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Towards Adaptive Quality Assurance in Industrial Applications
Research Studios Austria FG, Vienna, Austria.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-5408-0008
Viewpointsystem GmbH, Vienna, Austria.
Technische Universitat Dresden, Dresden, Germany.
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2022 (English)In: Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence / [ed] Pal Varga, Lisandro Zambenedetti Granville, Alex Galis, Istvan Godor, Noura Limam, Prosper Chemouil, Jérôme François, Marc-Oliver Pahl, IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

We propose the AQUILA framework (Adaptive Quality Assurance in Industrial Applications), a concept for digitalization in Industry 4.0 to support the entire industrial manufacturing chain, laying the groundwork for adaptive quality assurance in times of disrupted supply chains and, due to the COVID-19 pandemic, restricted travel possibilities. To that end, our proposed framework allows for the definition and description of industrial processes, quality assurance and testing protocols, and training scenarios in a comprehensive notation based on BPMN, and supports users in task execution, documentation, and evaluation by providing smart glass-based HCI with eye tracking technology, delivering a combination of process documentation, context-sensitive AR visualization, gaze-based interaction schemes, and remote maintenance and assistance functionality.

Place, publisher, year, edition, pages
IEEE, 2022.
Series
IEEE/IFIP Network Operations and Management Symposium, ISSN 1542-1201, E-ISSN 2374-9709
Keywords [en]
smart manufacturing, process modelling, cyber-physical systems, smart glasses, augmented reality
National Category
Computer Sciences Software Engineering
Research subject
Cyber-Physical Systems
Identifiers
URN: urn:nbn:se:ltu:diva-91526DOI: 10.1109/NOMS54207.2022.9789928ISI: 000851572700181Scopus ID: 2-s2.0-85133170299ISBN: 978-1-6654-0602-4 (print)ISBN: 978-1-6654-0601-7 (electronic)OAI: oai:DiVA.org:ltu-91526DiVA, id: diva2:1671316
Conference
IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, Hungary, April 25-29, 2022
Available from: 2022-06-17 Created: 2022-06-17 Last updated: 2022-09-23Bibliographically approved

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Bodin, Ulf

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