Resilient Capacity Planning
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We envision the next generation supply chain to be an efficient, resilient, and cybersecure system for the movement of goods, data, and money. An emerging design of the next generation supply chain is reconfigurable supply chain. A reconfigurable supply chain is a supply chain that permits material transshipment and adding, subtracting and relocating manufacturing/service modules. Relocatable manufacturing/service module is a trending concept in advanced manufacturing and service engineering. In this Ph.D. thesis, we investigate a class of problems called resilient capacity planning in reconfigurable supply chains for build-to-order manufacturing systems and service-upon-request service systems. This emerging class of problems applies to a wide spectrum of novel application domains, such as personalized medicine, 3D-printing manufacturing, relocatable storage network, epidemic/pandemic control and etc. The objective of this thesis is to study capacity planning problems in reconfigurable supply chains with coordinating controls on consumable and reusable resources when customer demand is stochastic and suppliers are unreliable. We investigate several key fundamental research projects for both centralized and decentralized reconfigurable supply chains to provide resilient capacity planning decision supports. We introduce the approaches to model and quantify supplier disruption risks in both centralized and decentralized networks and reveal the potential of resilient capacity planning in enhancing system performances.