Introduction to Supply Chain Digital Twins and AI
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Beschreibung
This textbook offers an introduction to supply chain digital twins and AI in a concise but comprehensive form covering management, modeling and technology perspectives. It is designed as a supplementary satellite book for textbook “Global Supply Chain and Operations Management” advancing the topics of the digital supply chain. The book aims at delineating major design principles and technologies and explaining methodologies for supply chain analytics in digital twins. Throughout the book, numerous practical examples and short case-studies are provided to illustrate theoretical concepts. It also reviews and explains novel frameworks and concepts related to digital ecosystems and agentic AI.
The book provides a structured presentation and explanation of major concepts, methods, and digital technologies for building or improving supply chain digital twins in a simple and predictable format, making it accessible to students and professionals with backgrounds in management or engineering. Application scenarios are considered, such as using digital twins for stress testing of supply chain resilience as well as building digital twins in automotive industry.
Graduate and PhD students, as well as supply chain professionals, will benefit from the book’s structured and didactically oriented presentation of the concepts, principles, and methods behind digital twins. By equipping readers with practical knowledge of contemporary theories and technologies, the book supports both academic learning and the development of digital supply chains in practice.
This textbook offers an introduction to supply chain digital twins and AI in a concise but comprehensive form covering management, modeling and technology perspectives. It is designed as a supplementary satellite book for textbook “Global Supply Chain and Operations Management” advancing the topics of the digital supply chain. The book aims at delineating major design principles and technologies and explaining methodologies for supply chain analytics in digital twins. Throughout the book, numerous practical examples and short case-studies are provided to illustrate theoretical concepts. It also reviews and explains novel frameworks and concepts related to digital ecosystems and agentic AI.
The book provides a structured presentation and explanation of major concepts, methods, and digital technologies for building or improving supply chain digital twins in a simple and predictable format, making it accessible to students and professionals with backgrounds in management or engineering. Application scenarios are considered, such as using digital twins for stress testing of supply chain resilience as well as building digital twins in automotive industry.
Graduate and PhD students, as well as supply chain professionals, will benefit from the book’s structured and didactically oriented presentation of the concepts, principles, and methods behind digital twins. By equipping readers with practical knowledge of contemporary theories and technologies, the book supports both academic learning and the development of digital supply chains in practice.
Offers a structured overview of key concepts and methods to build or improve supply chain digital twins and AI Delineates major features, explaining methodologies and principles for designing and applying them in practice Reviews and explains novel frameworks like human-AI collaboration, ecosystems, and agentic AI
Autor*in
Dmitry Ivanov
Themen in »Introduction to Supply Chain Digital Twins and AI«
Supply Chain Digital Twin Digital Supply Chain Supply Chain Viability Human-AI Collaboration Supply Chain Disruption Management Model-based Decision-making Support Digital Twin Data-driven Decision-making Support Digital Twin Analytics Predictive Analytics Prescriptive Analytics Supply Chain Resilience Supply Chain Stress Testing Digital Twin Design Supply Chain Ecosystem