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Management of virtual models with provenance information in the context of product lifecycle management: industrial case studies
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0001-7612-4470
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0001-7534-0382
2019 (English)In: Product Lifecycle Management (Volume 4): The Case Studies / [ed] John Stark, Cham: Springer, 2019, 1, p. 153-170Chapter in book (Refereed)
Abstract [en]

Using virtual models instead of physical models can help industries reduce the time and cost of developments, despite the time consuming process of building virtual models. Therefore, reusing previously built virtual models instead of starting from scratch can eliminate a large amount of work from users. Is having a virtual model enough to reuse it in another study or task? In most cases, not. Information about the history of that model makes it clear for the users to decide if they can reuse this model or to what extent the model is needed to be modified. A provenance management system (PMS) has been designed to manage provenance information, and it has been used with product lifecycle management system (PLM) and computer-aided technologies (CAx) to save and present historical information about a virtual model. This chapter presents a sequence-based framework of the CAx-PLM-PMS chain and two application case studies considering the implementation of this framework.

Place, publisher, year, edition, pages
Cham: Springer, 2019, 1. p. 153-170
Series
Decision Engineering, ISSN 1619-5736, E-ISSN 2197-6589
Keywords [en]
Virtual models, Provenance, Product lifecycle management, virtual models, CAx, Discrete event simulation, Meta model, Cutting simulation
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-17765DOI: 10.1007/978-3-030-16134-7_13ISBN: 978-3-030-16133-0 (print)ISBN: 978-3-030-16134-7 (electronic)OAI: oai:DiVA.org:his-17765DiVA, id: diva2:1358118
Projects
knowledge-driven decision making in Swedish industry (KDDS)Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-07Bibliographically approved

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Morshedzadeh, ImanNg, Amos H. C.Amouzgar, Kaveh

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