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Digital twin (DT) is an emerging concept in the Industry 4.0 era. It integrates intelligence into industrial processes. The broadness of DT’s concept allows for multiple definitions and designs to be labeled as DTs. However, general-purpose DTs are still out of reach due to the lack of consensus, tool dependency, and the focus on system integration. In this paper, a general-purpose DT framework is proposed by utilizing distributed system concepts. Data acquisition, system modeling, and intelligence applications are modularized in order to enable framework generality. Digital shadow (DS) is implemented as a core component of DT, which provides a real-time virtual replica of its physical counterpart. DT applications utilize DS models for recommending intelligent decisions. A systematic modeling approach is designed by differentiating between DS models and DT applications. The proposed approach defines the …