Data Analytics - Digital Twins to Real Time Control

Conference Video|Duration: 35:08
November 17, 2025
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  • Video details

    Brian W Anthony
    Principal Research Scientist, Department of Mechanical Engineering
    Associate Director, MIT.nano
    Director of Technical Operations, Center for Clinical and Translational Research

    Industry is undergoing a major transformation, shifting from automated to autonomous operations. The key to making this happen is the integration of digital technologies, including sensors, data, computing power, and information systems. At the heart of this shift are digital twins—virtual models that represent materials, processes, supply chains, and production lines. These digital replicas allow for simulation, monitoring, and improvement of operations in real-time using sensor data. When digital twins are combined with real-time control systems and machine learning, operations and factories become smarter and more adaptive. Real-time data flows from sensors to digital models and ML algorithms, enabling predictive maintenance, waste reduction, and optimizing production. A data-in-context connected ecosystem creates a highly efficient, data-driven environment in manufacturing and in mining. 

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Please login to view this video.
  • Video details

    Brian W Anthony
    Principal Research Scientist, Department of Mechanical Engineering
    Associate Director, MIT.nano
    Director of Technical Operations, Center for Clinical and Translational Research

    Industry is undergoing a major transformation, shifting from automated to autonomous operations. The key to making this happen is the integration of digital technologies, including sensors, data, computing power, and information systems. At the heart of this shift are digital twins—virtual models that represent materials, processes, supply chains, and production lines. These digital replicas allow for simulation, monitoring, and improvement of operations in real-time using sensor data. When digital twins are combined with real-time control systems and machine learning, operations and factories become smarter and more adaptive. Real-time data flows from sensors to digital models and ML algorithms, enabling predictive maintenance, waste reduction, and optimizing production. A data-in-context connected ecosystem creates a highly efficient, data-driven environment in manufacturing and in mining. 

Locked Interactive transcript