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Dynamic operator instructions based on augmented reality and rule-based expert systems
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-9512-7554
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-1699-3778
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Royal Institute of Technology, Stockholm, Sweden. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-8679-8049
2016 (English)In: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems / [ed] Roberto Teti, Elsevier, 2016, Vol. 41, 346-351 p.Conference paper, Published paper (Refereed)
Abstract [en]

Augmented reality is currently a hot research topic within manufacturing and a great potential of the technique is seen. In this study, we aim to increase the knowledge of the adaptation and usability of augmented reality for the training of operators. We propose an approach of using dynamic information content that is automatically adjusted to the individual operator and his/her learning progress for increased efficiency and shorter learning times. The approach make use of the concept of expert systems from the field of artificial intelligence for determine the information content on-line. We develop a framework called "Augmented Reality Expert System" (ARES) that combines AR and expert systems. A proof-of-concept evaluation of the framework is presented in the paper and possible future extensions are discussed.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 41, 346-351 p.
Series
Procedia CIRP, ISSN 2212-8271 ; 41
National Category
Other Mechanical Engineering
Research subject
Technology; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-11331DOI: 10.1016/j.procir.2015.12.113ISI: 000379247600059Scopus ID: 2-s2.0-84968830717OAI: oai:DiVA.org:his-11331DiVA: diva2:845096
Conference
CIRP CMS 2015, 48th CIRP Conference on Manufacturing Systems, Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future, 24-26 June 2015, Ischia (Naples), Italy
Available from: 2015-08-10 Created: 2015-08-10 Last updated: 2017-11-27Bibliographically approved

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Syberfeldt, AnnaDanielsson, OscarHolm, MagnusWang, Lihui

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CiteExportLink to record
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