This article proposes methods for modeling service reliability in a supply chain. The logistics system in a supply chain typically consists of thousands of retail stores along with multiple distribution centers (DC). Products are transported between DC & stores through multiple routes. The service reliability depends on DC location layouts, distances from DC to stores, time requirements for product replenishing at stores, DC's capability for supporting store demands, and the connectivity of transportation routes. Contingent events such as labor disputes, bad weather, road conditions, traffic situations, and even terrorist threats can have great impacts on a system's reliability. Given the large number of store locations & multiple combinations of routing schemes, this article applies an approximation technique for developing first-cut reliability analysis models. The approximation relies on multi-level spatial models to characterize patterns of store locations & demands. These models support several types of reliability evaluation of the logistics system under different probability scenarios & contingency situations. Examples with data taken from a large-scale logistics system of an automobile company illustrate the importance of studying supply-chain system reliability.

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Post-print Article

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Copyright © 2006 IEEE.

DOI: 10.1109/TR.2006.879603

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Full Citation:

Wang, Ni, Jye-Chyi Lu, and Paul K. Kvam. "Reliability Modeling in Spatially Distributed Logistics Systems." IEEE Transactions on Reliability 55, no. 3 (2006): 525-534. doi:10.1109/tr.2006.879603.