Digital Twin Model of Semiconductor Supply Chain for Managing Disruption and Resilience Through Data Driven Experiments

The semiconductor supply chain (SSC) was examined in this study for the effects of interruptions like the Covid-19 epidemic, and the resilience factors related to it were determined. With the use of Anylogistix's digital twin (DT), a simulation model was created using real-world disruption scenarios from the US in order to learn about the operational needs and supply chain characteristics. The SSC is still far from the recovery stage and is vulnerable to many existing challenges. Companies and firms that faced huge losses during the pandemic are on the search for innovative strategies to make supply chains more efficient. Collection of precise existing data cum information available from various resources using a thorough literature review was carried out. Through Anylogistix software, feeding of the data for experimenting using different Scenarios to test and analyze the factors which helped in evaluating the resiliency of the supply chain was done. A set of experiments was carried out using predictive tools and simulations available in the software. The research objectives of this study, found that the DT helped in aspects of prediction, metrics for evaluation, strategies for recovery, diagnostics, projections, and clear visibility of the SSC for providing optimum solutions for making the supply chain more resilient. Some methods to overcome challenges were also suggested in the paper. The findings of this study could help businesses, organizations, researchers, and medium-sized enterprises strengthen their resilience frameworks and better position themselves for unforeseen crisis circumstances that could arise shortly