Enhancing U.S. Critical Mineral Supply Chain Security Through Predictive Analytics, Risk Control Engineering, And Circular Economy Logistics

Abstract

Due to escalating geopolitical tensions, growing resource demands, and supply risks, the security of the United States' input of its critical mineral resources has become a national priority. The proposed paper offers a holistic framework that improves the security of a supply chain through predictive analytics as opposed to risk-control engineering and circular economy logistics. The prediction algorithms are used to forecast disturbances by using data to simulate the trade flow, the geopolitical risks as well as the operational weaknesses. Riskcontrol engineering approaches are next put to use to address the identified risks via the establishment of robust supply routeways, as well as redundancy, hence optimal stockpiling measures. Lastly, circular economy logistics are presented to facilitate material loops and decrease reliance on original assets, and boost sustainability by means of promoting recycling, reuse, and reverse logistics. An empirical study and scenario modeling have shown that the integrated approach enhances the readiness of disruptions, minimizes risk exposure, and facilitates the long-term ambitions of securing resources and the environment. The results provide useful recommendations to policymakers, industry leaders, and supply chain managers interested in receiving contributions that can help them secure the flows of critical minerals as well as contribute to sustainability.