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A Study of Discrete Event Simulation Project Data and Provenance Information Management in an Automotive Manufacturing Plant
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling. (Production and automation engineering)ORCID-id: 0000-0003-3541-9330
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling. (Production and automation engineering)ORCID-id: 0000-0001-9690-890X
Volvo Car Corporation, Skövde, Sweden.ORCID-id: 0000-0003-1215-152X
Volvo Car Corporation, Skövde, Sweden.
2017 (engelsk)Inngår i: Proceedings of the 2017 Winter Simulation Conference / [ed] W. K. V. Chan; A. D’Ambrogio; G. Zacharewicz; N. Mustafee; G. Wainer; E. Page, IEEE, 2017, , s. 12s. 4012-4023Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Discrete Event Simulation (DES) project data management is a complex and important engineering activity which impacts on an organization’s efficiency. This efficiency could be decreased by the lack of provenance information or the unreliability of existing information regarding previous simulation projects, all of which complicates the reusability of the existing data. This study presents an analysis of the management of simulation projects and their provenance data, according to the different types of scenarios usually found at a manufacturing plant. A survey based on simulation projects at an automotive manufacturing plant was conducted, in order to categorize the information regarding the studied projects, map the available provenance data and standardize its management. This study also introduces an approach that demonstrates how a structured framework based on the specific data involved in the different types of scenarios could allow an improvement of the management of DES projects.

sted, utgiver, år, opplag, sider
IEEE, 2017. , s. 12s. 4012-4023
Serie
Winter Simulation Conference (WSC), E-ISSN 1558-4305 ; 2017
HSV kategori
Forskningsprogram
Produktion och automatiseringsteknik; INF201 Virtual Production Development
Identifikatorer
URN: urn:nbn:se:his:diva-14579DOI: 10.1109/WSC.2017.8248110ISI: 000427768604020Scopus ID: 2-s2.0-85044506370ISBN: 978-1-5386-3428-8 (digital)ISBN: 978-1-5386-3429-5 (digital)ISBN: 978-1-5386-3430-1 (tryckt)OAI: oai:DiVA.org:his-14579DiVA, id: diva2:1166084
Konferanse
2017 Winter Simulation Conference, Las Vegas, December 3-6, 2017
Tilgjengelig fra: 2017-12-14 Laget: 2017-12-14 Sist oppdatert: 2023-07-19bibliografisk kontrollert

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