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Digital Twin: Applying emulation for machine reconditioning
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-9204-4603
Projektengagemang Industri & Energi Sverige AB, El & Automation, Skövde, Sweden.
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
2018 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 243-248Article in journal (Refereed) Published
Abstract [en]

Old machine reconditioning projects extend the life length of machines with reduced investments, however they frequently involve complex challenges. Due to the lack of technical documentation and the fact that the machines are running in production, they can require a reverse engineering phase and extremely short commissioning times. Recently, emulation software has become a key tool to create Digital Twins and carry out virtual commissioning of new manufacturing systems, reducing the commissioning time and increasing its final quality. This paper presents an industrial application study in which an emulation model is used to support a reconditioning project and where the benefits gained in the working process are highlighted.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 72, p. 243-248
Keywords [en]
digital twin, emulation, virtual commissioning, industry 4.0, reconditioning, retrofitting
National Category
Control Engineering
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-16078DOI: 10.1016/j.procir.2018.03.139ISI: 000526120800042Scopus ID: 2-s2.0-85049565560OAI: oai:DiVA.org:his-16078DiVA, id: diva2:1241633
Conference
51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018
Projects
Twin
Note

CC BY-NC-ND 4.0

Edited by Lihui Wang

Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2022-12-30Bibliographically approved

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fulltext(1472 kB)396 downloads
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Ayani, MikelNg, Amos H. C.

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