Advances in digital twin technology in industry: A review of applications, challenges, and standardization

This paper provides a comprehensive literature review on the application of digital twins (DTs) and the development of artificial intelligence (AI), big data, and building information management (BIM). Driven by the Internet of Things (IoT), big data analytics, and AI, the DT technology has become a transformative force in Industry 4.0. It enables real-time simulation, analysis, and optimization of industrial systems throughout their lifecycle, leading to significant improvements in operational efficiency and decision-making processes. This review explores the various applications, challenges, and prospects of DTs in the aerospace, manufacturing, construction, and power industries. The key challenges discussed include data management, model complexity, cybersecurity, and standardization. This review highlights the importance of addressing these challenges to realize the full potential of the DT technology in various industries while emphasizing the need for high-quality data, accurate modeling, robust security measures, and standardized evaluation criteria. As the DT technology continues to evolve, it will play a key role in advancing smart, resilient, and efficient industrial systems.