Journal
IEEE TRANSACTIONS ON RELIABILITY
Volume 66, Issue 4, Pages 1144-1156Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TR.2017.2737822
Keywords
Bayesian methods; reliability; resilience; supply chain management; supply chain risk propagation; system analysis and design
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Funding
- Faculty Research Initiation at the University of Michigan-Dearborn
- Seed Grant at the University of Michigan-Dearborn
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As the complexity of supply chain structures and the frequency of their disruptions rise, businesses are increasingly recognizing the value of supply chain reliability and resilience (SCRR). A number of efforts have been devoted to define SCRR or to develop risk mitigation strategies for their improvement. However, a key question remaining to be answered is how SCRR should be quantified. Existing methods are insufficient in addressing this question on two important fronts: First, they do not adequately represent the interdependencies between different supply chain nodes; second, they do not allow for the modeling of actionable decisions and thus cannot be used to guide improvement strategies. This paper aims to fill this gap by proposing a unified framework for evaluating SCRR that internalizes design inputs and is flexible to varying degrees of data availability. The proposed framework captures risks involved in the supply, the demand, the firm itself, and the external environment. It also contributes to the literature by relating SCRR to the supply chain's risk-mitigating capabilities prior to or postdisruptions. A novel method using the supply chain's inherent buyer-supplier relationships is designed to model node interdependencies. Two example applications are discussed to demonstrate how this framework can be utilized to assist in reliable and resilient supply chain design.
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