2026-09-19T03:48:59Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1128592026-06-06T01:04:14Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Omar Sherif Elwakil.
Rey, Maria (Maria de los Santos)
Xu, Xiaofan
Massachusetts Institute of Technology. Supply Chain Management Program.
Massachusetts Institute of Technology. Supply Chain Management Program
2017-12-20T18:15:05Z
2017-12-20T18:15:05Z
2017
2017
http://hdl.handle.net/1721.1/112859
1014182104
Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 81-82).
Medical 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.
by Maria Rey and Xiaofan Xu.
M.Eng. in Supply Chain Management
82 pages
eng
Massachusetts Institute of Technology
MIT 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.
http://dspace.mit.edu/handle/1721.1/7582
Supply Chain Management Program.
Identifying inventory excess and service risk in medical devices : a simulation approach
Thesis
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<Abstract>Medical 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.</Abstract>
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