ADVANCED SUPPLY CHAIN ANALYTICS

Innovating supply chain solutions for a secure global society

The interconnected nature of globalization presents an increasing number of challenges, uncertainties, and vulnerabilities for supply chains. The transportation, financial, cyber, and human networks that make up supply chains can cross traditional boundaries, which requires them to be responsive and resilient to different physical, regulatory, and social environments.

Scientists and engineers at Argonne National Laboratory holistically examine supply chains using a variety of methodologies, approaches, tools and techniques, providing meaningful insights and actionable information for key decision makers around the globe. Our analysts apply modeling, simulation, data analytics, and visualization techniques to achieve supply chain objectives such as balancing risk and efficiency, responding to disruptive trends and technologies, optimizing for cost-effective resilience, assessing the consequences of disruptions to complex interdependent supply chains, and addressing the challenges of the digital economy. Coupled with subject matter expertise in the physical and biological sciences, nuclear engineering, policy, infrastructure, and social behavior, Argonne uses these tools to strengthen the resilience and efficiency of critical supply chains and strengthen our country’s national security.

For example, Argonne experts work with emergency responders and economic stakeholders seeking to assure supply chains deliver critical resources to customers by strengthening the resilience of their networks against disruptions. We also assist national security experts seeking to deny the supply of proliferation sensitive goods and technology to adversaries by analyzing trade that could support illicit procurement for weapons of mass destruction programs.

Our core capabilities in supply chain analytics include:

  • Agent-based modeling
  • Logistics analysis
  • Policy impact analysis
  • System optimization
  • Data analytics
  • Machine learning
  • Scalable models
  • Threat analysis
  • Dependency modeling
  • Network analysis
  • Systems modeling
  • Visualization methods

Contact Information

Argonne National Laboratory
9700 S. Cass Avenue
Argonne, IL 60439

Email: gssinfo@anl.gov