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Verification and validation of digital twins: a systematic literature review for manufacturing applications.

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Title: Verification and validation of digital twins: a systematic literature review for manufacturing applications.
Authors: Bitencourt, Julia1 (AUTHOR) jzb0172@auburn.edu, Wooley, Ana2 (AUTHOR), Harris, Gregory1 (AUTHOR)
Source: International Journal of Production Research. Jan2025, Vol. 63 Issue 1, p342-370. 29p.
Subjects: Digital twin, Technological innovations, Trust, Industry 4.0, Research personnel
Abstract: Digital Twin (DT) is a concept of growing interest, driven by the technological advancements related to Industry 4.0. DT combines innovative technologies to create a virtual model replicating the physical system and allowing bi-directional data flow. However, to use DTs in support of decision-making, it is essential to have trust in the model and all components of the DT throughout its development. Verification and Validation (V&V) have traditionally been employed to assess models' credibility, providing a venue for the development of trust. Therefore, V&V are essential foundations for developing DTs that can support decisions in real-world environments. Through a systematic literature review, this research investigated whether and how researchers are employing V&V in DTs for manufacturing applications. It was concluded that very little research was reported to have performed both verification and validation of the developed DTs. The study also examined the most commonly used V&V techniques and explored their relationship with DT capability level and application areas. It was concluded that there is a lack of standard procedures to conduct V&V and a lack of agreement on the V&V objectives. This research uncovers the main challenges to verifying and validating DTs and future research directions to develop trusted DTs. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Verification and validation of digital twins: a systematic literature review for manufacturing applications.
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  Data: <searchLink fieldCode="AR" term="%22Bitencourt%2C+Julia%22">Bitencourt, Julia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jzb0172@auburn.edu</i><br /><searchLink fieldCode="AR" term="%22Wooley%2C+Ana%22">Wooley, Ana</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Harris%2C+Gregory%22">Harris, Gregory</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jan2025, Vol. 63 Issue 1, p342-370. 29p.
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  Data: <searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+innovations%22">Technological innovations</searchLink><br /><searchLink fieldCode="DE" term="%22Trust%22">Trust</searchLink><br /><searchLink fieldCode="DE" term="%22Industry+4%2E0%22">Industry 4.0</searchLink><br /><searchLink fieldCode="DE" term="%22Research+personnel%22">Research personnel</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Digital Twin (DT) is a concept of growing interest, driven by the technological advancements related to Industry 4.0. DT combines innovative technologies to create a virtual model replicating the physical system and allowing bi-directional data flow. However, to use DTs in support of decision-making, it is essential to have trust in the model and all components of the DT throughout its development. Verification and Validation (V&V) have traditionally been employed to assess models' credibility, providing a venue for the development of trust. Therefore, V&V are essential foundations for developing DTs that can support decisions in real-world environments. Through a systematic literature review, this research investigated whether and how researchers are employing V&V in DTs for manufacturing applications. It was concluded that very little research was reported to have performed both verification and validation of the developed DTs. The study also examined the most commonly used V&V techniques and explored their relationship with DT capability level and application areas. It was concluded that there is a lack of standard procedures to conduct V&V and a lack of agreement on the V&V objectives. This research uncovers the main challenges to verifying and validating DTs and future research directions to develop trusted DTs. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/00207543.2024.2357741
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        Text: English
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        Type: general
      – SubjectFull: Technological innovations
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      – SubjectFull: Trust
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      – SubjectFull: Industry 4.0
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              Text: Jan2025
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