@misc{EichenseerWinkler, author = {Eichenseer, Patrick and Winkler, Herwig}, title = {A data-oriented shopfloor management in the production context: a systematic literature review}, series = {The International Journal of Advanced Manufacturing Technology}, volume = {134}, journal = {The International Journal of Advanced Manufacturing Technology}, publisher = {Springer Science and Business Media LLC}, issn = {0268-3768}, doi = {10.1007/s00170-024-14238-8}, pages = {4071 -- 4097}, abstract = {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}, language = {en} } @misc{HuberWinkler, author = {Huber, Tobias and Winkler, Herwig}, title = {Fehlerprognose in der Automobilmontage. Einsatz eines {\"u}berwachten Lernalgorithmus zur fahrzeug- und stationsbezogenen Fehlerprognose}, series = {Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb}, volume = {117}, journal = {Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb}, number = {4}, issn = {0947-0085}, doi = {10.1515/zwf-2022-1042}, pages = {192 -- 199}, abstract = {Die Automobilmontage ist aktuell von der Produktvarianz und dem Faktor Mensch gepr{\"a}gt, sodass diese bisher - trotz zahlreicher pr{\"a}ventiver Maßnahmen - nicht g{\"a}nzlich fehlerfrei gestaltet werden konnte. Mit dem Ziel, jene Fehler prognostizieren zu k{\"o}nnen, wurde ein Klassifikationsmodell aus dem Bereich des {\"u}berwachten maschinellen Lernens trainiert und {\"u}ber einen dreimonatigen Zeitraum validiert. W{\"a}hrend dieses Zeitraums konnten rund 60 Prozent der relevanten Fehler korrekt vorhergesagt werden.}, language = {de} } @misc{StockmannWinkler, author = {Stockmann, Christian and Winkler, Herwig}, title = {Robustness in production systems - findings from a systematic literature review}, series = {International Journal of Services and Operations Management}, volume = {44}, journal = {International Journal of Services and Operations Management}, number = {3}, issn = {1744-2370}, doi = {10.1504/IJSOM.2023.129462}, pages = {368 -- 389}, abstract = {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.}, language = {en} } @misc{HayatWinkler, author = {Hayat, Mubashir and Winkler, Herwig}, title = {Blockchain Adoption in Product Lifecycle Management: Challenges and Potential Directions}, series = {Procedia CIRP}, volume = {120}, journal = {Procedia CIRP}, issn = {2212-8271}, doi = {10.1016/j.procir.2023.08.022}, pages = {117 -- 122}, abstract = {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.}, language = {en} } @misc{BartschWinkler, author = {Bartsch, Devis and Winkler, Herwig}, title = {A new Instrument for Production Control: The Smart Order Concept}, series = {Procedia CIRP}, volume = {120}, journal = {Procedia CIRP}, issn = {2212-8271}, doi = {10.1016/j.procir.2023.09.037}, pages = {559 -- 564}, abstract = {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.}, language = {en} } @misc{BerneisWinkler, author = {Berneis, Moritz and Winkler, Herwig}, title = {Matching supply chain management challenges with blockchain applications}, series = {Supply Chain Management: An International Journal}, volume = {29}, journal = {Supply Chain Management: An International Journal}, number = {6}, publisher = {Emerald}, issn = {1359-8546}, doi = {10.1108/SCM-12-2023-0615}, pages = {1063 -- 1077}, abstract = {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}, language = {en} } @misc{AbdulghaniWinkler, author = {Abdulghani, Tamer and Winkler, Herwig}, title = {Transition Towards a Green Future: Upgrading a Digital Decarbonization Maturity Model}, series = {Procedia Computer Science}, volume = {253}, journal = {Procedia Computer Science}, issn = {1877-0509}, doi = {https://doi.org/10.1016/j.procs.2025.01.192}, pages = {1303 -- 1312}, abstract = {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.}, language = {en} } @misc{KoenigWinkler, author = {K{\"o}nig, Mathias and Winkler, Herwig}, title = {Montage im Wandel : empirische Ergebnisse der Digitalisierung}, series = {Industry 4.0 Science}, volume = {41. Jahrgang}, journal = {Industry 4.0 Science}, number = {1}, issn = {2942-6154}, pages = {42 -- 49}, abstract = {Die Montage bildet einen zentralen Bestandteil der industriellen Fertigung und ist traditionell von einem hohen Anteil manueller Arbeit gepr{\"a}gt. Unternehmen sehen in der Digitalisierung eine große wirtschaftliche Chance. Im Fokus steht dabei, die Produktivit{\"a}t der Mitarbeitenden zu steigern und gleichzeitig die Lohnst{\"u}ckkosten stabil zu halten. Die Nutzung innovativer Technologien wird deshalb immer wichtiger, um diese Ziele in der Montage umzusetzen}, language = {de} } @misc{BartschWinkler, author = {Bartsch, Devis and Winkler, Herwig}, title = {Produktionssteuerungsumgebungen und ihre (technischen) Probleme}, series = {Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb}, volume = {119}, journal = {Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb}, number = {10}, publisher = {Walter de Gruyter GmbH}, issn = {2511-0896}, doi = {10.1515/zwf-2024-1145}, pages = {710 -- 719}, abstract = {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}, language = {en} } @misc{LamannWinklerLangeetal., author = {Lamann, Arian and Winkler, Herwig and Lange, Hans R{\"u}diger and Abdelkafi, Nizar}, title = {Co-innovation tools, mechanisms and methods : status quo and potentials}, series = {Procedia CIRP}, volume = {134}, journal = {Procedia CIRP}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2025.02.165}, pages = {514 -- 519}, abstract = {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.}, language = {en} } @misc{EichenseerWinkler, author = {Eichenseer, Patrick and Winkler, Herwig}, title = {Data-oriented shopfloor management : an inductively developed holistic conceptual model}, series = {The international journal of advanced manufacturing technology}, volume = {2025}, journal = {The international journal of advanced manufacturing technology}, publisher = {Springer}, address = {Wiesbaden}, issn = {1433-3015}, doi = {10.1007/s00170-025-15571-2}, pages = {1 -- 23}, abstract = {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.}, language = {en} } @misc{AbdulghaniWinkler, author = {Abdulghani, Tamer and Winkler, Herwig}, title = {A SWOT analysis approach for assessing the sustainable transition in the coal energy sector in Germany}, series = {Procedia computer science}, volume = {263}, journal = {Procedia computer science}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1877-0509}, doi = {10.1016/j.procs.2025.07.010}, pages = {76 -- 81}, abstract = {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.}, language = {en} } @misc{ThomasWinkler, author = {Thomas, Kevin and Winkler, Herwig}, title = {Extended reality for process visualization in cloud manufacturing : a systematic review}, series = {Procedia CIRP}, volume = {136}, journal = {Procedia CIRP}, editor = {Mourtzis, Dimitris}, publisher = {Elsevier B.V.}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2025.08.111}, pages = {648 -- 653}, abstract = {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.}, language = {en} } @misc{AbdulghaniWinkler, author = {Abdulghani, Tamer and Winkler, Herwig}, title = {Assessing the maturity of digital decarbonization in the manufacturing sector}, series = {LogForum : scientific journal of logistics}, volume = {22}, journal = {LogForum : scientific journal of logistics}, number = {1}, publisher = {Wyzsza Szkola Logistyki}, address = {Poznan}, issn = {1734-459X}, doi = {10.17270/J.LOG.001282}, pages = {15 -- 27}, abstract = {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.}, language = {en} } @misc{AbdulghaniTugraYilmazWinkler, author = {Abdulghani, Tamer and Tugra Yilmaz, Oguzkan and Winkler, Herwig}, title = {The role of information sharing in supply chain collaboration : impacts and emerging opportunities}, series = {Procedia computer science}, volume = {277}, journal = {Procedia computer science}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1877-0509}, doi = {10.1016/j.procs.2026.02.224}, pages = {1859 -- 1868}, abstract = {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.}, language = {en} } @misc{HayatRuesterWinkler, author = {Hayat, Mubashir and R{\"u}ster, Moritz and Winkler, Herwig}, title = {AI-based maintenance order planning and control of trains : status quo and conceptual considerations}, series = {Procedia computer science}, volume = {277}, journal = {Procedia computer science}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1877-0509}, doi = {10.1016/j.procs.2026.02.286}, pages = {2495 -- 2504}, abstract = {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.}, language = {en} }