Capacity disruption is one of the most profound influence on risk for globalized enterprises. This grant provides funding for building comprehensive analytical framework for capturing the integrative dynamics of available capacity and demand in enterprise networks exposed to random capacity disruptions. A number of factors defining the network capacity position will be incorporated into the models including, but are not limited to, various modes of capacity degradation and recovery as well as impact of network topology. This mathematical framework will provide a basis for developing a computationally viable methodology to support design of a sustainable and agile enterprise infrastructure. A software prototype with a dynamic database driven analytical engine and a 3D visualization module will be created to facilitate decision making involving network design. The grant will also support the educational component of the research focused on fostering a professional cadre from a spectrum of academic and ethnic backgrounds who can serve as strategic decision makers to effectively mitigate the uncertainties inherent in globalized production and services. An interdisciplinary enterprise risk analysis course will be developed which will uniquely integrate traditional decision making under uncertainty with risk-based design and analysis of capacitated networks.
The expected benefits of this research include development of novel mathematical models that will provide foundations to model network risk for topologies of large complexity. If successful, these underlying models and the methodology will enhance resilience and competitiveness of domestic manufacturing enterprises advocating lean manufacturing philosophy. At the same time, the research and educational tasks will contribute to existing and future methodologies that are tailored to model risk inherent in national critical infrastructure systems.
