Reliability Modeling in Spatially Distributed Logistics Systems

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 servi...

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Bibliographic Details
Published inIEEE transactions on reliability Vol. 55; no. 3; pp. 525 - 534
Main Authors Ni Wang, Jye-Chyi Lu, Kvam, P.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Automobile industry
Contingency
degradation
Demand
Density functional theory
Direct current
distribution centers
Joining processes
Kernel
Large-scale systems
Logistics
Mathematical analysis
National security
Position (location)
Reliability
Roads
service reliability
Stores
Supply chains
supply-chain systems
System reliability
Transportation
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Summary: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
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0018-9529
1558-1721
DOI:10.1109/TR.2006.879603