Series Vol. 12 , 17 November 2023
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Digital twin (DT) is considered one of the most promising enabling technologies for achieving intelligent manufacturing and Industry 4.0. The key characteristic of DT is the seamless integration between the cyber and physical spaces. The significance of DT is increasingly recognized by the academic and industrial communities. To understand the development and application of DT in industry, this paper provides an in-depth review of the research status of key components of DT, the current state of DT development, and its major applications in aerospace, industrial manufacturing and smart cities. This paper also outlines some potential directions for future work and discusses current challenges. First, the integration of machine learning algorithms with digital twins can enable more complex data analysis, decision-making, and predictive capabilities. Second, the application of blockchain technology in digital twin ecosystems can increase the potential for secure and transparent data sharing and collaboration. Finally, the expansion of the scope of digital twins can achieve environmental sustainability.
digital twin(DT), Industry 4.0, aerospace, industrial manufacturing, smart cities
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.