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Using Aggregated Discrete Event Simulation Models and Multi-Objective Optimization to Improve Real-World Factories
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-1215-152X
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: 0000-0003-0111-1776
2018 (English)In: Proceedings of the 2018 Winter Simulation Conference / [ed] M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson, IEEE, 2018, p. 2015-2024Conference paper, Published paper (Refereed)
Abstract [en]

Improving production line performance and identifying bottlenecks using simulation-based optimization has been shown to be an effective approach. Nevertheless, for larger production systems which are consisted of multiple production lines, using simulation-based optimization can be too computationally expensive, due to the complexity of the models. Previous research has shown promising techniques for aggregating production line data into computationally efficient modules, which enables the simulation of higher-level systems, i.e., factories. This paper shows how a real-world factory flow can be optimized by applying the previously mentioned aggregation techniques in combination with multi-objective optimization using an experimental approach. The particular case studied in this paper reveals potential reductions of storage levels by over 30 %, lead time reductions by 67 %, and batch sizes reduced by more than 50 % while maintaining the delivery precision of the industrial system.

Place, publisher, year, edition, pages
IEEE, 2018. p. 2015-2024
Series
Winter Simulation Conference. Proceedings., ISSN 0891-7736, E-ISSN 1558-4305
Keywords [en]
nondominated sorting approach, algorithm
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-16477DOI: 10.1109/WSC.2018.8632337ISI: 000461414102019Scopus ID: 2-s2.0-85062618810ISBN: 978-1-5386-6572-5 (electronic)ISBN: 978-1-5386-6573-2 (print)ISBN: 978-1-5386-6570-1 (electronic)ISBN: 978-1-5386-6571-8 (electronic)OAI: oai:DiVA.org:his-16477DiVA, id: diva2:1289853
Conference
Winter Simulation Conference, Gothenburg, Sweden, Decemeber 9-12, 2018
Funder
Knowledge Foundation, 20120066Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-06-18

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Lidberg, SimonPehrsson, LeifNg, Amos H. C.

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