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 - 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 - Hesse, Günter A1 - Matthies, Christoph A1 - Sinzig, Werner A1 - Uflacker, Matthias T1 - Adding Value by Combining Business and Sensor Data BT - an Industry 4.0 Use Case T2 - Database Systems for Advanced Applications N2 - Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs. KW - Industry 4.0 KW - Internet of Things KW - Data integration Y1 - 2019 SN - 978-3-030-18590-9 SN - 978-3-030-18589-3 U6 - https://doi.org/10.1007/978-3-030-18590-9_80 SN - 0302-9743 SN - 1611-3349 VL - 11448 SP - 528 EP - 532 PB - Springer CY - Cham ER - TY - JOUR A1 - Bender, Benedict A1 - Lass, Sander A1 - Habib, Natalie A1 - Scheel, Laura T1 - Plattform-Bereitstellungsstrategien im Maschinen- und Anlagenbau T1 - Platform Delivery Strategies in Mechanical and Plant Engineering BT - Strategien deutscher Unternehmen im Industrie 4.0-Kontext BT - Strategies of German Companies in the Industry 4.0 Context JF - HMD - Praxis der Wirtschaftsinformatik N2 - Digitale Plattformen finden zunehmende Verbreitung in unterschiedlichen Industriezweigen. Immer mehr Unternehmen sind an der Erschließung verbundener Potenziale für ihr Geschäft interessiert. Im Maschinen- und Anlagenbau wird die Vernetzung von Maschinen zunehmend ein Wettbewerbsfaktor für Hersteller. Der Einsatz digitaler Plattformen im Maschinen- und Anlagenbau bietet Herstellern Möglichkeiten zur gezielten Erweiterung des Geschäftsmodells. Für die Bereitstellung digitaler Plattformen können Unternehmen auf unterschiedliche Strategien zurückgreifen. Hierbei sollten Unternehmen die für ihre Konstellation geeignete Variante systematisch identifizieren, um die angestrebten Ziele zu erreichen. Die geeignete Strategie ist von einer Vielzahl an Faktoren abhängig. Als Grundlage für die Identifikation der geeigneten Strategie bietet dieser Beitrag eine systematische Untersuchung der möglichen Bereitstellungsstrategien für Unternehmen. Neben der theoretischen Systematisierung werden gegenwärtig genutzte Strategien am Beispiel des Maschinen- und Anlagenbaus in Deutschland vorgestellt. Zudem werden spezifische Merkmale, welche die Nutzung einer Strategie beeinflussen, als Ansatzpunkt für einen Strategieformulierungsprozess identifiziert. Im Maschinen- und Anlagenbau ist die Bereitstellung einer eigenen Plattform, insbesondere bei Großunternehmen vorherrschend. Die Strategien von KMU unterschieden sich von Großunternehmen. N2 - Digital platforms are becoming increasingly widespread across different industries. More and more companies are interested in developing related potential for their business. In mechanical and plant engineering, the networking of machines becomes increasingly important and a strategic advantage for manufacturers. The use of digital platforms in mechanical and plant engineering offers manufacturers opportunities for targeted expansion of their business model. For the provision of digital platforms, companies can use different strategical approaches. Companies should systematically identify the variant suitable for their constellation in order to achieve the desired objectives. The appropriate strategy depends on a variety of factors. As a basis for the identification of the appropriate strategy, this article offers a systematic overview of the possible deployment strategies for companies. In addition to the theoretical systematization, currently used strategies are presented using the example of the mechanical and plant engineering industry in Germany. In addition, specific features that influence the use of a strategy are identified as a starting point for a strategy formulation process. In mechanical and plant engineering, the provision of an own platform is predominant, especially in large companies. The strategies of SMEs differ from those of large companies. KW - Digitale Plattformen KW - KMU KW - Maschinen- und Anlagenbau KW - Industrie 4.0 KW - Plattform-Bereitstellungsstrategien KW - Digital platforms KW - SME KW - Machinery and plant engineering KW - Industry 4.0 KW - Platform delivery strategies Y1 - 2020 U6 - https://doi.org/10.1365/s40702-020-00648-1 SN - 2198-2775 SN - 1436-3011 IS - 58 SP - 645 EP - 660 PB - Springer CY - Wiesbaden ER - TY - JOUR A1 - Beier, Grischa A1 - Ullrich, André A1 - Niehoff, Silke A1 - Reißig, Malte A1 - Habich, Matthias T1 - Industry 4.0 BT - how it is defined from a sociotechnical perspective and how much sustainability it includes - a literature review JF - Journal of cleaner production N2 - Industry 4.0 has had a strong influence on the debate on the digitalization of industrial processes, despite being criticized for lacking a proper definition. However, Industry 4.0 might offer a huge chance to align the goals of a sustainable development with the ongoing digital transformation in industrial development. The main contribution of this paper is therefore twofold. We provide a de-facto definition of the concept "Industry 4.0" from a sociotechnical perspective based on its most often cited key features, as well as a thorough review of how far the concept of sustainability is incorporated in it. KW - sustainability KW - digitalization KW - manufacturing KW - Industry 4.0 KW - definition KW - sociotechnical approach Y1 - 2020 U6 - https://doi.org/10.1016/j.jclepro.2020.120856 SN - 0959-6526 SN - 1879-1786 VL - 259 PB - Elsevier Science CY - Amsterdam ER - 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 - JOUR A1 - Vladova, Gergana A1 - Heuts, Alexander A1 - Teichmann, Malte T1 - Dem Mitarbeiter zu Diensten T1 - At the Service of the Employee BT - Weiterbildung und Qualifizierung als Personennahe Dienstleistung BT - Further Training and Qualification as a Personal Service JF - HMD : Praxis der Wirtschaftsinformatik N2 - Die Weiterbildung und Qualifizierung der Mitarbeiter sind zentrale Erfolgsfaktoren des digitalen Wandels. Die zentrale Herausforderung besteht darin, diese maßgeschnitten anzubieten sowie notwendige Akzeptanz nicht vorauszusetzen, sondern ebenso als Zielgröße anzusehen. Dies geschieht jedoch nur, wenn die Mitarbeiter als Partner gesehen werden, deren Bedürfnisse und Verständnis nachhaltig berücksichtigt werden. Dieser Beitrag schlägt vor diesem Hintergrund einen Ansatz vor, Weiterbildung als Personennahe Dienstleistung zu realisieren. Dafür wird zuerst ein skizzenhafter Überblick über grundlegende Kompetenzanforderungen des digitalen Wandels gegeben. Danach wird die aktuelle Situation betrieblicher Weiterbildung in der digitalen Transformation beleuchtet. Hierzu wurde in einem Zeitraum von sechs Monaten im Rahmen einer quantitativen Untersuchung erhoben, wie Beschäftigte die digitale Transformation ihres Unternehmens und daraus resultierende Bedarfe betrieblicher Weiterbildung wahrnehmen. Darauf basierend werden drei aktuelle Paradoxe abgeleitet, die mit einer Durchführung von Weiterbildung als Personennahe Dienstleistung verhindert werden können. Empfehlungen und Lösungsansätze werden hierzu diskutiert und weiterer Forschungsbedarf abgeleitet. N2 - The further training and qualification of employees are central success factors of digital change. The central challenge is to offer these customized services and not to presuppose acceptance, but rather to regard it as a target value. However, this will only happen if the employees are seen as partners and their needs and understanding are taken into account in the long term. Against this background, this article proposes an approach to realize further education as a personal service. For this purpose, a brief outline of the basic competence requirements of digital change is given first. Afterwards, the current situation of in-company continuing training in the digital transformation will be examined. A quantitative survey was conducted over a period of six months to determine how employees perceive the digital transformation of their company and the resulting needs for continuing vocational training. Based on this, three current paradoxes are derived, which can be prevented by conducting continuing education as personal service. Recommendations and solutions will be discussed and further research is needed. KW - Digitale Transformation KW - Kompetenzentwicklung KW - Weiterbildung KW - Industrie 4.0 KW - Personalisierung KW - Personennahe Dienstleistungen KW - Digital transformation KW - Competence development KW - Further education KW - Industry 4.0 KW - Personalization KW - Personal service Y1 - 2021 U6 - https://doi.org/doi.org/10.1365/s40702-020-00626-7 SN - 1436-3011 SN - 2198-2775 IS - 57 SP - 710 EP - 721 PB - Springer CY - Wiesbaden ER - TY - THES A1 - Grum, Marcus T1 - Construction of a concept of neuronal modeling N2 - The business problem of having inefficient processes, imprecise process analyses, and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating, and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS), and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes. N2 - Die vorliegende Arbeit addressiert das Geschäftsproblem von ineffizienten Prozessen, unpräzisen Prozessanalysen und -simulationen sowie untransparenten künstlichen neuronalen Netzwerken, indem ein Modellierungskonzept zum Neuronalen Modellieren konstruiert wird. Dieses neuartige Konzept des Neuronalen Modellierens (CoNM) fungiert als flexibler und effizienter Ansatz zum Modellieren, Simulieren und Optimieren von Prozessen mit Hilfe von neuronalen Netzwerken und wird mittels einer Modellierungssprache, dessen mathematischen Formalisierung und technischen Substanziierung sowie einer Sammlung von neuartigen Subartefakten beschrieben. In der Verwendung derer Implementierung als CoNM-Werkzeuge können somit neue Arten einer Neuronalen-Prozess-Modellierung (NPM), Neuronalen-Prozess-Simulation (NPS) sowie Neuronalen-Prozess-Optimierung (NPO) realisiert werden. Die Wirksamkeit der erstellten Artefakte wurde anhand von sechs Experimenten demonstriert sowie in einem Simulator in realen Produktionsprozessen gezeigt. T2 - Konzept des Neuronalen Modellierens KW - Deep Learning KW - Artificial Neuronal Network KW - Explainability KW - Interpretability KW - Business Process KW - Simulation KW - Optimization KW - Knowledge Management KW - Process Management KW - Modeling KW - Process KW - Knowledge KW - Learning KW - Enterprise Architecture KW - Industry 4.0 KW - Künstliche Neuronale Netzwerke KW - Erklärbarkeit KW - Interpretierbarkeit KW - Geschäftsprozess KW - Simulation KW - Optimierung KW - Wissensmanagement KW - Prozessmanagement KW - Modellierung KW - Prozess KW - Wissen KW - Lernen KW - Enterprise Architecture KW - Industrie 4.0 Y1 - 2021 ER -