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Adaptive instructions to novice shop-floor operators using Augmented Reality
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. (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: 0000-0003-3973-3394
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and automation engineering)
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2017 (English)In: Journal of Industrial and Production Engineering, ISSN 2168-1015, Vol. 34, no 5, 362-374 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 34, no 5, 362-374 p.
Keyword [en]
Adaptive instructions, Augmented reality, Shop-floor operators, Expert systems, Shop-floor support
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-13565DOI: 10.1080/21681015.2017.1320592ISI: 000409142300004Scopus ID: 2-s2.0-85018720899OAI: oai:DiVA.org:his-13565DiVA: diva2:1103988
Projects
SYMBIO-TIC [637107] & YOU2 [20130303]
Funder
Knowledge Foundation, 20130303EU, Horizon 2020, 637107
Available from: 2017-05-31 Created: 2017-05-31 Last updated: 2017-11-27Bibliographically approved

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Holm, MagnusDanielsson, OscarSyberfeldt, AnnaMoore, PhilipWang, Lihui

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Citation style
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