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Open Access Thesis
Industrial Engineering & Operations Research
Master of Science in Industrial Engineering and Operations Research (M.S.I.E.O.R.)
Year Degree Awarded
Month Degree Awarded
There are many aspects to consider when managing an entire supply chain from procurement to fulfillment. Complex assemblies require hundreds of components, sourced from all corners of the globe, to come together in a synchronized fashion. Given the magnitude of the supply chain, high quality standards, and significantly increased outsourcing, there is a strong need to monitor supplier risk and quickly identify and mitigate potential problems. Moreover, the continuous pressure to reduce resources and pressure to cut costs, further increases the need for the development of procedures and tools that can quickly and efficiently address these potential supply chain risks. This thesis focuses on two unique problems brought to our attention by supply chain managers in the field. The first is the analysis of the robustness of advanced ordering strategies (AOS). AOS have been proposed in previous research to coordinate the delivery of components for complex assemblies with long and highly variable lead times. They have been shown to be highly successful to synchronize the supply chain under on-going conditions. It is not clear; however, their effect as the underlying performance of suppliers evolves over time. The second topic covers the methodological foundation and development of a tool to accurately classify suppliers based off risk, and provides a method to calculate final assembly risk, in addition to guiding the deployment of scarce supplier development teams and resources.
Greene, Christopher A., "Strategies for Reducing Supplier Risk: Inputs into the Supply Chain" (2016). Masters Theses. 322.