Show simple item record

dc.contributor.advisorOmar Sherif Elwakil.en_US
dc.contributor.authorRey, Maria (Maria de los Santos)en_US
dc.contributor.authorXu, Xiaofanen_US
dc.contributor.otherMassachusetts Institute of Technology. Supply Chain Management Program.en_US
dc.date.accessioned2017-12-20T18:15:05Z
dc.date.available2017-12-20T18:15:05Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/112859
dc.descriptionThesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 81-82).en_US
dc.description.abstractMedical devices companies struggle to balance between inventory and service performance, as the products are non-interchangeable and inventory investment is expensive. To find the right level of inventory, we first used unsupervised clustering method to find demand pattern uncertainty for each product. Then, we developed a simulation-based approach to determine the required inventory to achieve a required service level guarantee. We further explored policy changes in the demand fulfillment process to identify how the company can effectively improve performance without increasing inventory level. After comparing different results, we concluded that reduction of replenishment lead time is the most effective measure. The methodology can be applied to a wide range of products and sectors.en_US
dc.description.statementofresponsibilityby Maria Rey and Xiaofan Xu.en_US
dc.format.extent82 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSupply Chain Management Program.en_US
dc.titleIdentifying inventory excess and service risk in medical devices : a simulation approachen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Supply Chain Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Supply Chain Management Program
dc.identifier.oclc1014182104en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record