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Systems engineering and digital modeling are converging fast, reshaping the design and management of complex, large-scale systems across their lifecycle. Modern engineering increasingly depends on tools that represent system architecture and behavior as living digital models, but traditional document-based approaches are often too fragmented to keep pace. That mismatch has driven the rise of model-based systems engineering (MBSE), which uses frameworks like systems modeling language (SysML) to bring integrated, traceable modeling directly into the design and verification process. The payoff appears across domains like aerospace and automotive engineering, where model-driven traceability has begun replacing the siloed, document-heavy coordination previously defining system development. That shift extends further still, as MBSE's integration with digital twins and AI enables more informed decisions across the system lifecycle, even as questions emerge around tool interoperability and organizational adoption. Applied Model-Based Systems Engineering: Methods, Tools, and Industrial Applications advances research and practice in MBSE, bridging theoretical foundations with real-world industrial applications through state-of-the-art methodologies and implementation strategies. By examining modeling languages and standards, such as SysML, alongside MBSE's integration with digital twins and AI, this book connects academic research with industrial practice while supporting the shift from document-centric to model-centric engineering. Covering topics such as systems-of-systems engineering, machine learning, and lifecycle management, this book is an indispensable academic resource for graduate and doctoral students, systems engineers and architects, digital engineering professionals, smart manufacturing specialists, and more.
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