Loading...
Dr. N. Mohananthini is an Associate Professor in the Department of Electrical and Electronics Engineering at Muthayammal Engineering College, Rasipuram, India. Her contribution focuses on cloud-based digital twins for industrial monitoring and control.
Cloud-based Digital Twin technology offers a sophisticated method for overseeing, evaluating, modelling, and regulating industrial systems via perpetually refreshed virtual models of tangible assets and processes. Through the incorporation of Industrial Internet of Things (IIoT) devices, cloud computing, Artificial Intelligence (AI), Machine Learning (ML), extensive data analytics, and sophisticated communication technologies, cloud-based Digital Twins empower organisations to gather and analyse substantial amounts of real-time industrial data. These technologies provide remote surveillance, anticipatory upkeep, anomaly identification, process enhancement, energy oversight, and smart regulation within decentralised industrial settings. This chapter elucidates the essential principles, framework, facilitating technologies, and applications of cloud-based Digital Twins for industrial oversight and regulation. It addresses data acquisition based on IIoT, cloud architecture, data storage solutions, real-time analytics, AI-enhanced forecasting, simulation, feedback regulation, and interaction with industrial automation frameworks. The study investigates applications in intelligent manufacturing, anticipatory maintenance, robotics, energy systems, production enhancement, and supply chain oversight. The section additionally examines edge-cloud frameworks, synchronisation of Digital Twins, cybersecurity measures, interoperability, scalability, and autonomous governance.