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Challenges and Opportunities of Digital Twins

The Julia Programming Language via YouTube

Overview

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Explore the challenges and opportunities in developing digital twins across automotive, aerospace, energy, industrial, high-tech, and healthcare sectors in this keynote presentation from JuliaCon Global 2025. Discover how digital twins model complex physical systems through the integration of physical assets, virtual models, and bidirectional information flow via IoT platforms. Learn about two primary approaches to building digital twins: data-based analytics using AI and machine learning, which requires extensive training data but has accuracy limitations, and physics-based simulation, which offers high accuracy but demands significant computation time. Understand how reduced-order models can accelerate simulation runtimes and examine the innovative concept of hybrid digital twins on the Industrial Metaverse that combines AI/ML analytics with physics-based simulation to achieve superior accuracy, reduced training data requirements, and enhanced operational efficiency. See practical demonstrations of how platforms like JuliaHub can facilitate hybrid digital twin development, with specific applications to semiconductor manufacturing fabs aimed at improving yields, increasing throughput, reducing costs, and maximizing operating equipment efficiency.

Syllabus

Keynote: Challenges and Opportunities of Digital Twins | JuliaCon Global 2025 | Prith Banerjee

Taught by

The Julia Programming Language

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