Digital Twins Drive Supply Chain Resilience: A Case Study of Suzhou Boyang Chemical Plant and Baikuang Debao Base

Abstract

Under the new normal of global "high uncertainty, high complexity, and high externalities", traditional supply chains expose significant vulnerabilities in extreme shocks. This study, with the theme of "digital twin-driven supply chain resilience enhancement", selects Suzhou Boyang Chemical Plant (discrete-multi-variety-high control) and Baikuang Debao Base (continuous-heavy asset-green transformation) as dual cases. Based on operational data from 2021 to 2023, a before-and-after A/B experimental design is adopted to quantitatively evaluate the four-dimensional indicators of resistance, recovery, adaptability, and evolution. The results show that digital twins have reduced the leakage probability of Boyang by 38%, compressed the recovery time by 87%, reduced unplanned tank stoppages of Baikuang by 55%, decreased annual carbon emissions per ton of aluminum by 10%, and precipitated 127 pieces of reusable resilience knowledge. The study refines a common resilience enhancement loop of "second-level perception-minute-level simulation-hour-level decision-making", providing empirical evidence and policy insights for governments and enterprises to develop a cross-industry resilience governance paradigm.