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Creators/Authors contains: "Balta, Efe"

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  1. ; ; ; (, 2020 American Control Conference)
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  2. ; ; (, 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE))
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  3. ; ; (, 2019 American Control Conference)
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  4. ; ; ; ; ; ; (, IEEE Access)
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  5. ; ; ; ; (, 2019 American Control Conference)
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  6. ; ; ; ; ; ; ; (, IEEE International Conference on Automation Science and Engineering (CASE))
    Digital Twin (DT) is one of the key enabling technologies for realizing the promise of Smart Manufacturing (SM) and Industry 4.0 to improve production systems operation. Driven by the generation and analysis of high volume data coming from interconnected cyber and physical spaces, DTs are real-time digital images of physical systems, processes or products that help evaluate and improve business performance. This paper proposes a novel DT architecture for the real- time monitoring and evaluation of large-scale SM systems. An application to a manufacturing flow-shop is presented to illustrate the usefulness of the proposed methodology. 
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    Accepted Manuscript Full Text Available
  7. ; ; ; ; ; ; ; (, 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE))
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  8. ; ; ; ; ; ; ; (, IEEE Robotics and Automation Letters)
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