Capacity Management for Low Cost Storage
The growth that Amazon is projecting brings implications on the supply chain network, mainly, increasing capacity needs that can be addressed by adding Amazon Robotics (AR) Sortable Fulfillment Centers (FC), which require significant investment. High per unit storage costs, driven by the technology...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/139344 |
| _version_ | 1826217424587849728 |
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| author | Kahil, Omar |
| author2 | Simchi-Levi, David |
| author_facet | Simchi-Levi, David Kahil, Omar |
| author_sort | Kahil, Omar |
| collection | MIT |
| description | The growth that Amazon is projecting brings implications on the supply chain network, mainly, increasing capacity needs that can be addressed by adding Amazon Robotics (AR) Sortable Fulfillment Centers (FC), which require significant investment. High per unit storage costs, driven by the technology used at the AR-Sortable FCs, along with stock keeping units (SKUs) with high dwell time have created an opportunity to leverage low cost storage (LCS) nodes upstream of the FCs. These nodes reduce the number of required future AR-Sortable FCs allowing for significant savings.
Amazon conceived its first LCS node to address the challenge of high safety stock requirements and costly holding overheads. This solution proved that pooling excess inventory upstream improved turns at the FCs and reduced storage related fixed cost. The LCS node is now established for all excess inventory across imports and domestic retailing businesses which would provide opportunities for additional free cash flow savings.
LCS receives inventory from three flows: Asia Pacific consolidation node, US consolidation node that processes overseas shipment, and domestic. LCS has been experiencing a high backlog meaning trailers waiting at LCS yards to have their freight processed into the sites for a prolonged period of time. A high backlog can cause added out of stock risk, carrier fees and disruptions, and for units to dwell at the LCS below the required period to breakeven with the added processing cost at the sites. The backlog is driven by the fact that LCS nodes have instances where the amount of freight arriving is higher than what can be processed into the facilities.
To support LCS in its capacity management efforts, this thesis explores the redirection of trailers from LCS nodes towards the fulfillment network during instances of high backlog. In addition, the effort will include balancing the backlog at LCS by setting processing capacity (i.e. mechanical and labor capability to transfer freight from trailers into facilities) constraints on incoming arcs into LCS nodes. This will contribute to achieving cost savings by prioritizing inventory that will spend the bigger portion of its dwell time at the LCS nodes, and support the mitigation of out of stock risk by redirecting inventory with low excess coverage in the fulfillment network. |
| first_indexed | 2024-09-23T17:03:26Z |
| format | Thesis |
| id | mit-1721.1/139344 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T17:03:26Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1393442022-01-15T03:01:19Z Capacity Management for Low Cost Storage Kahil, Omar Simchi-Levi, David Graves, Stephen C. Sloan School of Management Massachusetts Institute of Technology. Department of Civil and Environmental Engineering The growth that Amazon is projecting brings implications on the supply chain network, mainly, increasing capacity needs that can be addressed by adding Amazon Robotics (AR) Sortable Fulfillment Centers (FC), which require significant investment. High per unit storage costs, driven by the technology used at the AR-Sortable FCs, along with stock keeping units (SKUs) with high dwell time have created an opportunity to leverage low cost storage (LCS) nodes upstream of the FCs. These nodes reduce the number of required future AR-Sortable FCs allowing for significant savings. Amazon conceived its first LCS node to address the challenge of high safety stock requirements and costly holding overheads. This solution proved that pooling excess inventory upstream improved turns at the FCs and reduced storage related fixed cost. The LCS node is now established for all excess inventory across imports and domestic retailing businesses which would provide opportunities for additional free cash flow savings. LCS receives inventory from three flows: Asia Pacific consolidation node, US consolidation node that processes overseas shipment, and domestic. LCS has been experiencing a high backlog meaning trailers waiting at LCS yards to have their freight processed into the sites for a prolonged period of time. A high backlog can cause added out of stock risk, carrier fees and disruptions, and for units to dwell at the LCS below the required period to breakeven with the added processing cost at the sites. The backlog is driven by the fact that LCS nodes have instances where the amount of freight arriving is higher than what can be processed into the facilities. To support LCS in its capacity management efforts, this thesis explores the redirection of trailers from LCS nodes towards the fulfillment network during instances of high backlog. In addition, the effort will include balancing the backlog at LCS by setting processing capacity (i.e. mechanical and labor capability to transfer freight from trailers into facilities) constraints on incoming arcs into LCS nodes. This will contribute to achieving cost savings by prioritizing inventory that will spend the bigger portion of its dwell time at the LCS nodes, and support the mitigation of out of stock risk by redirecting inventory with low excess coverage in the fulfillment network. S.M. M.B.A. 2022-01-14T15:05:22Z 2022-01-14T15:05:22Z 2021-06 2021-06-10T19:13:14.212Z Thesis https://hdl.handle.net/1721.1/139344 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Kahil, Omar Capacity Management for Low Cost Storage |
| title | Capacity Management for Low Cost Storage |
| title_full | Capacity Management for Low Cost Storage |
| title_fullStr | Capacity Management for Low Cost Storage |
| title_full_unstemmed | Capacity Management for Low Cost Storage |
| title_short | Capacity Management for Low Cost Storage |
| title_sort | capacity management for low cost storage |
| url | https://hdl.handle.net/1721.1/139344 |
| work_keys_str_mv | AT kahilomar capacitymanagementforlowcoststorage |