Data analytics and simulation methodologies for adaptive supply chain risk management in bio-pharmaceutical manufacturing

Abstract

To assess the system risk performance and study the random behaviors, we develop simulation analytics and output analysis methodologies, and analyze the sensitivity of the system performance to each source of uncertainty. For complex end-to-end bio-pharmaceutical supply chains, metamodels are constructed as knowledge representation of the system input/output relationship and further employed to predict the system risk behaviors.