Integrating Digital Twin Software Solutions with Collaborative Industrial Systems: A Comprehensive Review for Operational Efficiency
The integration of digital twin software solutions with industrial collaborative robotics applications has gained significant attention due to its potential to enhance operational efficiency in various industries. The authors of this paper provide a comprehensive review of the literature, analyzing...
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Published in | Applied sciences Vol. 15; no. 13; p. 7049 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
01.07.2025
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Subjects | |
Online Access | Get full text |
ISSN | 2076-3417 2076-3417 |
DOI | 10.3390/app15137049 |
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Summary: | The integration of digital twin software solutions with industrial collaborative robotics applications has gained significant attention due to its potential to enhance operational efficiency in various industries. The authors of this paper provide a comprehensive review of the literature, analyzing the benefits, challenges, and opportunities associated with this unification. The research methodology incorporates both quantitative and qualitative analyses of relevant scholarly articles, case studies, and industry reports. The study identifies research gaps and challenges, including data management, security, scalability, interoperability, and transitioning simulations to digital twins. To address these gaps, the authors explore published frameworks for effectively integrating digital twin software solutions with industrial collaborative robotics applications. An important challenge is to define some tools to develop a digital twin. This paper explores the tools implemented by other researchers to develop a digital twin. The findings of this research contribute to a deeper understanding of the combination of digital twins and collaborative robots, paving the way for improved operational efficiency and informed decision-making. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app15137049 |