Digital Twins on the Resilience of Supply Chain Under COVID-19 Pandemic

The coronavirus disease 2019 (COVID-19) has put enormous pressure on the global supply chain. This work aims to solve supply chain interruption caused by public health emergencies in real life through the resilient supply chain based on digital twins (DTs). The research example used here is the disruption of the supply chain of N95 medical masks under the COVID-19 epidemic. First, the resilient supply chain's emergency decision cost and profit model is established under the manufacturer-supplier shared mode. The supply chain of M company of N95 medical masks in Hubei under the COVID-19 pandemic is selected to discuss the cost of emergency decision-making in the resilient supply chain. Moreover, a product supply chain model is built, including H suppliers, J manufacturers, K distributors, and L retailers. Supply failures result in lower supplier capacity ratios. Accordingly, the supply chain will adopt emergency strategies to reduce operating costs and increase profits. Activating alternative suppliers and distributors can mitigate the loss caused by partial supply chain disruption in emergencies. The elasticity of supply chains based on DTs discussed here is of significant value in helping the automation of critical links of the supply chain. The resilient supply chain combined with the capacity recovery strategy can significantly improve the traditional supply chain's response to supply disruption events.