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Digital Twins possess the capability to create virtual representations of a device’s components and dynamics. They transcend static images or blueprints, offering intricate models that reveal the entire lifecycle of system design, construction, and operation. Digital Twins now spearhead the virtual revolution, equipped to faithfully replicate each component through sensor-driven data collection. This replication aids in informed decision-making, monitoring complex systems, and validating novel products and services. Numerous companies already leverage digital twins within these domains to detect issues and enhance productivity. Conversely, accurate data collection and analysis from digital twins can pose challenges, potentially introducing ambiguity in decision-making and complicating object lifecycle management. Consequently, ongoing debates and discussions revolve around the fundamental concepts, frameworks, and technologies of digital twins. In this work, we delve into the realm of Industrial Applications of Digital Twins, exploring their merits and limitations. |
