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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Main Authors: Kristina Wärmefjord, Rikard Söderberg, Benjamin Schleich, Hua Wang
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Applied Sciences
Subjects:
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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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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