Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation
Digital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research interest in academia and in...
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MDPI AG
2020-05-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/10/10/3342 |
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author | Kristina Wärmefjord Rikard Söderberg Benjamin Schleich Hua Wang |
author_facet | Kristina Wärmefjord Rikard Söderberg Benjamin Schleich Hua Wang |
author_sort | Kristina Wärmefjord |
collection | DOAJ |
description | Digital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research interest in academia and industry, identifying a larger need in industry. This indicates that there are some barriers in the industry to overcome before the benefits of a digital twin for variation management and geometry assurance can be fully capitalized on in an industrial context. To identify those barriers and challenges, an extensive interview study with engineers from eight different companies in the manufacturing sectors was accomplished. The analysis identifies industrial challenges in the areas of system-level, simulation working process, management issues, and education. One of the main challenges is to keep the 3D models fully updated, including keeping track of changes during the product development process and also feedback changes during full production to the development engineers. This is a part of what is called the digital thread, which is also addressed in this paper. |
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format | Article |
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issn | 2076-3417 |
language | English |
last_indexed | 2024-03-10T19:53:48Z |
publishDate | 2020-05-01 |
publisher | MDPI AG |
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series | Applied Sciences |
spelling | doaj.art-ad5ea78cb81541db954ffb4f02bf65a22023-11-20T00:08:36ZengMDPI AGApplied Sciences2076-34172020-05-011010334210.3390/app10103342Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the ImplementationKristina Wärmefjord0Rikard Söderberg1Benjamin Schleich2Hua Wang3Department of Industrial and Materials Sciences, Chalmers University of Technology, 41296 Gothenburg, SwedenDepartment of Industrial and Materials Sciences, Chalmers University of Technology, 41296 Gothenburg, SwedenDepartment of Mechanical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), 91054 Erlangen, GermanySchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaDigital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research interest in academia and industry, identifying a larger need in industry. This indicates that there are some barriers in the industry to overcome before the benefits of a digital twin for variation management and geometry assurance can be fully capitalized on in an industrial context. To identify those barriers and challenges, an extensive interview study with engineers from eight different companies in the manufacturing sectors was accomplished. The analysis identifies industrial challenges in the areas of system-level, simulation working process, management issues, and education. One of the main challenges is to keep the 3D models fully updated, including keeping track of changes during the product development process and also feedback changes during full production to the development engineers. This is a part of what is called the digital thread, which is also addressed in this paper.https://www.mdpi.com/2076-3417/10/10/3342digital twinmanufacturingtolerancinggeometry assurancedigital thread |
spellingShingle | Kristina Wärmefjord Rikard Söderberg Benjamin Schleich Hua Wang Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation Applied Sciences digital twin manufacturing tolerancing geometry assurance digital thread |
title | Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation |
title_full | Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation |
title_fullStr | Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation |
title_full_unstemmed | Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation |
title_short | Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation |
title_sort | digital twin for variation management a general framework and identification of industrial challenges related to the implementation |
topic | digital twin manufacturing tolerancing geometry assurance digital thread |
url | https://www.mdpi.com/2076-3417/10/10/3342 |
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