TY - GEN A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - A deep reinforcement learning based hyper-heuristic for modular production control T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 173 KW - production control KW - modular production KW - multi-agent system KW - deep reinforcement learning KW - deep learning KW - multi-objective optimisation Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-605642 SN - 1867-5808 ER - TY - JOUR A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - A deep reinforcement learning based hyper-heuristic for modular production control JF - International journal of production research N2 - In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios. KW - production control KW - modular production KW - multi-agent system KW - deep reinforcement learning KW - deep learning KW - multi-objective optimisation Y1 - 2023 U6 - https://doi.org/10.1080/00207543.2023.2233641 SN - 0020-7543 SN - 1366-588X SN - 0278-6125 SP - 1 EP - 22 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Ullrich, André A1 - Weber, Edzard A1 - Gronau, Norbert T1 - Regionale Refabrikationsnetzwerke BT - Potenziale und Herausforderungen der lokalen Wiederaufarbeitung von Produkten JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - Die Herstellung von Produkten bindet Energie sowie auch materielle Ressourcen. Viel zu langsam entwickeln sich sowohl das Bewusstsein der Konsumenten sowie der Produzenten als auch gesetzgebende Aktivitäten, um zu einem nachhaltigen Umgang mit den zur Verfügung stehenden Ressourcen zu gelangen. In diesem Beitrag wird ein lokaler Remanufacturing-Ansatz vorgestellt, der es ermöglicht, den Ressourcenverbrauch zu reduzieren, lokale Unternehmen zu fördern und effiziente Lösungen für die regionale Wieder- und Weiterverwendung von Gütern anzubieten. KW - Refabrikation KW - Regionale Ansätze KW - Remanufacturing Y1 - 2023 U6 - https://doi.org/10.30844/IM_23-2_11-14 SN - 2364-9208 VL - 39 IS - 2 SP - 11 EP - 14 PB - GITO mbH Verlag CY - Berlin ER - TY - GEN A1 - Ullrich, André A1 - Weber, Edzard A1 - Gronau, Norbert T1 - Regionale Refabrikationsnetzwerke BT - Potenziale und Herausforderungen der lokalen Wiederaufarbeitung von Produkten T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Die Herstellung von Produkten bindet Energie sowie auch materielle Ressourcen. Viel zu langsam entwickeln sich sowohl das Bewusstsein der Konsumenten sowie der Produzenten als auch gesetzgebende Aktivitäten, um zu einem nachhaltigen Umgang mit den zur Verfügung stehenden Ressourcen zu gelangen. In diesem Beitrag wird ein lokaler Remanufacturing-Ansatz vorgestellt, der es ermöglicht, den Ressourcenverbrauch zu reduzieren, lokale Unternehmen zu fördern und effiziente Lösungen für die regionale Wieder- und Weiterverwendung von Gütern anzubieten. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 183 KW - Refabrikation KW - Regionale Ansätze KW - Remanufacturing Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-604510 SN - 2364-9208 SN - 1867-5808 IS - 2 ER - TY - CHAP A1 - Gonnermann, Jana A1 - Brandenburger, Bonny A1 - Vladova, Gergana A1 - Gronau, Norbert ED - Bui, Tung X. T1 - To what extent can individualisation in terms of different types of mode improve learning outcomes and learner satisfaction? BT - a pre-study T2 - Proceedings of the 56th Annual Hawaii International Conference on System Sciences January 3-6, 2023 N2 - With the latest technological developments and associated new possibilities in teaching, the personalisation of learning is gaining more and more importance. It assumes that individual learning experiences and results could generally be improved when personal learning preferences are considered. To do justice to the complexity of the personalisation possibilities of teaching and learning processes, we illustrate the components of learning and teaching in the digital environment and their interdependencies in an initial model. Furthermore, in a pre-study, we investigate the relationships between the learner's ability to (digital) self-organise, the learner’s prior- knowledge learning in different variants of mode and learning outcomes as one part of this model. With this pre-study, we are taking the first step towards a holistic model of teaching and learning in digital environments. KW - advances in teaching and learning technologies KW - digital learning KW - digital teaching KW - experimental design KW - personalised learning KW - teaching and learning model Y1 - 2023 SN - 978-0-9981331-6-4 SP - 123 EP - 132 PB - Department of IT Management Shidler College of Business University of Hawaii CY - Honolulu, HI ER - TY - CHAP A1 - Klippert, Monika A1 - Stolpmann, Robert A1 - Grum, Marcus A1 - Thim, Christof A1 - Gronau, Norbert A1 - Albers, Albert T1 - Knowledge transfer quality improvement BT - the quality enhancement of knowledge transfers in product engineering T2 - Procedia CIRP N2 - Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect. KW - knowledge transfer KW - product generation engineering KW - improvement KW - quality KW - intervention Y1 - 2023 U6 - https://doi.org/10.1016/j.procir.2023.02.171 SN - 2212-8271 VL - 119 SP - 919 EP - 925 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Gronau, Norbert A1 - Weber, Edzard A1 - Wander, Paul A1 - Ullrich, André ED - Plapper, Peter T1 - A regional remanufacturing network approach BT - modeling and simulation of circular economy processes in the era of industry 4.0 T2 - Digitization of the work environment for sustainable production N2 - Manufacturing companies still have relatively few points of contact with the circular economy. Especially, extending life time of whole products or parts via remanufacturing is an promising approach to reduce waste. However, necessary cost-efficient assessment of the condition of the individual parts is challenging and assessment procedures are technically complex (e.g., scanning and testing procedures). Furthermore, these assessment procedures are usually only available after the disassembly process has been completed. This is where conceptualization, data acquisition and simulation of remanufacturing processes can help. One major constraining aspect of remanufacturing is reducing logistic efforts, since these also have negative external effects on the environment. Thus regionalization is an additional but in the end consequential challenge for remanufacturing. This article aims to fill a gap by providing an regional remanufacturing approach, in particular the design of local remanufacturing chains. Thereby, further focus lies on modeling and simulating alternative courses of action, including feasibility study and eco-nomic assessment. KW - regional network KW - remanufacturing KW - scenario modeling Y1 - 2022 SN - 978-3-95545-407-4 U6 - https://doi.org/10.30844/WGAB_2022_8 SP - 145 EP - 170 PB - GITO Verlag CY - Berlin ER - TY - CHAP A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Errors in the process of modeling business processes T2 - Business modeling and software design : 12th International Symposium, BMSD 2022, Fribourg, Switzerland, June 27–29, 2022, proceedings N2 - Process models are the basic ingredient for many attempts to improve business processes. The graphical depiction of otherwise not observable behavior in an enterprise is one of the most important techniques in the digital society. They help to enable decision making in the design of processes and workflows. Nevertheless it is not easy to correctly model business processes. Some approaches try to detect errors by an automated analysis of the process model. This contribution focuses on the creation of the first model from scratch. Which errors occur most frequently and how can these be avoided? KW - business process modeling KW - errors in modeling KW - process of modeling Y1 - 2022 SN - 978-3-031-11509-7 SN - 978-3-031-11510-3 SN - 978-3-031-11511-0 U6 - https://doi.org/10.1007/978-3-031-11510-3_13 VL - 453 SP - 221 EP - 229 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Teichmann, Malte A1 - Lass, Sander A1 - Ullrich, André A1 - Gronau, Norbert ED - Weber, Kristin ED - Reinheimer, Stefan T1 - Modellfabriken als Enabler flexibler Lehr- und Lernsituationen für die Kompetenzentwicklung im Fabrikkontext BT - die Lernfabrik des Zentrums Industrie 4.0 Potsdam T2 - Faktor Mensch N2 - Dieses Kapitel diskutiert die Notwendigkeit einer stärkeren Praxisorientierung für die Schaffung konkreter Lehr- und Lernräume in Unternehmen und zeigt die Vorteile einer Lernfabrik vor dem Hintergrund der stattfindenden Digitalisierung als Mittel zur Kompetenzentwicklung auf. Die technologiebedingt erweiterten Weiterbildungsziele erfordern die Nutzung geeigneter Konzepte und Lösungen. Dahingehend erfolgt die zielorientierte Konkretisierung der Kreation geeigneter Lehr- und Lernsituationen. Die Darstellung der Nutzbarmachung einer Modellfabrik als Lernfabrik der betrieblichen Weiterbildungspraxis zeigt nicht nur eine Lösung für die intendierte Bereitstellung flexibler Lehr- und Lernsituationen, sondern liefert ebenso Handlungsempfehlungen und Best-Practices für die erfolgreiche Kompetenzentwicklung. Insbesondere Praktiker profitieren von der Darstellung der Lernfabrik: aus dieser können sowohl betriebliche Weiterbildner als auch Geschäftsverantwortliche Implikationen für die didaktische Transformation betrieblicher Arbeitsorte in betriebliche Lern-Orte ableiten. Die detaillierte Darstellung einer Tagesschulung zum Thema Auswirkungen von Industrie 4.0 auf die Arbeit der Mitarbeiter sowie Illustration eines Lernszenarios geben reale Einblicke, wie betriebliche Weiterbildung abseits von Lehr-Lern-Kurzschluss-orientierter Didaktik gelingt. KW - betriebliche Weiterbildung KW - Digitalisierung KW - Modellfabrik KW - Lehr-Lernsituationen KW - Industrie 4.0 KW - Zentrum Industrie 4.0 Y1 - 2022 SN - 978-3-658-34523-5 SN - 978-3-658-34524-2 U6 - https://doi.org/10.1007/978-3-658-34524-2_10 N1 - vollständig überarbeiteter und erweiterter Beitrag basierend auf dem Artikel „Herausforderungen und Handlungsempfehlungen betrieblicher Weiterbildungspraxis in Zeiten der Digitalisierung“ von Malte Teichmann, André Ullrich, Julian Wenz, Norbert Gronau, HMD Heft 333, Stefan Reinheimer, Kristin Weber (Hrsg.): Faktor Mensch, Juni 2020, S. 512–527. SP - 173 EP - 196 PB - Springer Fachmedien CY - Wiesbaden ER - TY - JOUR A1 - Bender, Benedict A1 - Bertheau, Clementine A1 - Körppen, Tim A1 - Lauppe, Hannah A1 - Gronau, Norbert T1 - A proposal for future data organization in enterprise systems BT - an analysis of established database approaches JF - Information systems and e-business management N2 - The digital transformation sets new requirements to all classes of enterprise systems in companies. ERP systems in particular, which represent the dominant class of enterprise systems, are struggling to meet the new requirements at all levels of the architecture. Therefore, there is an urgent need to reconsider the overall architecture of the systems and address the root of the related issues. Given that many restrictions ERP pose on their adaptability are related to the standardization of data, the database layer of ERP systems is addressed. Since database serve as the foundation for data storage and retrieval, they limit the flexibility of enterprise systems and the chance to adapt to new requirements accordingly. So far, relational databases are widely used. Using a systematic literature approach, recent requirements for ERP systems were identified. Prominent database approaches were assessed against the 23 requirements identified. The results reveal the strengths and weaknesses of recent database approaches. To this end, the results highlight the demand to combine multiple database approaches to fulfill recent business requirements. From a conceptual point of view, this paper supports the idea of federated databases which are interoperable to fulfill future requirements and support business operation. This research forms the basis for renewal of the current generation of ERP systems and proposes to ERP vendors to use different database concepts in the future. KW - database KW - enterprise system KW - ERP system KW - requirements KW - problems KW - future Y1 - 2022 U6 - https://doi.org/10.1007/s10257-022-00555-6 SN - 1617-9846 SN - 1617-9854 VL - 20 SP - 441 EP - 494 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Grum, Marcus A1 - Körppen, Tim A1 - Korjahn, Nicolas A1 - Gronau, Norbert T1 - Entwicklung eines KI-ERP-Indikators BT - Evaluation der Potenzialerschließung von Künstlicher Intelligenz in Enterprise-Resource-Planning-Systemen N2 - Künstliche Intelligenz (KI) gewinnt in zahlreichen Branchen rasant an Bedeutung und wird zunehmend auch in Enterprise Resource Planning (ERP)-Systemen als Anwendungsbereich erschlossen. Die Idee, dass Maschinen die kognitiven Fähigkeiten des Menschen imitieren können, indem Wissen durch Lernen auf Basis von Beispielen in Daten, Informationen und Erfahrungen generiert wird, ist heute ein Schlüsselelement der digitalen Transformation. Jedoch charakterisiert der Einsatz von KI in ERP-System einen hohen Komplexitätsgrad, da die KI als Querschnittstechnologie zu verstehen ist, welche in unterschiedlichen Unternehmensbereichen zum Einsatz kommen kann. Auch die Anwendungsgrade können sich dabei erheblich voneinander unterscheiden. Um trotz dieser Komplexität den Einsatz der KI in ERP-Systemen erfassen und systembezogen vergleichen zu können, wurde im Rahmen dieser Studie ein Reifegradmodell entwickelt. Dieses bildet die Ausgangsbasis zur Ermittlung der KI-Reife in ERP-Systemen und grenzt dabei die folgenden vier KI- bzw. systembezogenen Ebenen voneinander ab: 1) Technische Möglichkeiten, 2) Datenreife, 3) Funktionsreife und 4) Erklärfähigkeit des Systems. KW - Künstliche Intelligenz KW - Enterprise-Resource-Planning KW - KI-ERP-Indikator Y1 - 2022 UR - https://lswi.de/assets/downloads/publikationen/110/Grum-Entwicklung-eines-KI-ERP-Indikators--.pdf PB - Center for Enterprise Research, Universität Potsdam CY - Potsdam ER - TY - BOOK A1 - Gronau, Norbert T1 - Geschäftsprozessmanagement in Wirtschaft und Verwaltung N2 - Dieses Standardwerk zu Geschäftsprozessmanagement in Wirtschaft und Verwaltung gibt gleichzeitig einen Überblick über den aktuellen Stand der Forschung zu diesem Thema und führt Interessierte wie Studierende oder Praktiker in das Thema und seine Facetten ein. Aktuelle Entwicklungen wie Robotic Process Automation und Process Mining werden aufgegriffen. Im Mittelpunkt stehen die drei wesentlichen GPM- Blickwinkel Technik, Organisation und Mensch. Aus Sicht der Forschung werden innovative Methoden zur Modellierung und Analyse von Geschäftsprozessen beschrieben. Aus Sicht der Lehre dient das Buch als Einstiegslektüre und liefert Ansatzpunkte für die vertiefte Befassung mit einzelnen Aspekten des Geschäftsprozessmanagements. Für die Praxis beschreibt dieses Werk die dort bestehenden konzeptionellen und methodischen Hindernisse des Prozessmanagements und zeigt Wege zur Überwindung dieser Hindernisse. Die vorliegende Auflage wurde vollständig überarbeitet und stark erweitert, u. a. mit neuen Kapiteln zu Software für das Geschäftsprozessmanagement und zum Change Management. Y1 - 2022 UR - https://ebookcentral.proquest.com/lib/potsdamuni/detail.action?docID=7119120 SN - 978-3-95545-399-2 PB - Gito CY - Berlin ET - 3. Aufl. ER - TY - CHAP A1 - Bender, Benedict A1 - Gronau, Norbert ED - Bui, Tung T1 - Introduction to the Minitrack on towards the future of enterprise systems T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, specialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions. Y1 - 2022 SN - 978-0-9981331-5-7 U6 - https://doi.org/10.24251/HICSS.2022.869 SP - 7232 EP - 7233 PB - Hawaii International Conference on System Sciences CY - Honolulu, HI ER - TY - CHAP A1 - Gronau, Norbert ED - Roth, Stefan ED - Corsten, Hans T1 - Künstliche Intelligenz in der Produktionssteuerung T2 - Handbuch Digitalisierung Y1 - 2022 SN - 978-3-8006-6562-4 SN - 978-3-8006-6563-1 SP - 629 EP - 650 PB - Verlag Franz Vahlen CY - München ER - TY - JOUR A1 - Ullrich, André A1 - Vladova, Gergana A1 - Marquart, Danny A1 - Braun, Andreas A1 - Gronau, Norbert T1 - An overwiew of benefits and risks in open innovation projects and the influence of intermediary participation, decision-making authority, experience, and position on their perception JF - International journal of innovation management : IJIM N2 - This paper presents an exploratory study investigating the influence of the factors (1) intermediary participation, (2) decision-making authority, (3) position in the enterprise, and (4) experience in open innovation on the perception and assessment of the benefits and risks expected from participating in open innovation projects. For this purpose, an online survey was conducted in Germany, Austria and Switzerland. The result of this paper is an empirical evidence showing whether and how these factors affect the perception of potential benefits and risks expected within the context of open innovation project participation. Furthermore, the identified effects are discussed against the theory. Existing theory regarding the benefits and risks of open innovation is expanded by (1) finding that they are perceived mostly independently of the factors, (2) confirming the practical relevance of benefits and risks, and (3) enabling a finer distinction between their degrees of relevance according to respective contextual specifics. KW - Open innovation KW - intermediaries KW - benefits KW - decision-making KW - experience; KW - risks Y1 - 2022 U6 - https://doi.org/10.1142/S1363919622500128 SN - 1363-9196 SN - 1757-5877 VL - 26 IS - 02 PB - World Scientific Publ. CY - Singapore ER - TY - GEN A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Neural agent-based production planning and control BT - an architectural review T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 172 KW - production planning and control KW - machine learning KW - neural networks KW - systematic literature review KW - taxonomy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-604777 SN - 1867-5808 ER - TY - JOUR A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Neural agent-based production planning and control BT - an architectural review JF - Journal of Manufacturing Systems N2 - Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality. KW - production planning and control KW - machine learning KW - neural networks KW - systematic literature review KW - taxonomy Y1 - 2022 U6 - https://doi.org/10.1016/j.jmsy.2022.10.019 SN - 0278-6125 SN - 1878-6642 VL - 65 SP - 743 EP - 766 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Bender, Benedict A1 - Gronau, Norbert ED - Bui, Tung T1 - Introduction to the Minitrack on towards the future of enterprise systems T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, pecialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 188 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-605406 SN - 978-0-9981331-5-7 SN - 1867-5808 ER - TY - JOUR A1 - Vladova, Gergana A1 - Gronau, Norbert T1 - KI-basierte Assistenzsysteme in betrieblichen Lernprozessen JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - Assistenzsysteme finden im Kontext der digitalen Transformation immer mehr Einsatz. Sie können Beschäftigte in industriellen Produktionsprozessen sowohl in der Anlern- als auch in der aktiven Arbeitsphase unterstützen. Kompetenzen können so arbeitsplatz- und prozessnah sowie bedarfsorientiert aufgebaut werden. In diesem Beitrag wird der aktuelle Forschungsstand zu den Einsatzmöglichkeiten dieser Assistenzsysteme diskutiert und mit Beispielen illustriert. Es werden unter anderem auch Herausforderungen für den Einsatz aufgezeigt. Am Ende des Beitrags werden Potenziale für die zukünftige Nutzung von AS in industriellen Lernprozessen und für die Forschung identifiziert. KW - KI KW - kognitive Assistenzsysteme KW - betriebliche Lernprozesse KW - Weiterbildung Y1 - 2022 U6 - https://doi.org/10.30844/I40M_22-2_11-14 SN - 2364-9216 SN - 2364-9208 VL - 38 IS - 2 SP - 11 EP - 14 PB - GITO mbH Verlag für Industrielle Informationstechnik und Organisation CY - Berlin ER - TY - CHAP A1 - Gronau, Norbert A1 - Rojahn, Marcel ED - Leupold, Andreas ED - Wiebe, Andreas ED - Glossner, Silke T1 - Das Industrial Internet of Things (IIOT) T2 - IT-Recht : Recht, Wirtschaft und Technik der digitalen Transformation Y1 - 2021 UR - https://beck-online.beck.de/Bcid/Y-400-W-LeupoldGlossnerHdbITR-GL-Teil10-1 SN - 978-3-406-74458-7 SP - 1115 EP - 1124 PB - C.H. Beck CY - München ET - 4., überarbeitet und erweitert ER -