A new research effort led by the University of Oklahoma and funded by the Defense Advanced Research Projects Agency, or DARPA, will develop a visual analytics system to help Department of Defense decision makers understand the different types of risks associated with the global supply chain networks, the various actions that can be taken to protect the interests of national security, and ways to withstand and recover from any supply chain disruptions as quickly as possible.
Recent events like the COVID-19 pandemic have made apparent how supply chain networks are an essential yet vulnerable necessity for how resources, goods and services move around the globe.
“Everything that has happened in recent years has emphasized the importance of studying supply chain networks and making those more resilient to a broad range of disruptions, as well as more adaptable to new technologies,” said Andrés D. González, Ph.D., assistant professor in the School of Industrial and Systems Engineering, Gallogly College of Engineering at OU and the principal investigator of the study.
“For example, COVID-19 caused significant cascading failures, where in diverse circumstances, a delay or a disruption in one of the functions from a single supplier propagated globally throughout the entire supply chain network and had effects in multiple regions and industries,” he added. “Many of these failures were caused by mechanisms that had never been observed before in history, and the depth and complexity of their effects were not adequately foreseen, thus inspiring the type of work we’re doing.”
González, who is also an affiliate faculty in the data science and analytics program in the Gallogly College of Engineering at OU, is leading an interdisciplinary team composed of experts spanning economics, industrial and systems engineering, and computer science, as well as aerospace and mechanical engineering, among others. González is also working with OU’s Data Institute for Societal Challenges and Oklahoma Aerospace and Defense Innovation Institute, whose executive director, retired Lt. Gen. Gene Kirkland, observed that this effort is “yet another example of emerging partnerships between academic colleges and university-wide centers to advance OU’s research in support of national security challenges.”
Over the course of the four-year $3.7 million project, the research team plans to create an extensive computational and visual analytic environment using state-of-the-art modeling and predictive techniques, along with visualizations such as spatiotemporal graphs, charts and maps, to identify vulnerabilities and patterns that can help to better understand and evaluate the interactions and interdependencies between different components in supply-demand systems.
“First, we need to gain adequate supply chain visibility and understand the complex regional and global supply-demand networks, their structures and dynamical properties, using novel data-driven system identification techniques based on multiple data sources such as contracts, partnerships, and flow of commodities and information,” González said. “Once a good understanding of supply chain network structure and dynamics has been achieved, it is critical to develop advanced models for supplier survivability prediction, risk quantification and propagation, and resilience-based mitigation, preparedness and recovery actions.”
By integrating those components within a visual analytics environment, researchers and practitioners will have a framework that can show not only visual representations of existing supply-demand networks but also provide significant insights and actionable information for stakeholders and decision makers.
“A strong visual analytics environment can provide valuable information into what-if scenarios associated with a diverse range of disruptions, as well as pre- and post-event policies,” González said. “For example, what if we had another pandemic? What would be the effect of increasing tributary duties in a particular industry? Or, what if there is some political issue that affects some trade deal? The idea is to learn how people make decisions and how that can also give information to mathematical models to improve their predictive power.
“It is also very important to understand the effect that other countries have on the performance of supply chain networks in the U.S., so having an understanding of this will enable us to make better decisions to reduce vulnerabilities, enhance our resilience, and improve cooperation as well,” he added.