Digital Twins for Enhanced Supply Chain Visibility and Resilience

Abstract

The globalized and dynamic nature of present-day supply chains requires strong visibility and flexibility. This dissertation investigates the transformative potential of computerized twins - advanced replicas of physical supply chain systems. By leveraging real-time information and simulation capabilities, computerized twins can engage organizations to pick up uncommon visibility into their operations. This dissertation explores how advanced twins can improve supply chain visibility by following stock development, checking generation forms, and recognizing potential bottlenecks. Besides, it looks at how proactive bits of knowledge inferred from advanced twins can reinforce supply chain strength. Through situation recreations and data-driven decision-making, organizations can relieve disturbances, optimize asset allotment, and guarantee proceeded delivery of products and services. This paper contributes to the developing body of information on digital twins by analysing their effect on supply chain visibility and resilience within the complex and everevolving scene of the 21st century.