Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
Digital Factories & Industry 4.0 1
Time:
Monday, 09/Mar/2020:
1:30pm - 3:00pm

Session Chair: Sander Lass
Session Chair: Barbara Dinter
Session Chair: Rainer Alt
Location: S24

Presentations

Edge Computing: A Comprehensive Survey of Current Initiatives and a Roadmap for a Sustainable Edge Computing Development

Andrea Hamm1,2, Alexander Willner2,3, Ina Schieferdecker1,2

1Weizenbaum Institute for the Networked Society; 2TU Berlin; 3Fraunhofer FOKUS

Edge Computing is a new distributed Cloud Computing paradigm in which computing and storage capabilities are pushed to the topological edge of a network. However, various standards and implementations are promoted by different initiatives. Lead by a reference architecture model for Edge Computing, current initiatives are analyzed by explorative content analysis. Providing two main contributions to the field, we present, first, how current initiatives are characterized, and second, a roadmap for sustainable Edge Computing relating three dimensions of sustainable development to four cross-concerns of Edge Computing. Findings show that most initiatives are internationally organized software development projects; important branches are currently telecom and industrial sectors; most addressed is the network virtualization layer. The roadmap reveals numerous chances and risks of Edge Computing related to sustainable development; such as the use of renewable energies, biases, new business models, increase and decrease of energy consumption, responsiveness, monitoring and traceability.



Design and Implementation of a Decision Support System for Production Scheduling in the Context of Cyber-Physical Systems

Pascal Freier, Matthias Schumann

University of Goettingen, Germany

The use of cyber-physical systems in production promises great potential for production scheduling since a larger information base is available for the scheduling of production orders. However, the mere acquisition of real-time data does not inherently lead to improvements. On the contrary, a targeted preparation of the data is required in order to prevent an information overload. Decision support systems that support decision makers in production scheduling can perform this task. However, the design of such systems in combination with cyber-physical systems has hardly been investigated so far. In this paper, we therefore design and implement a corresponding decision support system in a design science approach. For this, we identify meta-requirements based on a literature analysis and an interview study. Finally, we evaluate the created meta-artifact in a laboratory setting in order to obtain generalizable knowledge about building such a decision support system.



Der Mittelstand auf dem Weg zur intelligenten Fabrik: Adoptionsdeterminanten tragbarer Augmented-Reality-Assistenzsysteme

Julian Schuir, Frank Teuteberg

Fachgebiet Unternehmensrechnung und Wirtschaftsinformatik, Universität Osnabrück, Katharinenstraße 1, 49069 Osnabrück, Deutschland

Augmented-Reality-Assistenzsysteme unterstützen Arbeitsprozesse aktiv im Sinne einer intelligenten Fabrik. Sie bieten insbesondere kleinen und mittelständischen Unternehmen (KMU) aus dem produzierenden Gewerbe Vorteile, indem die menschlich induzierte Fehlerquote reduziert und Einarbeitungsprozesse effizienter gestaltet werden können. Dennoch stellt ihre Adoption in der Praxis bisher eine Seltenheit dar. Ziel dieses Beitrages ist es daher, die Adoptionsdeterminanten von Augmented-Reality-Assistenzsystemen in KMU mithilfe des Technology-Organization-Environment-Frameworks und qualitativer Forschung in Form von semi-strukturierten Interviews zu explorieren. Die Ergebnisse zeigen u. a., dass organisatorische Aspekte wie fehlendes Expertenwissen sowie die Qualifikation der Mitarbeiter die Adoption beeinflussen.