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Digital Twin Engineering: AI, Enterprise Systems and the Industrial Metaverse expands the digital twin architecture into the domain of intelligent cyber-physical ecosystems.
Building on the infrastructure described in Volume I, this book explores how artificial intelligence, predictive analytics, and enterprise software systems transform digital twins into autonomous optimization platforms.
Readers will discover how machine learning models analyze telemetry streams to detect anomalies, estimate remaining useful life, and control complex industrial processes. The book also examines how digital twins integrate with enterprise systems such as ERP, MES, and PLM, enabling organizations to synchronize operations across entire value chains.
Through real-world industry examples-from smart factories and wind farms to aerospace engineering-the book demonstrates how digital twins evolve from isolated asset models into large-scale digital ecosystems.
The final chapters explore the future of cyber-physical systems, including cognitive twins, immersive interfaces, and the emerging industrial metaverse.
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