TY - JOUR A1 - Vladova, Gergana A1 - Wotschack, Philip A1 - Lareiro, Patricia de Paiva A1 - Gronau, Norbert A1 - Thim, Christof T1 - Lernen mit Assistenzsystemen T1 - Learning with assistance systems BT - vor lauter Aufgaben den Prozess nicht sehen? BT - not seeing the process for the tasks? JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - Der Beitrag beschreibt die Konzeption und Durchführung und bietet einen Einblick in die ersten Ergebnisse einer Untersuchung mit experimentellem Design in einer simulierten Prozessumgebung im Forschungs- und Anwendungszentrum Industrie 4.0 in Potsdam. Im Mittelpunkt stehen Anlernprozesse im Bereich der Einfacharbeit (Helfertätigkeiten) und ihre Gestaltung durch den Einsatz digitaler Assistenzsysteme. In der Arbeitsforschung finden sich Hinweise darauf, dass mit dem Einsatz dieser Systeme Prozesswissen verloren geht, im Sinne einer guten Kenntnis des gesamten Arbeitsprozesses, in den die einzelnen Tätigkeiten eingebettet sind. Das kann sich als Problem erweisen, vor allem wenn unvorhersehbare Situationen oder Fehler eintreten. Um die Rolle von Prozesswissen beim Einsatz von digitalen Assistenzsystemen zu untersuchen, wird im Experiment eine echte Fabriksituation simuliert. Die Probanden werden über ein Assistenzsystem Schritt für Schritt in ihre Aufgabentätigkeit angelernt, einem Teil der Probanden wird allerdings am Anfang zusätzlich Prozesswissen im Rahmen einer kurzen Schulung vermittelt. N2 - The paper describes the conception and implementation as well as offers an insight into the first results of a study with experimental design in a simulated process environment at the Research and Application Center Industry 4.0 in Potsdam. The focus is on learning processes in the field of simple work and their organization through the use of digital assistance systems. In labour research, there are indications that process knowledge is lost with the use of these systems, in the sense of a good knowledge of the entire work process in which the individual activities are embedded. To investigate the role of process knowledge in the use of digital assistance systems, a real factory situation is simulated in the experiment. KW - Assistenzsysteme KW - Industrie 4.0 KW - Prozesswissen KW - Lernfabrik KW - assistance systems KW - industry 4.0 KW - process knowledge KW - learning factory Y1 - 2020 U6 - https://doi.org/10.30844/I40M_20-3_S16-20 SN - 2364-9208 VL - 36 IS - 3 SP - 16 EP - 20 PB - GITO mbH Verlag CY - Berlin ER - TY - CHAP A1 - Vladova, Gergana A1 - Ullrich, André A1 - Bender, Benedict A1 - Gronau, Norbert ED - Reis, Arsénio ED - Barroso, João ED - Lopes, J. Bernardino ED - Mikropoulos, Tassos ED - Fan, Chih-Wen T1 - Yes, we can (?) BT - a critical review of the COVID-19 semester T2 - Technology and innovation in learning, teaching and education : second international conference, TECH-EDU 2020, Vila Real, Portugal, December 2-4, 2020 : proceedings N2 - The COVID-19 crisis has caused an extreme situation for higher education institutions around the world, where exclusively virtual teaching and learning has become obligatory rather than an additional supporting feature. This has created opportunities to explore the potential and limitations of virtual learning formats. This paper presents four theses on virtual classroom teaching and learning that are discussed critically. We use existing theoretical insights extended by empirical evidence from a survey of more than 850 students on acceptance, expectations, and attitudes regarding the positive and negative aspects of virtual teaching. The survey responses were gathered from students at different universities during the first completely digital semester (Spring-Summer 2020) in Germany. We discuss similarities and differences between the subjects being studied and highlight the advantages and disadvantages of virtual teaching and learning. Against the background of existing theory and the gathered data, we emphasize the importance of social interaction, the combination of different learning formats, and thus context-sensitive hybrid learning as the learning form of the future. KW - COVID-19 KW - higher education KW - virtual learning KW - digital learning KW - subject differences Y1 - 2021 SN - 978-3-030-73987-4 SN - 978-3-030-73988-1 U6 - https://doi.org/10.1007/978-3-030-73988-1_17 SP - 225 EP - 235 PB - Springer CY - Cham 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 - 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 - JOUR A1 - Ullrich, André A1 - Teichmann, Malte A1 - Gronau, Norbert T1 - Fast trainable capabilities in software engineering-skill development in learning factories JF - Ji suan ji jiao yu = Computer Education / Qing hua da xue N2 - The increasing demand for software engineers cannot completely be fulfilled by university education and conventional training approaches due to limited capacities. Accordingly, an alternative approach is necessary where potential software engineers are being educated in software engineering skills using new methods. We suggest micro tasks combined with theoretical lessons to overcome existing skill deficits and acquire fast trainable capabilities. This paper addresses the gap between demand and supply of software engineers by introducing an actionoriented and scenario-based didactical approach, which enables non-computer scientists to code. Therein, the learning content is provided in small tasks and embedded in learning factory scenarios. Therefore, different requirements for software engineers from the market side and from an academic viewpoint are analyzed and synthesized into an integrated, yet condensed skills catalogue. This enables the development of training and education units that focus on the most important skills demanded on the market. To achieve this objective, individual learning scenarios are developed. Of course, proper basic skills in coding cannot be learned over night but software programming is also no sorcery. KW - learning factory KW - programming skills KW - software engineering KW - training Y1 - 2021 U6 - https://doi.org/10.16512/j.cnki.jsjjy.2020.12.002 SN - 1672-5913 IS - 12 SP - 2 EP - 10 PB - [Verlag nicht ermittelbar] CY - Bei jing shi ER - TY - JOUR A1 - Ullrich, André A1 - Gronau, Norbert T1 - Bestimmung nachhaltiger Anwendungssystemarchitekturen JF - ERP-Management : Auswahl, Einführung und Betrieb von ERP-Systemen N2 - Die teilweise sehr kurzfristig notwendige Reaktion auf Veränderungen erfordert von Unternehmen ein hohes Maß an Flexibilität und Reaktionsgeschwindigkeit. Anwendungssystemarchitekturen, die im Wesentlichen aus alten und selbst entwickelten Systemen bestehen, erfüllen häufig diese Anforderungen nicht. Investitionsmittel für neue Software sind jedoch begrenzt, daher müssen Prioritäten in der Ablösung von Altsystemen gesetzt werden. Eine effiziente Analysemethode zur Planung der Erneuerung der Anwendungssystemlandschaft stellt die Wandlungsfähigkeitsanalyse dar. Dieser Beitrag beschreibt Vorgehen und Ergebnisse am Beispiel eines international tätigen Automobilzulieferers. N2 - The sometimes necessary reaction to changes requires a high degree of adaptability and speed of reaction from companies. Application system architectures, which essentially consist of old and self-developed systems, often do not meet these requirements. However, investment funds for new software are limited, so priorities must be set in the replacement of old systems. An efficient analysis method for planning the renewal of the application system landscape is the adaptability analysis. This article describes the procedure and results using the example of an internationally active automotive supplier. KW - Anpassungsfähigkeit KW - Anwendungssystemarchitekturen KW - Bewertung KW - adaptability KW - application system architectures KW - assessment Y1 - 2020 UR - https://www.wiso-net.de/document/ERP__1ba9f709bedd19d76acba5daebbc08c9befe5b9f U6 - https://doi.org/10.30844/ERP_20-1_54-57 SN - 1860-6725 VL - 16 IS - 1 SP - 54 EP - 57 PB - GITO mbH CY - Berlin ER - TY - CHAP A1 - Ullrich, André A1 - Gronau, Norbert ED - Panetto, Hervé ED - Madani, Kurosh ED - Smirnov, Alexander T1 - Time to change BT - considering the 4th Industrial Revolution from three sustainability perspectives T2 - Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics N2 - Industry 4.0 leads to a radical change that is progressing incrementally. The new information and communication technologies provide many conceivable opportunities for their application in the context of sustainable corporate management. The combination of new digital technologies with the ecological and social goals of companies offers a multitude of unimagined potentials and challenges. Although companies already see the need for action, there was in the past and currently still is a lack of concrete measures that lever the potential of Industry 4.0 for sustainability management. During the course of this position paper we develop six theses (two from each sustainability perspective) against the background of the current situation in research and practice, and policy. KW - industry 4.0 KW - sustainability KW - triple bottom line Y1 - 2020 SN - 978-989-758-476-3 U6 - https://doi.org/10.5220/0010148601090116 SP - 109 EP - 116 PB - SciTePress CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Thim, Christof A1 - Ullrich, André A1 - Gronau, Norbert T1 - Process model driven learning scenario implementation JF - Procedia manufacturing N2 - The implementation of learning scenarios is a diversely challenging, frequently purely manual and effortful undertaking. In this contribution a process based view is used in scenario generation to overcome communication, coordination and technical gaps. A framework is provided to identify, define and integrate technological artefacts and learning content as modular, reusable building blocks along a modeled production process. The specific contribution is twofold: 1) the theoretical framework represents a unique basis for modularization of content and technology in order to enhance reusability, 2) the model based scenario definition is a starting point for automated implementation of learning scenarios in industrial learning environments that has not been created before. KW - learning factories KW - learning scenario implementation KW - process modelling Y1 - 2020 U6 - https://doi.org/10.1016/j.promfg.2020.04.071 SN - 2351-9789 VL - 45 SP - 522 EP - 527 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Thim, Christof A1 - Ullrich, André A1 - Eigelshoven, Felix A1 - Gronau, Norbert A1 - Ritter, Ann-Carolin T1 - Crowdsourcing bei industriellen Innovationen T1 - Crowdsourcing for industrial innovations BT - Lösungsansätze und Herausforderung für KMU BT - solutions and challenges for SMEs JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - Die Innovationstätigkeit im industriellen Umfeld verlagert sich durch die Digitalisierung hin zu Produkt-Service-Systemen. Kleine und mittlere Unternehmen haben sich in ihrer Entwicklungstätigkeit bisher stark auf die Produktentwicklung bezogen. Der Umstieg auf „smarte“ Produkte und die Kopplung an Dienstleistungen erfordert häufig personelle und finanzielle Ressourcen, welche KMU nicht aufbringen können. Crowdsourcing stellt eine Möglichkeit dar, den Innovationsprozess für externe Akteure zu öffnen und Kosten- sowie Geschwindigkeitsvorteile zu realisieren. Bei der Integration von Crowdsourcing-Elementen ist jedoch einigen Herausforderungen zu begegnen. Dieser Beitrag zeigt sowohl die Potenziale als auch die Barrieren einer Crowdsourcing-Nutzung im industriellen Umfeld auf. N2 - Innovation activity in the industrial environment is shifting towards product-service systems as a result of digitalisation. Small and medium-sized enterprises have so far focused their development activities strongly on product development. The switch to “smart” products and the coupling to services often requires personnel and financial resources that SMEs cannot provide. Crowdsourcing is one way of opening up the innovation process to external actors and realising cost and speed advantages. However, the integration of crowdsourcing elements faces several challenges. This article shows both the potentials and the barriers of crowdsourcing in the industrial environment. KW - Crowdsourcing KW - industrielle Innovationen KW - KMU KW - industrial innovation KW - SMEs Y1 - 2020 U6 - https://doi.org/10.30844/I40M_20-6_S9-13 SN - 2364-9208 VL - 36 IS - 6 SP - 9 EP - 13 PB - GITO mbH Verlag CY - Berlin ER - TY - CHAP A1 - Thim, Christof A1 - Grum, Marcus A1 - Schüffler, Arnulf A1 - Roling, Wiebke A1 - Kluge, Annette A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - A concept for a distributed Interchangeable knowledge base in CPPS T2 - Towards sustainable customization: cridging smart products and manufacturing systems N2 - As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization. KW - learning KW - distributed knowledge base KW - artificial intelligence KW - CPPS Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90702-0 SN - 978-3-030-90700-6 U6 - https://doi.org/10.1007/978-3-030-90700-6_35 SP - 314 EP - 321 PB - Springer CY - Cham ER - TY - CHAP A1 - Thim, Christof A1 - Gronau, Norbert A1 - Haase, Jennifer A1 - Grum, Marcus A1 - Schüffler, Arnulf A1 - Roling, Wiebke A1 - Kluge, Annette ED - Shishkov, Boris T1 - Modeling change in business processes T2 - Business modeling and software design N2 - 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. KW - intentional forgetting KW - routines KW - business processes KW - unlearning Y1 - 2023 SN - 978-3-031-36756-4 SN - 978-3-031-36757-1 U6 - https://doi.org/10.1007/978-3-031-36757-1_1 SP - 3 EP - 17 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Teichmann, Malte A1 - Vladova, Gergana A1 - Gronau, Norbert T1 - Conception of subject-oriented learning BT - ameso-didactic design framework for learning scenarios for manufacturing JF - SSRN eLibrary / Social Science Research Network N2 - Competence development must change at all didactic levels to meet the new requirements triggered by digitization. Unlike classic learning theories and the resulting popular approaches (e.g., sender-receiver model), future-oriented vocational training must include new learning theory impulses in the discussion about competence acquisition. On the one hand, these impulses are often very well elaborated on the theoretical side, but the transfer into innovative learning environments - such as learning factories - is often still missing. On the other hand, actual learning factory (design) approaches often concentrate primarily on the technical side. Subject-oriented learning theory enables the design of competence development-oriented vocational training projectsin learning factories in which persons can obtain relevant competencies for digitization. At the same time, such learning theory approaches assume a potentially infinite number of learning interests and reasons. Following this, competence development is always located in an institutional or organizational context. The paper conceptionally answers how this theoryimmanent challenge is synthesizable with the reality of organizationally competence development requirements. KW - subject-oriented learning KW - learning scenario for manufacturing KW - didactic framework KW - action problems KW - didactic concept Y1 - 2023 U6 - https://doi.org/10.2139/ssrn.4457995 SN - 1556-5068 PB - Social Science Electronic Publ. CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Teichmann, Malte A1 - Ullrich, André A1 - Wenz, Julian A1 - Gronau, Norbert T1 - Herausforderungen und Handlungsempfehlungen betrieblicher Weiterbildungspraxis in Zeiten der Digitalisierung T1 - Challenges and recommended actions for in-company vocational training in times of digitization JF - HMD Praxis der Wirtschaftsinformatik N2 - Die Digitalisierung von Produktionsprozessen schreitet mit einer hohen Intensität voran. Weiterbildung hat eine hohe Relevanz für betriebliche Transformationsprozesse. Die betriebliche Weiterbildungspraxis ist den aktuellen Herausforderungen der Digitalisierung jedoch nicht gewachsen. Herausforderungen sind Kompetenzlücken der Mitarbeiter, ungewisse Anforderungsprofile und Tätigkeitstypen, demographischer Wandel sowie veraltete didaktische Ansätze. Zudem wird bestehender inhaltlicher und pädagogischer Freiraum bei der Gestaltung von Weiterbildung oftmals nur unzureichend ausgenutzt. Die skizzierte Situation führt dazu, dass der Mehrwert gegenwärtiger Qualifizierungsangebote sowohl für Unternehmen als auch Beschäftigte nicht ausgeschöpft wird. Ausgehend von Veränderungen durch Digitalisierung in der Produktion und deren Auswirkungen auf die Kompetenzentwicklung diskutiert dieser Beitrag Herausforderungen gegenwärtiger betrieblicher Weiterbildung. Er leitet Handlungsempfehlungen ab, die mithilfe von Beispielen gewerkschaftlich unterstützter Weiterbildungspraxis illustriert werden. Im Ergebnis erhalten Interessierte einen Überblick über gegenwärtige Herausforderungen und Handlungsempfehlungen für die Gestaltung und Durchführung von Weiterbildung in Zeiten der Digitalisierung. N2 - The digital transformation of production processes is constantly progressing. The human workforce is a central success factor, but employees must be prepared for the requirements induced by change, using inter alia competence development. In reality, however, the content-related and pedagogical freedom to design vocational training is often inadequately addressed. Based on the changes trough digitization in production processes, the challenges of current continuing vocational training in enterprises are discussed. Recommendations for action are then derived and illustrated by examples. The recommendations for action can serve as a basis for the design and implementation of their further vocational training practice. KW - betriebliche Weiterbildungspraxis KW - Digitalisierung von Produktionsprozessen KW - gewerkschaftlich unterstützte Weiterbildungspraxis KW - Kompetenzentwicklung KW - vocational training KW - digitization of production processes KW - labour union education KW - competence development Y1 - 2020 U6 - https://doi.org/10.1365/s40702-020-00614-x SN - 1436-3011 SN - 2198-2775 VL - 57 SP - 512 EP - 527 PB - Springer Vieweg CY - Wiesbaden ER - TY - JOUR A1 - Teichmann, Malte A1 - Ullrich, André A1 - Kotarski, David A1 - Gronau, Norbert T1 - Facing the demographic change BT - recommendations for designing learning factories as age-appropriate teaching-learning environments for older blue-collar workers JF - SSRN eLibrary / Social Science Research Network N2 - Digitization and demographic change are enormous challenges for companies. Learning factories as innovative learning places can help prepare older employees for the digital change but must be designed and configured based on their specific learning requirements. To date, however, there are no particular recommendations to ensure effective age-appropriate training of bluecollar workers in learning factories. Therefore, based on a literature review, design characteristics and attributes of learning factories and learning requirements of older employees are presented. Furthermore, didactical recommendations for realizing age-appropriate learning designs in learning factories and a conceptualized scenario are outlined by synthesizing the findings. KW - learning factory KW - vocational training KW - learning environment KW - age-appropriate competence development KW - demographic change Y1 - 2021 U6 - https://doi.org/10.2139/ssrn.3858716 SN - 1556-5068 PB - Social Science Electronic Publ. CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Teichmann, Malte A1 - Ullrich, André A1 - Knost, Dennis A1 - Gronau, Norbert T1 - Serious games in learning factories BT - perpetuating knowledge in learning loops by game-based learning JF - Procedia manufacturing N2 - The usage of gamification in the contexts of commerce, consumption, innovation or eLearning in schools and universities has been extensively researched. However, the potentials of serious games to transfer and perpetuate knowledge and action patterns in learning factories have not been levered so far. The goal of this paper is to introduce a serious game as an instrument for knowledge transfer and perpetuation. Therefore, reqirements towards serious games in the context of learning factories are pointed out. As a result, that builds on these requirements, a serious learning game for the topic of Industry 4.0 is practically designed and evaluated. KW - game-based learning KW - gamification KW - serious game KW - learning factories Y1 - 2020 U6 - https://doi.org/10.1016/j.promfg.2020.04.104 SN - 2351-9789 VL - 45 SP - 259 EP - 264 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Teichmann, Malte A1 - Ullrich, André A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Mobile IIoT-Technologien in hybriden Lernfabriken T1 - Using Mobile IIoT-Technologies in Hybrid Learning Factories BT - Szenariobasierte Entwicklung von Handlungskompetenz im Anwendungszentrum Industrie 4.0 BT - a Scenario-Based Development of Acting Capability in the Application Center Industry 4.0 JF - Industrie 4.0 Management N2 - Der Wandel zur automatisierten Produktion, die fortschreitende Digitalisierung der Wertschöpfungsprozesse sowie die stetige Implementierung von mobilen Industrial Internet of Things-Technologien (IIoT) in diese zur Unterstützung der Mitarbeiter stellen betriebliche Weiterbildung vor Herausforderungen. Komple-xere Anforderungen und veränderte Tätigkeitsprofile erfordern Handlungskom-petenzen bei Mitarbeitern im Sinne der Fähigkeit, in unbekannten Situationen auf Basis eigenen Könnens handlungsfähig zu bleiben. Jene sowie dafür notwendiges umfassendes Verständnis gegenüber digitalisierten Produktions-prozessen kann jedoch durch konventionelle Lehrmethoden nicht realisiert werden, da diese der erhöhten Anforderungskomplexität und den komplexen Rückkopplungen im Rahmen der Steuer- und Regelkreise nicht gerecht werden können. Diese Aspekte aufgreifend wird im Folgenden ein szenariobasierter Wei-terbildungsansatz für eine Lernfabrik vorgestellt, der insbesondere die Potenziale mobiler IIoT-Technologien zur Ausgestaltung dieser in den Blick nimmt. N2 - Recently, implementation procedures of automatic production, digitalization and Industrial Internet of Things technologies (IIoT) play an increasing role in industrial manufacturing processes. Subsequently, the competence requirements for employees change. These changes cannot be anticipated by traditional learning approaches. The following contribution faces this challenge and will show a new integrated learning factory approach which combines the application of new technologies with a flexible production environment. Thus establishing production surroundings that are familiar to the learner. The contribution demonstrates this approach using a quality control process in the context of logistics. KW - Mobile IIoT-Technologie KW - Lernszenario KW - Anwendungszentrum Industrie 4.0 KW - Lernfabrik KW - mobile IIoT-technologies KW - learning scenario KW - application center Industrie 4.0 KW - digital learning factory Y1 - 2018 U6 - https://doi.org/10.30844/I40M_18-3_S21-24 SN - 2364-9208 VL - 34 IS - 3 SP - 21 EP - 24 PB - GITO CY - Berlin 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 - CHAP A1 - Teichmann, Malte A1 - Busse, Jana A1 - Gonnermann, Jana A1 - Reimann, Daniela A1 - Ritterbusch, Georg David A1 - Langemeyer, Ines A1 - Gronau, Norbert ED - Nitsch, Verena ED - Brandl, Christopher ED - Häußling, Roger ED - Roth, Philip ED - Gries, Thomas ED - Schmenk, Bernhard T1 - Konzeption, Erstellung und Evaluation von VR-Räumen für die betriebliche Weiterbildung in KMU BT - Erfahrungen und Handlungsempfehlungen aus dem Forschungsprojekt API-KMU T2 - Digitalisierung der Arbeitswelt im Mittelstand 3 N2 - Der Beitrag adressiert die Erstellung von Virtual-Reality gestützten (Lehr- und Lern-) Räumen für 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 Ansätze zur Gestaltung digitaler Lehr- und Lernarrangements, die jedoch 1) oft Gefahr laufen, an den realen Bedürfnissen 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 könnten, äußerst rar. Der Beitrag setzt an dieser Stelle an: basierend auf zwei real existierenden betrieblichen Anwendungsfällen aus den Bereichen Natursteinbearbeitung sowie Einzel- und Sondermaschinenbau werden Herausforderungen und Lösungswege des Erstellungsprozesses von Virtual-Reality gestützten (Lehr- und Lern-)Räumen beschrieben. Ebenfalls werden basierend auf den gemachten Projekterfahrungen Handlungsempfehlungen für die gelingende Konzeption, Umsetzung und Evaluation dieser Räume formuliert. Betriebliche Beschäftigte 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 für weiterführende Forschungsvorhaben erhalten. Y1 - 2023 SN - 978-3-662-67023-1 SN - 978-3-662-67024-8 U6 - https://doi.org/10.1007/978-3-662-67024-8_5 SP - 155 EP - 204 PB - Springer Vieweg CY - Berlin ER - TY - JOUR A1 - Schüffler, Arnulf A1 - Thim, Christof A1 - Haase, Jennifer A1 - Gronau, Norbert A1 - Kluge, Annette T1 - Information processing in work environment 4.0 and the beneficial impact of intentional forgetting on change management T1 - Informationsverarbeitung in der Industrie 4.0 und die vorteilhafte Wirkung von intentionalem Vergessen für das Change Management JF - Zeitschrift für Arbeits- und Organisationspsychologie : german journal of work and organizational psychology N2 - Industry 4.0, based on increasingly progressive digitalization, is a global phenomenon that affects every part of our work. The Internet of Things (IoT) is pushing the process of automation, culminating in the total autonomy of cyber-physical systems. This process is accompanied by a massive amount of data, information, and new dimensions of flexibility. As the amount of available data increases, their specific timeliness decreases. Mastering Industry 4.0 requires humans to master the new dimensions of information and to adapt to relevant ongoing changes. Intentional forgetting can make a difference in this context, as it discards nonprevailing information and actions in favor of prevailing ones. Intentional forgetting is the basis of any adaptation to change, as it ensures that nonprevailing memory items are not retrieved while prevailing ones are retained. This study presents a novel experimental approach that was introduced in a learning factory (the Research and Application Center Industry 4.0) to investigate intentional forgetting as it applies to production routines. In the first experiment (N = 18), in which the participants collectively performed 3046 routine related actions (t1 = 1402, t2 = 1644), the results showed that highly proceduralized actions were more difficult to forget than actions that were less well-learned. Additionally, we found that the quality of cues that trigger the execution of routine actions had no effect on the extent of intentional forgetting. N2 - Industrie 4.0 ist basierend auf fortschreitender Digitalisierung eine globale Entwicklung, die in allen Bereichen uns heute bekannter Arbeits- und Lebenswelten Einzug halten wird. Das Internet der Dinge beschleunigt Automatisierung bis hin zu autonomen cyber-physischen Systemen. Dieser Prozess wird begleitet von einer weiteren Zunahme von Daten. Gleichzeitig reduziert sich die Aktualität der Daten und damit die Dauer ihrer Relevanz. Die Herausforderungen im Umfeld von Industrie 4.0 zu meistern bedeutet für Menschen in Organisationen diese wachsenden Datenmengen und Anpassung an fortwährende Veränderung zu bewältigen. Intentionales Vergessen kann hier unterstützen. Intentionales Vergessen fokussiert das Vergessen irrelevanter Informationen und Verhaltensweisen zu Gunsten relevanter. In diesem Artikel stellen wir einen experimentellen Ansatz zur Erforschung von Prozessen des intentionalen Vergessens in Organisationen in einer Laborumgebung (Anwendungszentrum Industrie 4.0) vor. Im Fokus der Untersuchung steht dabei das Vergessen einer ungültig gewordenen Produktions-Routine und das Ausführen der neuen, jetzt gültigen. Wir beschreiben dabei zunächst das innovative experimentelle Design zur Untersuchung von Vergessensprozessen. In einer ersten Untersuchung mit N = 18 Personen, die insgesamt 3046 Handlungen zu t1 (1402) und t2 (1644) ausführen, zeigte sich, dass hoch gelernte (prozeduralisierte) Handlungen schwerer zu vergessen sind als ohnehin nicht prozeduralisierte. Es zeigt sich aber kein Unterschied hinsichtlich der Art der Handlungen und der Hinweisreize, durch die sie aufgerufen werden. KW - intentional forgetting KW - retrieval cues KW - production routine KW - intentionales Vergessen KW - Produktions-Routine KW - Hinweisreize Y1 - 2019 U6 - https://doi.org/10.1026/0932-4089/a000307 SN - 0932-4089 SN - 2190-6270 VL - 64 IS - 1 SP - 17 EP - 29 PB - Hogrefe CY - Göttingen ER - TY - JOUR A1 - Rojahn, Marcel A1 - Weber, Edzard A1 - Gronau, Norbert T1 - Towards a standardization in scheduling models BT - assessing the variety of homonyms JF - International journal of industrial and systems engineering N2 - Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods. KW - job-shop scheduling KW - JSP KW - terminology KW - notation KW - standardization Y1 - 2023 UR - https://publications.waset.org/10013137/pdf SN - 1748-5037 SN - 1748-5045 VL - 17 IS - 6 SP - 401 EP - 408 PB - Inderscience Enterprises CY - Genève ER - TY - CHAP A1 - Rojahn, Marcel A1 - Gronau, Norbert T1 - Digital platform concepts for manufacturing companies BT - a review T2 - 10th International Conference on Future Internet of Things and Cloud (FiCloud) N2 - 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. Y1 - 2023 SN - 979-8-3503-1635-3 U6 - https://doi.org/10.1109/FiCloud58648.2023.00030 SP - 149 EP - 158 PB - IEEE CY - [Erscheinungsort nicht ermittelbar] ER - TY - CHAP A1 - Rojahn, Marcel A1 - Gronau, Norbert ED - Bui, Tung X. T1 - Openness indicators for the evaluation of digital platforms between the launch and maturity phase T2 - Proceedings of the 57th Annual Hawaii International Conference on System Sciences N2 - In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation. KW - federated industrial platform ecosystems KW - technologies KW - business models KW - data-driven artifacts KW - design-science research KW - digital platform openness KW - evaluation KW - morphological analysis Y1 - 2024 SN - 978-0-99813-317-1 SP - 4516 EP - 4525 PB - Department of IT Management Shidler College of Business University of Hawaii CY - Honolulu, HI ER - TY - CHAP A1 - Rojahn, Marcel A1 - Ambros, Maximilian A1 - Biru, Tibebu A1 - Krallmann, Hermann A1 - Gronau, Norbert A1 - Grum, Marcus ED - Rutkowski, Leszek ED - Scherer, Rafał ED - Korytkowski, Marcin ED - Pedrycz, Witold ED - Tadeusiewicz, Ryszard ED - Zurada, Jacek M. T1 - Adequate basis for the data-driven and machine-learning-based identification T2 - Artificial intelligence and soft computing N2 - Process mining (PM) has established itself in recent years as a main method for visualizing and analyzing processes. However, the identification of knowledge has not been addressed adequately because PM aims solely at data-driven discovering, monitoring, and improving real-world processes from event logs available in various information systems. The following paper, therefore, outlines a novel systematic analysis view on tools for data-driven and machine learning (ML)-based identification of knowledge-intensive target processes. To support the effectiveness of the identification process, the main contributions of this study are (1) to design a procedure for a systematic review and analysis for the selection of relevant dimensions, (2) to identify different categories of dimensions as evaluation metrics to select source systems, algorithms, and tools for PM and ML as well as include them in a multi-dimensional grid box model, (3) to select and assess the most relevant dimensions of the model, (4) to identify and assess source systems, algorithms, and tools in order to find evidence for the selected dimensions, and (5) to assess the relevance and applicability of the conceptualization and design procedure for tool selection in data-driven and ML-based process mining research. KW - data mining KW - knowledge engineering KW - various applications Y1 - 2023 SN - 978-3-031-42504-2 SN - 978-3-031-42505-9 U6 - https://doi.org/10.1007/978-3-031-42505-9_48 SP - 570 EP - 588 PB - Springer CY - Cham ER - TY - JOUR A1 - Panzer, Marcel A1 - Gronau, Norbert T1 - Enhancing economic efficiency in modular production systems through deep reinforcement learning JF - Procedia CIRP N2 - In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios. KW - modular production KW - production control KW - multi-agent system KW - deep reinforcement learning KW - discrete event simulation Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2023.09.229 SN - 2212-8271 VL - 121 SP - 55 EP - 60 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Deep reinforcement learning in production planning and control BT - A systematic literature review T2 - Proceedings of the Conference on Production Systems and Logistics N2 - Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations. KW - deep reinforcement learning KW - machine learning KW - production planning KW - production control KW - systematic literature review Y1 - 2021 U6 - https://doi.org/10.15488/11238 SN - 2701-6277 SP - 535 EP - 545 PB - publish-Ing. CY - Hannover ER - TY - GEN A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Deep reinforcement learning in production planning and control BT - A systematic literature review T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep reinforcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensorand process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 198 KW - deep reinforcement learning KW - machine learning KW - production planning KW - production control KW - systematic literature review Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-605722 SN - 2701-6277 SN - 1867-5808 ER - 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 - 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 - JOUR A1 - Lewandowski, Stefanie A1 - Ullrich, André A1 - Gronau, Norbert T1 - Normen zur Berechnung des CO₂-Fußabdrucks T1 - Standards for calculating a carbon footprint BT - ein Vergleich von PAS 2050, GHG Protocol und ISO 14067 JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - CO₂-Fußabdrücke sind ein aktuell viel diskutiertes Thema mit weitreichenden Implikationen für Individuen als auch Unternehmen. Firmen können einen proaktiven Beitrag zur Transparenz leisten, indem der unternehmens- oder produktbezogene CO₂-Fußabdruck ausgewiesen wird. Ist der Entschluss gefasst einen CO₂-Fußabdruck auszuweisen und die entstehenden Treibhausgase zu erfassen, existiert eine Vielzahl unterschiedlicher Normen und Zertifikate, wie die publicly available specification 2050, das Greenhouse Gas Protokoll oder die ISO 14067. Das Ziel dieses Beitrags ist es, diese drei Normen zur Berechnung des produktbezogenen CO₂-Fußabdrucks zu vergleichen, um Gemeinsamkeiten und Unterschiede sowie Vor- und Nachteile in der Anwendung aufzuzeigen. Die Übersicht soll Unternehmen bei der Entscheidungsfindung hinsichtlich der Eignung eines CO₂-Fußabdrucks für ihr Unternehmen unterstützen. N2 - Carbon footprints are a widely discussed topic impacting the individuals as well as companies. A company can be transparent in their actions, by publishing a carbon footprint. These footprints can be calculated for a single product or the whole company. However, there is a variety of different carbon footprint standards. The internationally most recognized ones are the publicly available specification 2050, Greenhouse Gas protocol (2011) and ISO 14067. This paper compares the standards and gives a recommendation for the application of product carbon footprints. KW - environmental footprint KW - product carbon footprint KW - ökologischer Fußabdruck KW - CO₂-Fußabdruck KW - PAS 2050 KW - GHG Protocol KW - ISO 14067 Y1 - 2021 U6 - https://doi.org/10.30844/I40M_21-4_S17-20 SN - 2364-9208 VL - 37 IS - 4 SP - 17 EP - 20 PB - GITO mbH Verlag CY - München ER - TY - CHAP A1 - Langemeyer, Ines A1 - Gronau, Norbert A1 - Schmid-Walz, Sabrina A1 - Kotarski, David A1 - Reimann, Daniela A1 - Teichmann, Malte T1 - From employee to expert BT - towards a corona-sensitive approach for data collection T2 - 2021 Crossing Boundaries Muttenz/Basel and Bern : 4th International VET Conference Crossing Boundaries 8 to 9 April 2021, online, Muttenz and Bern, Switzerland N2 - In the context of the collaborative project Ageing-appropriate, process-oriented and interactive further training in SME (API-KMU), innovative solutions for the challenges of demographic change and digitalisation are being developed for SMEs. To this end, an approach to age-appropriate training will be designed with the help of AR technology. In times of the corona pandemic, a special research design is necessary for the initial survey of the current state in the companies, which will be systematically elaborated in this paper. The results of the previous methodological considerations illustrate the necessity of a mix of methods to generate a deeper insight into the work processes. Video-based retrospective interviews seem to be a suitable instrument to adequately capture the employees' interpretative perspectives on their work activities. In conclusion, the paper identifies specific challenges, such as creating acceptance among employees, open questions, e.g., how a transfer or generalization of the results can succeed, and hypotheses that will have to be tested in the further course of the research process. KW - cross self-confrontation KW - recording of workplaces KW - corona-sensitive data collection KW - age-appropriate vocational training KW - augmented reality Y1 - 2021 U6 - https://doi.org/10.5281/zenodo.4590196 SP - 226 EP - 231 ER - TY - JOUR 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 JF - 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 - JOUR A1 - Haase, Jennifer A1 - Hanel, Paul H. P. A1 - Gronau, Norbert T1 - Creativity enhancement methods for adults BT - a meta-analysis JF - Psychology of aesthetics, creativity, and the arts N2 - This meta-analysis synthesizes 332 effect sizes of various methods to enhance creativity. We clustered all studies into 12 methods to identify the most effective creativity enhancement methods. We found that, on average, creativity can be enhanced, Hedges’ g = 0.53, 95% CI [0.44, 0.61], with 70.09% of the participants in the enhancement conditions being more creative than the average person in the control conditions. Complex training courses, meditation, and cultural exposure were the most effective (gs = 0.66) while the use of cognitive manipulation drugs was the least and also noneffective, g = 0.10. The type of training material was also important. For instance, figural methods were more effective in enhancing creativity, and enhancing converging thinking was more effective than enhancing divergent thinking. Study effect sizes varied considerably across all studies and for many subgroup analyses, suggesting that researchers can plausibly expect to find reversed effects occasionally. We found no evidence of publication bias. We discuss theoretical implications and suggest future directions for best practices in enhancing creativity. (PsycInfo Database Record (c) 2023 APA, all rights reserved) KW - manipulation KW - enhancement KW - assessment KW - effectiveness KW - creativity training Y1 - 2023 U6 - https://doi.org/10.1037/aca0000557 SN - 1931-3896 SN - 1931-390X PB - American Psychological Association CY - Washington, DC ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Roling, Wiebke A1 - Schüffler, Arnulf A1 - Kluge, Annette A1 - Gronau, Norbert ED - Masrour, Tawfik ED - El Hassani, Ibtissam ED - Barka, Noureddine T1 - AI case-based reasoning for artificial neural networks T2 - Artificial intelligence and industrial applications N2 - 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. KW - case-based reasoning KW - neural networks KW - industry 4.0 Y1 - 2023 SN - 978-3-031-43523-2 SN - 978-3-031-43524-9 U6 - https://doi.org/10.1007/978-3-031-43524-9_2 VL - 771 SP - 17 EP - 35 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - Aiming for knowledge-transfer-optimizing intelligent cyber-physical systems T2 - Towards sustainable customization : cridging smart products and manufacturing systems N2 - Since more and more production tasks are enabled by Industry 4.0 techniques, the number of knowledge-intensive production tasks increases as trivial tasks can be automated and only non-trivial tasks demand human-machine interactions. With this, challenges regarding the competence of production workers, the complexity of tasks and stickiness of required knowledge occur [1]. Furthermore, workers experience time pressure which can lead to a decrease in output quality. Cyber-Physical Systems (CPS) have the potential to assist workers in knowledge-intensive work grounded on quantitative insights about knowledge transfer activities [2]. By providing contextual and situational awareness as well as complex classification and selection algorithms, CPS are able to ease knowledge transfer in a way that production time and quality is improved significantly. CPS have only been used for direct production and process optimization, knowledge transfers have only been regarded in assistance systems with little contextual awareness. Embedding production and knowledge transfer optimization thus show potential for further improvements. This contribution outlines the requirements and a framework to design these systems. It accounts for the relevant factors. KW - smart automation KW - smart production KW - human-machine-interaction Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90700-6 SN - 978-3-030-90702-0 U6 - https://doi.org/10.1007/978-3-030-90700-6_16 SP - 149 EP - 157 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Rapp, Simon A1 - Gronau, Norbert A1 - Albers, Albert ED - Shishkov, Boris T1 - Accelerating knowledge BT - the speed optimization of knowledge transfers T2 - Business modeling and software design N2 - As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation. KW - knowledge transfers KW - business process optimization KW - interventions KW - product development KW - product generation engineering KW - empirical evaluation Y1 - 2019 SN - 978-3-030-24853-6 SN - 978-3-030-24854-3 U6 - https://doi.org/10.1007/978-3-030-24854-3_7 VL - 356 SP - 95 EP - 113 PB - Springer CY - Cham 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 - CHAP A1 - Grum, Marcus A1 - Kotarski, David A1 - Ambros, Maximilian A1 - Biru, Tibebu A1 - Krallmann, Hermann A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Managing knowledge of intelligent systems BT - the design of a chatbot using domain-specific knowledge T2 - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings N2 - Since more and more business tasks are enabled by Artificial Intelligence (AI)-based techniques, the number of knowledge-intensive tasks increase as trivial tasks can be automated and non-trivial tasks demand human-machine interactions. With this, challenges regarding the management of knowledge workers and machines rise [9]. Furthermore, knowledge workers experience time pressure, which can lead to a decrease in output quality. Artificial Intelligence-based systems (AIS) have the potential to assist human workers in knowledge-intensive work. By providing a domain-specific language, contextual and situational awareness as well as their process embedding can be specified, which enables the management of human and AIS to ease knowledge transfer in a way that process time, cost and quality are improved significantly. This contribution outlines a framework to designing these systems and accounts for their implementation. KW - domain-specific language KW - morphologic box KW - explainability Y1 - 2021 SN - 978-3-030-79975-5 SN - 978-3-030-79976-2 U6 - https://doi.org/10.1007/978-3-030-79976-2_5 VL - 422 SP - 78 EP - 96 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Klippert, Monika A1 - Albers, Albert A1 - Gronau, Norbert A1 - Thim, Christof T1 - Examining the quality of knowledge transfers BT - the draft of an empirical research T2 - Proceedings of the Design Society N2 - Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers. KW - knowledge management KW - new product development KW - evaluation Y1 - 2021 U6 - https://doi.org/10.1017/pds.2021.404 SN - 2732-527X VL - 1 SP - 1431 EP - 1440 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Grum, Marcus A1 - Hiessl, Werner A1 - Maresch, Karl A1 - Gronau, Norbert T1 - Design of a neuronal training modeling language BT - exemplified with the AI-based dynamic GUI adaption JF - AIS-Transactions on enterprise systems N2 - As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration. KW - AI and business informatics KW - development of AI-based systems KW - AI-based decision support system KW - cooperative AI (human-in-the-loop) KW - process-oriented knowledge acquisition KW - modeling language Y1 - 2021 UR - https://www.aes-journal.com/index.php/ais-tes/article/view/20/18 U6 - https://doi.org/10.30844/aistes.v5i1.20 SN - 1867-7134 VL - 5 IS - 1 PB - GITO-Publ., Verl. für Industrielle Informationstechnik und Organisation CY - Berlin ER - TY - CHAP A1 - Grum, Marcus A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Quantification of knowledge transfers BT - the design of an experiment setting for the examination of knowledge transfers T2 - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings N2 - Faced with the triad of time-cost-quality, the realization of knowledge-intensive tasks at economic conditions is not trivial. Since the number of knowledge-intensive processes is increasing more and more nowadays, the efficient design of knowledge transfers at business processes as well as the target-oriented improvement of them is essential, so that process outcomes satisfy high quality criteria and economic requirements. This particularly challenges knowledge management, aiming for the assignment of ideal manifestations of influence factors on knowledge transfers to a certain task. Faced with first attempts of knowledge transfer-based process improvements [1], this paper continues research about the quantitative examination of knowledge transfers and presents a ready-to-go experiment design that is able to examine quality of knowledge transfers empirically and is suitable to examine knowledge transfers on a quantitative level. Its use is proven by the example of four influence factors, which namely are stickiness, complexity, competence and time pressure. KW - knowledge management KW - knowledge transfer KW - conversion KW - empirical examination KW - experiment Y1 - 2021 SN - 978-3-030-79975-5 SN - 978-3-030-79976-2 U6 - https://doi.org/10.1007/978-3-030-79976-2_13 VL - 422 SP - 224 EP - 242 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Adaptable knowledge-driven information systems improving knowledge transfers BT - design of context-sensitive, AR-enabled furniture assemblies T2 - Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings N2 - A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS. KW - augmented reality KW - knowledge transfers KW - empirical studies KW - context-aware computing KW - adaptable software systems KW - business process improvement Y1 - 2020 SN - 978-3-030-52305-3 SN - 978-3-030-52306-0 U6 - https://doi.org/10.1007/978-3-030-52306-0_13 VL - 391 SP - 202 EP - 220 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Blunk, Oliver A1 - Rojahn, Marcel A1 - Fettke, Peter A1 - Gronau, Norbert T1 - Research challenges of knowledge modelling and the outline of a research agenda T2 - Knowledge in digital age : IFKAD 2020 KW - knowledge management KW - process modelling KW - research challenges Y1 - 2020 SN - 978-88-96687-13-0 SN - 2280-787X PB - The Arts of Business Institute CY - Matera, Italy ER - TY - CHAP A1 - Grum, Marcus A1 - Bender, Benedict A1 - Gronau, Norbert A1 - Alfa, Attahiru S. T1 - Efficient task realizations in networked production infrastructures T2 - Proceedings of the Conference on Production Systems and Logistics N2 - As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies. KW - Industry 4.0 KW - CPS KW - Decentral Decision Making KW - Industrial Analytics KW - Case Study Y1 - 2020 U6 - https://doi.org/10.15488/9682 SP - 397 EP - 407 PB - publish-Ing. CY - Hannover 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 A1 - Teichmann, Malte A1 - Weber, Edzard ED - Shishkov, Boris T1 - Serious game-based haptic modeling BT - an application-oriented approach for sequentially developing new business models from tacit knowledge T2 - Business modeling and software design N2 - The authors propose that while tacit knowledge is a valuable resource for developing new business models, its externalization presents several challenges. One major challenge is that individuals often don’t recognize their tacit knowledge resources, while another is the reluctance to share one’s knowledge with others. Addressing these challenges, the authors present an application-oriented serious game-based haptic modeling approach for externalize tacit knowledge, which can be used to develop the first versions of business models based on tacit knowledge. Both conceptual and practical design fundamentals are presented based on elaborated theoretical approaches, which were developed with the help of a design science approach. The development of the research process is presented step by step, whereby we focused on the high accessibility of the presented research. Practitioners are presented with guidelines for implementing their serious game projects. Scientists benefit from starting points for their research topics of externalization, internalization, and socialization of tacit knowledge, development of business models, and serious games or gamification. The paper concludes with open research desiderata and questions from the presented research process. KW - serious game KW - tacit knowledge KW - business model KW - SECI-model KW - conversion sequences KW - design science Y1 - 2023 SN - 978-3-031-36756-4 U6 - https://doi.org/10.1007/978-3-031-36757-1_3 SP - 32 EP - 55 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Gronau, Norbert A1 - Teichmann, Malte T1 - ERP-Auswahl für ein Professional Services Unternehmen JF - ERP-Management : Auswahl, Einführung und Betrieb von ERP-Systemen N2 - Die Branche der Dienstleistungsunternehmen (Professional Services) hat einige Anforderungen, die sie von den „klassischen“ ERP-Branchen Industrie und Handel unterscheidet. Dieser Beitrag beschreibt einige der aktuellen Herausforderungen dieses immer wichtiger werdenden Wirtschaftszweigs und geht dann am Beispiel eines mittelständischen Ingenieurdienstleisters auf typische Anforderungen dieser Branche, infrage kommende Systeme und das Vorgehen zur Auswahl ein. KW - ERP-Systeme KW - ERP-Auswahl KW - Auswahlvorgehen KW - Professional Services Unternehmen Y1 - 2020 U6 - https://doi.org/10.30844/ERP_20-2_31-35 SN - 1860-6725 VL - 16 IS - 2 SP - 31 EP - 35 PB - Gito mbh Verlag für Industrielle Informationstechnik und Organisation CY - Berlin ER - TY - JOUR A1 - Gronau, Norbert A1 - Schaefer, Martin T1 - Why metadata matters for the future of copyright JF - European Intellectual Property Review N2 - In the copyright industries of the 21st century, metadata is the grease required to make the engine of copyright run smoothly and powerfully for the benefit of creators, copyright industries and users alike. However, metadata is difficult to acquire and even more difficult to keep up to date as the rights in content are mostly multi-layered, fragmented, international and volatile. This article explores the idea of a neutral metadata search and enhancement tool that could constitute a buffer to safeguard the interests of the various proprietary database owners and avoid the shortcomings of centralised databases. KW - copyright KW - databases KW - metadata KW - music industry Y1 - 2021 SN - 0142-0461 VL - 43 IS - 8 SP - 488 EP - 494 PB - Sweet & Maxwell CY - London ER -