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Aggregated models for decision-support in manufacturing systems management
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-0880-2572
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)
2021 (English)In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 16, no 3, p. 217-240Article in journal (Refereed) Published
Abstract [en]

Many industrial challenges can be related to the setup of manufacturing plants and supply chains. While there are techniques available for discrete event simulation of production lines, the opportunities of applying such techniques on higher manufacturing network levels are not explored to the same extent. With established methods for optimisation of manufacturing lines showing proven potential in conceptual analysis and development of production lines, the application of such optimisation methods on higher level manufacturing networks is a subject for further exploration. In this paper, an extended aggregation technique for discrete event simulation of higher level manufacturing systems is discussed, proposed, tested, and verified with real-world problem statements as a proof of concept. The contribution of the new technique is to enable the application of DES models, with reasonable computational requirements, at higher level manufacturing networks. The proposed technique can be used to generate valuable decision information supporting conceptual systems development.

Place, publisher, year, edition, pages
InderScience Publishers, 2021. Vol. 16, no 3, p. 217-240
Keywords [en]
aggregation, discrete event simulation, DES, optimisation, decision-support, manufacturing systems management
National Category
Computer Sciences
Research subject
VF-KDO; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-21820DOI: 10.1504/IJMR.2021.117926ISI: 000849830400001OAI: oai:DiVA.org:his-21820DiVA, id: diva2:1696259
Part of project
Virtual factories with knowledge-driven optimization (VF-KDO), Knowledge Foundation
Note

Pehrsson, Leif (corresponding author)

Available from: 2022-09-16 Created: 2022-09-16 Last updated: 2024-06-19Bibliographically approved

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Pehrsson, LeifAslam, Tehseen

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