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Combining augmented reality and simulation-based optimization for decision support in manufacturing
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineeering)
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineeering)ORCID iD: 0000-0002-9643-6233
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineeering)ORCID iD: 0000-0003-0111-1776
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineeering)
2017 (English)In: Proceedings of the 2017 Winter Simulation Conference / [ed] W. K. V. Chan, A. D’Ambrogio, G. Zacharewicz, N. Mustafee, G. Wainer, and E. Page, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3988-3999Conference paper, Published paper (Refereed)
Abstract [en]

Although the idea of using Augmented Reality and simulation within manufacturing is not a new one, the improvement of hardware enhances the emergence of new areas. For manufacturing organizations, simulation is an important tool used to analyze and understand their manufacturing systems; however, simulation models can be complex. Nonetheless, using Augmented Reality to display the simulation results and analysis can increase the understanding of the model and the modeled system. This paper introduces a decision support system, IDSS-AR, which uses simulation and Augmented Reality to show a simulation model in 3D. The decision support system uses Microsoft HoloLens, which is a head-worn hardware for Augmented Reality. A prototype of IDSS-AR has been evaluated with a simulation model depicting a real manufacturing system on which a bottleneck detection method has been applied. The bottleneck information is shown on the simulation model, increasing the possibility of realizing interactions between the bottlenecks. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 3988-3999
Series
Winter Simulation Conference. Proceedings, ISSN 0891-7736, E-ISSN 1558-4305
Keywords [en]
Artificial intelligence, Augmented reality, Automobile drivers, Decision support systems, Hardware, Optimization, Bottleneck detection, Decision supports, Manufacturing IS, Manufacturing organizations, MicroSoft, Simulation model, Simulation-based optimizations, Quality control
National Category
Computer Sciences Computer Systems Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
URN: urn:nbn:se:his:diva-15109DOI: 10.1109/WSC.2017.8248108ISI: 000427768604018Scopus ID: 2-s2.0-85044511682ISBN: 9781538634288 (electronic)ISBN: 9781538634301 (print)OAI: oai:DiVA.org:his-15109DiVA, id: diva2:1202726
Conference
2017 Winter Simulation Conference, WSC 2017, Las Vegas, USA, 3-6 December 2017
Available from: 2018-04-30 Created: 2018-04-30 Last updated: 2019-01-24Bibliographically approved

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Karlsson, IngemarBernedixen, JacobNg, Amos H. C.Pehrsson, Leif

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CiteExportLink to record
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