeit und KI Unterstützung bevorzugt, während eine vollautonome KI seltener favorisiert wird. Die Studienergebnisse zeigen eine wachsende Zustimmung und Offenheit für den Einsatz von KI als Werkzeug in der Produktionssteuerung, jedoch unter menschlicher Aufsicht und Beteiligung - Die Herausforderungen der Integration von Künstlicher Intelligenz in die Mensch Maschine Interaktion umfassen technische und soziale Aspekte. Um diesen Herausforderungen zu begegnen, sind geeignete Lösungsansätze notwendig, wie die Entwicklung sicherer Schnittstellen, robuste Datenschutzmaßnahmen aber auch Nutzerakzeptanzförderung durch Aufklärung und Schulung - Innerhalb eines hybriden Rahmens, wo der Mensch mit der KI arbeitet, müssen klare Regeln für die Interaktion definiert werden. Die KI soll die menschliche Entscheidungsfindung interaktiv unterstützen, neue Perspektiven bieten und alternative Vorschläge unterbreiten. - Insgesamt betonen die Ergebnisse der Umfrage die Bedeutung von Sicherheit, Transparenz, Kontrolle und die Validierung von KI Entscheidungen durch menschliche Akteure. Es zeigt sich, dass die Kombination von Mensch und KI nicht nur technologische Vorteile bietet, sondern auch dazu beitragen kann, nachhaltig wirtschaftlichere Ergebnisse zu erzielen. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-65009 PB - Brandenburgische Technische Universität, IKMZ, Universitätsbibliothek CY - Cottbus ; Senftenberg ER - 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 - TY - GEN A1 - Abdulghani, Tamer A1 - Tugra Yilmaz, Oguzkan A1 - Winkler, Herwig T1 - The role of information sharing in supply chain collaboration : impacts and emerging opportunities T2 - Procedia computer science N2 - Effective supply chain management is essential for competitive advantage in an increasingly complex global marketplace, and information sharing between partners is becoming a strategic necessity. This paper aims to investigate information sharing practices within the supply chain of the fast-moving consumer goods sector. Specifically, it explores the challenges associated with these practices and their influence on collaboration among partners. Additionally, it analyzes the practical effects of technology and Industry 4.0 on these processes, emphasizing their impact on enhancing or reconfiguring supply chain collaboration. As a methodological approach, semi-structured interviews were conducted with three key supply chain actors: a supplier, a logistics service provider, and a retailer. The Gioia method was employed to analyze the interview data, thereby generating a meaningful data structure. This resulted in a conceptual model demonstrating the relationship between information sharing and collaborative supply chain performance, providing practical insights for enhancing integration. KW - Information sharing KW - Supply chain collaborations KW - Opportunities KW - Conceptual model Y1 - 2026 U6 - https://doi.org/10.1016/j.procs.2026.02.224 SN - 1877-0509 VL - 277 SP - 1859 EP - 1868 PB - Elsevier BV CY - Amsterdam ER - TY - GEN A1 - Hayat, Mubashir A1 - Rüster, Moritz A1 - Winkler, Herwig T1 - AI-based maintenance order planning and control of trains : status quo and conceptual considerations T2 - Procedia computer science N2 - Maintenance of trains 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 the railway sector. 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 work presents a conceptual framework designed to enhance maintenance order planning and control in train 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. The framework remains conceptual at this stage, which is the main limitation of the work; however, as future work, its practical effectiveness will be explored through implementation in trains maintenance workshop and empirical validation. KW - Artificial intelligence KW - Maintenance planning KW - Maintenance control KW - Conceptual framework KW - Train maintenance Y1 - 2026 U6 - https://doi.org/10.1016/j.procs.2026.02.286 SN - 1877-0509 VL - 277 SP - 2495 EP - 2504 PB - Elsevier BV CY - Amsterdam ER -