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Applying Aggregated Line Modeling Techniques to Optimize Real World Manufacturing Systems
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Skövde, Sweden. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-1215-152x
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-4086-3877
2018 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 89-96Article in journal (Refereed) Published
Abstract [en]

The application of discrete event simulation methodology in the analysis of higher level manufacturing systems has been limited due to model complexity and the lack of aggregation techniques for manufacturing lines. Recent research has introduced new aggregation methods preparing for new approaches in the analysis of higher level manufacturing systems or networks. In this paper one of the new aggregated line modeling techniques is successfully applied on a real world manufacturing system, solving a real-world problem. The results demonstrate that the aggregation technique is adequate to be applied in plant wide models. Furthermore, in this particular case, there is a potential to reduce storage levels by over 25 %, through leveling the production flow, without compromising deliveries to customers.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 25, p. 89-96
Keywords [en]
Discrete event simulation, Aggregated line modeling, Multi-objective optimization, Manufacturing systems
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
INF203 Virtual Machining; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-16476DOI: 10.1016/j.promfg.2018.06.061Scopus ID: 2-s2.0-85062632645OAI: oai:DiVA.org:his-16476DiVA, id: diva2:1278896
Conference
8th Swedish Production Symposium, SPS, Stockholm, Sweden May 16-18, 2018
Funder
Knowledge FoundationAvailable from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-09-04Bibliographically approved

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Lidberg, SimonPehrsson, LeifFrantzén, Marcus

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