TY - JOUR A1 - Dragičević, Nikolina A1 - Ullrich, André A1 - Tsui, Eric A1 - Gronau, Norbert T1 - A conceptual model of knowledge dynamics in the industry 4.0 smart grid scenario JF - Knowledge management research & practice : KMRP N2 - Technological advancements are giving rise to the fourth industrial revolution - Industry 4.0 -characterized by the mass employment of smart objects in highly reconfigurable and thoroughly connected industrialproduct-service systems. The purpose of this paper is to propose a theory-based knowledgedynamics model in the smart grid scenario that would provide a holistic view on the knowledge-based interactions among smart objects, humans, and other actors as an underlyingmechanism of value co-creation in Industry 4.0. A multi-loop and three-layer - physical, virtual, and interface - model of knowledge dynamics is developedby building on the concept of ba - an enabling space for interactions and theemergence of knowledge. The model depicts how big data analytics are just one component inunlocking the value of big data, whereas the tacit engagement of humans-in-the-loop - theirsense-making and decision-making - is needed for insights to be evoked fromanalytics reports and customer needs to be met. KW - Industry 4.0 KW - tacit knowledge KW - humans-in-the-loop KW - big data analytics KW - internet of things and services KW - smart grid Y1 - 2020 U6 - https://doi.org/10.1080/14778238.2019.1633893 SN - 1477-8238 SN - 1477-8246 VL - 18 IS - 2 SP - 199 EP - 213 PB - Taylor & Francis CY - London [u.a.] 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 - JOUR A1 - Lass, Sander A1 - Gronau, Norbert T1 - A factory operating system for extending existing factories to Industry 4.0 JF - Computers in industry : an international, application oriented research journal N2 - Cyber-physical systems (CPS) have shaped the discussion about Industry 4.0 (I4.0) for some time. To ensure the competitiveness of manufacturing enterprises the vision for the future figures out cyber-physical production systems (CPPS) as a core component of a modern factory. Adaptability and coping with complexity are (among others) potentials of this new generation of production management. The successful transformation of this theoretical construct into practical implementation can only take place with regard to the conditions characterizing the context of a factory. The subject of this contribution is a concept that takes up the brownfield character and describes a solution for extending existing (legacy) systems with CPS capabilities. KW - Factory operating system KW - CPPS KW - CPS KW - Decentralized production control KW - Industry 4.0 KW - retrofit Y1 - 2019 U6 - https://doi.org/10.1016/j.compind.2019.103128 SN - 0166-3615 SN - 1872-6194 VL - 115 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Bender, Benedict A1 - Grum, Marcus A1 - Gronau, Norbert A1 - Alfa, Attahiru A1 - Maharaj, B. T. T1 - Design of a worldwide simulation system for distributed cyber-physical production networks T2 - 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) N2 - Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example. KW - production networks KW - geographical distribution KW - task realization strategies KW - Industry 4.0 KW - simulation KW - evaluation Y1 - 2019 SN - 978-1-7281-3401-7 SN - 978-1-7281-3402-4 U6 - https://doi.org/10.1109/ICE.2019.8792609 SN - 2334-315X PB - IEEE CY - New York ER - TY - GEN A1 - Grum, Marcus A1 - Gronau, Norbert T1 - Process modeling within augmented reality BT - the bidirectional interplay of two worlds T2 - Business Modeling and Software Design, BMSD 2018 N2 - The collaboration during the modeling process is uncomfortable and characterized by various limitations. Faced with the successful transfer of first process modeling languages to the augmented world, non-transparent processes can be visualized in a more comprehensive way. With the aim to rise comfortability, speed, accuracy and manifoldness of real world process augmentations, a framework for the bidirectional interplay of the common process modeling world and the augmented world has been designed as morphologic box. Its demonstration proves the working of drawn AR integrations. Identified dimensions were derived from (1) a designed knowledge construction axiom, (2) a designed meta-model, (3) designed use cases and (4) designed directional interplay modes. Through a workshop-based survey, the so far best AR modeling configuration is identified, which can serve for benchmarks and implementations. KW - Augmented reality KW - Process modeling KW - Simulation process building KW - Generalized knowledge constructin axiom KW - Meta-model KW - Use cases Morphologic box KW - Industry 4.0 KW - CPS KW - CPPS KW - Internet of things Y1 - 2018 SN - 978-3-319-94214-8 SN - 978-3-319-94213-1 U6 - https://doi.org/10.1007/978-3-319-94214-8_7 SN - 1865-1348 VL - 319 SP - 99 EP - 115 PB - Springer CY - Berlin ER -