@inproceedings{RojahnGronau2023, author = {Rojahn, Marcel and Gronau, Norbert}, title = {Digital platform concepts for manufacturing companies}, series = {10th International Conference on Future Internet of Things and Cloud (FiCloud)}, booktitle = {10th International Conference on Future Internet of Things and Cloud (FiCloud)}, publisher = {IEEE}, address = {[Erscheinungsort nicht ermittelbar]}, isbn = {979-8-3503-1635-3}, doi = {10.1109/FiCloud58648.2023.00030}, pages = {149 -- 158}, year = {2023}, abstract = {Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.}, language = {en} } @inproceedings{BenderGronauWinter2023, author = {Bender, Benedict and Gronau, Norbert and Winter, Robert}, title = {Minitrack introduction enterprise-level information systems}, series = {Proceedings of the 56th Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 56th Hawaii International Conference on System Sciences}, editor = {Bui, Tung X.}, publisher = {Hawaii International Conference on System Sciences}, address = {Honolulu, HI}, isbn = {978-0-9981331-6-4}, issn = {2572-6862}, pages = {5809 -- 5810}, year = {2023}, abstract = {While Information Systems (IS) Research on the individual and workgroup level of analysis is omnipresent, research on the enterprise-level IS is less frequent. Even though research on Enterprise Systems and their management is established in academic associations and conference programs, enterprise-level phenomena are underrepresented. This minitrack provides a forum to integrate existing research streams that traditionally needed to be attached to other topics (such as IS management or IS governance). The minitrack received broad attention. The three selected papers address different facets of the future role of enterprise-wide IS including aspects such as carbonization, ecosystem integration, and technology-organization fit.}, language = {en} } @incollection{ThimGronauHaaseetal.2023, author = {Thim, Christof and Gronau, Norbert and Haase, Jennifer and Grum, Marcus and Sch{\"u}ffler, Arnulf and Roling, Wiebke and Kluge, Annette}, title = {Modeling change in business processes}, series = {Business modeling and software design}, booktitle = {Business modeling and software design}, editor = {Shishkov, Boris}, publisher = {Springer Nature}, address = {Cham}, isbn = {978-3-031-36756-4}, doi = {10.1007/978-3-031-36757-1_1}, pages = {3 -- 17}, year = {2023}, abstract = {Business processes are regularly modified either to capture requirements from the organization's environment or due to internal optimization and restructuring. Implementing the changes into the individual work routines is aided by change management tools. These tools aim at the acceptance of the process by and empowerment of the process executor. They cover a wide range of general factors and seldom accurately address the changes in task execution and sequence. Furthermore, change is only framed as a learning activity, while most obstacles to change arise from the inability to unlearn or forget behavioural patterns one is acquainted with. Therefore, this paper aims to develop and demonstrate a notation to capture changes in business processes and identify elements that are likely to present obstacles during change. It connects existing research from changes in work routines and psychological insights from unlearning and intentional forgetting to the BPM domain. The results contribute to more transparency in business process models regarding knowledge changes. They provide better means to understand the dynamics and barriers of change processes.}, language = {en} } @inproceedings{GrumThimRolingetal.2023, author = {Grum, Marcus and Thim, Christof and Roling, Wiebke and Sch{\"u}ffler, Arnulf and Kluge, Annette and Gronau, Norbert}, title = {AI case-based reasoning for artificial neural networks}, series = {Artificial intelligence and industrial applications}, volume = {771}, booktitle = {Artificial intelligence and industrial applications}, editor = {Masrour, Tawfik and El Hassani, Ibtissam and Barka, Noureddine}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-43523-2}, doi = {10.1007/978-3-031-43524-9_2}, pages = {17 -- 35}, year = {2023}, abstract = {Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.}, language = {en} } @incollection{TeichmannBusseGonnermannetal.2023, author = {Teichmann, Malte and Busse, Jana and Gonnermann, Jana and Reimann, Daniela and Ritterbusch, Georg David and Langemeyer, Ines and Gronau, Norbert}, title = {Konzeption, Erstellung und Evaluation von VR-R{\"a}umen f{\"u}r die betriebliche Weiterbildung in KMU}, series = {Digitalisierung der Arbeitswelt im Mittelstand 3}, booktitle = {Digitalisierung der Arbeitswelt im Mittelstand 3}, editor = {Nitsch, Verena and Brandl, Christopher and H{\"a}ußling, Roger and Roth, Philip and Gries, Thomas and Schmenk, Bernhard}, publisher = {Springer Vieweg}, address = {Berlin}, isbn = {978-3-662-67023-1}, doi = {10.1007/978-3-662-67024-8_5}, pages = {155 -- 204}, year = {2023}, abstract = {Der Beitrag adressiert die Erstellung von Virtual-Reality gest{\"u}tzten (Lehr- und Lern-) R{\"a}umen f{\"u}r die betriebliche Weiterbildung im Rahmen eines Forschungsprojektes. Der damit verbundene Konzeptions- und Umsetzungsprozess ist mit verschiedenen Herausforderungen verbunden: einerseits ist Virtual-Reality ein vergleichsweise neues Lehr- und Lernmedium, womit wenig praktische Handreichungen zur praktischen Umsetzung existieren. Andererseits existieren theoretisch-konzeptionelle Ans{\"a}tze zur Gestaltung digitaler Lehr- und Lernarrangements, die jedoch 1) oft Gefahr laufen, an den realen Bed{\"u}rfnissen der Praxis „vorbei" zu gehen und 2) zumeist nicht konkret Virtual-Reality bzw. damit verbundene Lehr- und Lernumgebungen adressieren. In dieser Folge sind Best-Practice Beispiele basierend auf erfolgreichen Umsetzungsvorhaben, die nachfolgenden Projekten als „Wegweiser" dienen k{\"o}nnten, {\"a}ußerst rar. Der Beitrag setzt an dieser Stelle an: basierend auf zwei real existierenden betrieblichen Anwendungsf{\"a}llen aus den Bereichen Natursteinbearbeitung sowie Einzel- und Sondermaschinenbau werden Herausforderungen und L{\"o}sungswege des Erstellungsprozesses von Virtual-Reality gest{\"u}tzten (Lehr- und Lern-)R{\"a}umen beschrieben. Ebenfalls werden basierend auf den gemachten Projekterfahrungen Handlungsempfehlungen f{\"u}r die gelingende Konzeption, Umsetzung und Evaluation dieser R{\"a}ume formuliert. Betriebliche Besch{\"a}ftigte aus den Bereichen Aus- und Weiterbildung, Management oder Human Ressources, die in eigenen Projekten im Bereich Virtual Reality aktiv werden wollen, profitieren von den herausgestellten praktischen Handreichungen. Forschende Personen sollen Anregungen f{\"u}r weiterf{\"u}hrende Forschungsvorhaben erhalten.}, language = {de} } @misc{PanzerBenderGronau2023, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {A deep reinforcement learning based hyper-heuristic for modular production control}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, issn = {1867-5808}, doi = {10.25932/publishup-60564}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-605642}, pages = {24}, year = {2023}, abstract = {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.}, language = {en} } @article{PanzerBenderGronau2023, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {A deep reinforcement learning based hyper-heuristic for modular production control}, series = {International journal of production research}, journal = {International journal of production research}, publisher = {Taylor \& Francis}, address = {London}, issn = {0020-7543}, doi = {10.1080/00207543.2023.2233641}, pages = {1 -- 22}, year = {2023}, abstract = {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.}, language = {en} } @article{UllrichWeberGronau2023, author = {Ullrich, Andr{\´e} and Weber, Edzard and Gronau, Norbert}, title = {Regionale Refabrikationsnetzwerke}, series = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse}, volume = {39}, journal = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse}, number = {2}, publisher = {GITO mbH Verlag}, address = {Berlin}, issn = {2364-9208}, doi = {10.30844/IM_23-2_11-14}, pages = {11 -- 14}, year = {2023}, abstract = {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 Aktivit{\"a}ten, um zu einem nachhaltigen Umgang mit den zur Verf{\"u}gung stehenden Ressourcen zu gelangen. In diesem Beitrag wird ein lokaler Remanufacturing-Ansatz vorgestellt, der es erm{\"o}glicht, den Ressourcenverbrauch zu reduzieren, lokale Unternehmen zu f{\"o}rdern und effiziente L{\"o}sungen f{\"u}r die regionale Wieder- und Weiterverwendung von G{\"u}tern anzubieten.}, language = {de} } @misc{UllrichWeberGronau2023, author = {Ullrich, Andr{\´e} and Weber, Edzard and Gronau, Norbert}, title = {Regionale Refabrikationsnetzwerke}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, number = {2}, issn = {2364-9208}, doi = {10.25932/publishup-60451}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-604510}, pages = {6}, year = {2023}, abstract = {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 Aktivit{\"a}ten, um zu einem nachhaltigen Umgang mit den zur Verf{\"u}gung stehenden Ressourcen zu gelangen. In diesem Beitrag wird ein lokaler Remanufacturing-Ansatz vorgestellt, der es erm{\"o}glicht, den Ressourcenverbrauch zu reduzieren, lokale Unternehmen zu f{\"o}rdern und effiziente L{\"o}sungen f{\"u}r die regionale Wieder- und Weiterverwendung von G{\"u}tern anzubieten.}, language = {de} } @incollection{GonnermannBrandenburgerVladovaetal.2023, author = {Gonnermann, Jana and Brandenburger, Bonny and Vladova, Gergana and Gronau, Norbert}, title = {To what extent can individualisation in terms of different types of mode improve learning outcomes and learner satisfaction?}, series = {Proceedings of the 56th Annual Hawaii International Conference on System Sciences January 3-6, 2023}, booktitle = {Proceedings of the 56th Annual Hawaii International Conference on System Sciences January 3-6, 2023}, editor = {Bui, Tung X.}, publisher = {Department of IT Management Shidler College of Business University of Hawaii}, address = {Honolulu, HI}, isbn = {978-0-9981331-6-4}, pages = {123 -- 132}, year = {2023}, abstract = {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.}, language = {en} }