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Systematic Review Dataset: Integration of Digital Twins, Extended Reality, and Artificial Intelligence in Reconfigurable Manufacturing Systems
- Citation Author(s):
- Submitted by:
- Anjela Mayer
- Last updated:
- Sun, 11/17/2024 - 22:01
- DOI:
- 10.21227/deqs-1a94
- Data Format:
- License:
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Abstract
This dataset supports a systematic review on the integration of Digital Twins (DT), Extended Reality (XR), and Artificial Intelligence (AI) in Reconfigurable Manufacturing Systems (RMS). The data was collected during a search performed on March 3, 2024, using the Scopus database. Articles published since 2018 were screened based on predefined inclusion and exclusion criteria, resulting in 37 articles selected for qualitative analysis.
Instructions:
1. Dataset Overview
This dataset includes metadata and categorization for 147 articles initially screened from the Scopus database and the 37 articles selected for final analysis.
2. Search Strategy
- Search Date: March 3, 2024
- Database: Scopus
- Search Keys:
- RMS: ("reconfigurable OR cyber physical OR changeable OR adaptive") AND ("manufacturing OR production")
- DT: ("digital twin" OR "digital shadow" OR "virtual twin" OR "hybrid twin")
- XR: ("virtual reality" OR "augmented reality" OR "mixed reality" OR "extended reality" OR XR)
- AI: ("artificial intelligence" OR "machine learning" OR "deep learning" OR "neural networks")
3. Screening Criteria
Inclusion Criteria:
- Peer-reviewed articles published in English since 2018.
- Articles discussing DT, XR, and AI integration in RMS.
- Studies offering theoretical advancements or practical applications in CPS reconfiguration.
Exclusion Criteria:
- Articles not related to RMS or reconfiguration.
- Studies lacking evaluation, validation, or relevance to DT, XR, and AI integration.
- Review papers and non-peer-reviewed articles.