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dc.contributor.authorŞen, A.en_US
dc.contributor.authorBhatia, D.en_US
dc.contributor.authorDoǧan, K.en_US
dc.date.accessioned2016-02-08T09:58:03Z
dc.date.available2016-02-08T09:58:03Z
dc.date.issued2010en_US
dc.identifier.issn1359-0820
dc.identifier.urihttp://hdl.handle.net/11693/22286
dc.description.abstractApplied Materials Inc. is the global leader in nanomanufacturing technology solutions. It has a broad portfolio of innovative equipment, service, and software products and supports its customers worldwide with an extensive service and parts network with more than 100 locations. At the end of 2006, Applied Materials decided to evaluate and rationalize the design of its North American network. It set up a detailed optimization model (including 50,000 parts) to develop a network and distribution strategy. To our knowledge, this is the first large-scale multiechelon network-design model that incorporates safety stock inventory costs while considering the effects of lead time and risk pooling. The company used the model's recommendations to reduce costs while maintaining or improving its service to customers. The recommendations included simplifying the distribution network by consolidating depot locations for specific customers and skipping an echelon for others, thus leading to a projected inventory reduction of $10 million. The company is currently implementing these recommendations and has already eliminated five depots. Applied Materials estimates that during the first year of implementation, inventory reductions of $5.24 million and total savings of $1.1 million can be attributed to these network changes.en_US
dc.language.isoEnglishen_US
dc.source.titleInterfacesen_US
dc.relation.isversionofhttp://dx.doi.org/10.1287/inte.1100.0493en_US
dc.subjectFacilities-equipment planningen_US
dc.subjectIndustriesen_US
dc.subjectLocationen_US
dc.subjectSemiconductoren_US
dc.subjectServiceen_US
dc.titleApplied Materials uses operations research to design its service and parts networken_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage253en_US
dc.citation.epage266en_US
dc.citation.volumeNumber40en_US
dc.citation.issueNumber4en_US
dc.identifier.doi10.1287/inte.1100.0493en_US
dc.publisherInstitute for Operations Research and the Management Sciences (INFORMS)en_US


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