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Augmented Reality Smart Glasses in the Smart Factory: Product Evaluation Guidelines and Review of Available Products
University of Skövde, School of Engineering Science. (Produktion och Automatiseringsteknik)ORCID iD: 0000-0003-3973-3394
University of Skövde, School of Engineering Science. (Produktion och Automatiseringsteknik)ORCID iD: 0000-0001-9512-7554
University of Skövde, School of Engineering Science. (Produktion och Automatiseringsteknik)ORCID iD: 0000-0001-8874-0676
2017 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 5, no 1, 9118-9130 p.Article in journal (Refereed) Published
Abstract [en]

Augmented reality smart glasses (ARSG) are increasingly popular and have been identified as a vital technology supporting shop-floor operators in the smart factories of the future. By improving our knowledge of how to efficiently evaluate and select ARSG for the shop-floor context, this paper aims to facilitate and accelerate the adoption of ARSG by the manufacturing industry. The market for ARSG has exploded in recent years, and the large variety of products to select from makes it not only difficult but also time consuming to identify the best alternative. To address this problem, this paper presents an efficient step-by-step process for evaluating ARSG, including concrete guidelines as to what parameters to consider and their recommended minimum values. Using the suggested evaluation process, manufacturing companies can quickly make optimal decisions about what products to implement on their shop floors. The paper demonstrates the evaluation process in practice, presenting a comprehensive review of currently available products along with a recommended best buy. The paper also identifies and discusses topics meriting research attention to ensure that ARSG are successfully implemented on the industrial shop floor.

Place, publisher, year, edition, pages
2017. Vol. 5, no 1, 9118-9130 p.
Keyword [en]
Augmented reality smart glasses, smart factory, augmented reality, industrial operator support
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-13922DOI: 10.1109/ACCESS.2017.2703952ISI: 000404270600043OAI: oai:DiVA.org:his-13922DiVA: diva2:1127484
Available from: 2017-07-15 Created: 2017-07-15 Last updated: 2017-07-19

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Syberfeldt, AnnaDanielsson, OscarGustavsson, Patrik
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CiteExportLink to record
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Citation style
  • apa
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  • ieee
  • modern-language-association-8th-edition
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  • de-DE
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