Raw Material Minimum Order Quantity Optimization
The sponsoring company, wants to review their raw material ordering policy and production plan for one of their product segments. This product faces a high degree of volatility in demand and the company currently orders one month of demand worth of products from the suppliers. The suppliers offer in...
| Main Authors: | , |
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| Published: |
2019
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| Online Access: | https://hdl.handle.net/1721.1/121302 |
| _version_ | 1826214765035257856 |
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| author | Shenoy, Shilpa Zhao, Ai |
| author_facet | Shenoy, Shilpa Zhao, Ai |
| author_sort | Shenoy, Shilpa |
| collection | MIT |
| description | The sponsoring company, wants to review their raw material ordering policy and production plan for one of their product segments. This product faces a high degree of volatility in demand and the company currently orders one month of demand worth of products from the suppliers. The suppliers offer incremental discounts for larger quantities of raw materials ordered, and the company wants to leverage this discount better. To that end, our research focuses on how to optimize the raw material ordering policy in a way that reduces the total costs, while storing sufficient raw materials to ensure continuity of the production plan. The model we developed provides the optimal minimum order quantity (MOQ) to use while re-ordering raw materials. It also incorporates a switching rule that automatically switches the MOQ value to a higher or lower value depending on the demand forecast and determines the order quantity (OQ) of the raw material. |
| first_indexed | 2024-09-23T16:10:48Z |
| id | mit-1721.1/121302 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T16:10:48Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | mit-1721.1/1213022019-06-15T03:04:09Z Raw Material Minimum Order Quantity Optimization Shenoy, Shilpa Zhao, Ai Optimization Sourcing Demand Planning Inventory The sponsoring company, wants to review their raw material ordering policy and production plan for one of their product segments. This product faces a high degree of volatility in demand and the company currently orders one month of demand worth of products from the suppliers. The suppliers offer incremental discounts for larger quantities of raw materials ordered, and the company wants to leverage this discount better. To that end, our research focuses on how to optimize the raw material ordering policy in a way that reduces the total costs, while storing sufficient raw materials to ensure continuity of the production plan. The model we developed provides the optimal minimum order quantity (MOQ) to use while re-ordering raw materials. It also incorporates a switching rule that automatically switches the MOQ value to a higher or lower value depending on the demand forecast and determines the order quantity (OQ) of the raw material. 2019-06-14T21:15:13Z 2019-06-14T21:15:13Z 2019 https://hdl.handle.net/1721.1/121302 application/pdf |
| spellingShingle | Optimization Sourcing Demand Planning Inventory Shenoy, Shilpa Zhao, Ai Raw Material Minimum Order Quantity Optimization |
| title | Raw Material Minimum Order Quantity Optimization |
| title_full | Raw Material Minimum Order Quantity Optimization |
| title_fullStr | Raw Material Minimum Order Quantity Optimization |
| title_full_unstemmed | Raw Material Minimum Order Quantity Optimization |
| title_short | Raw Material Minimum Order Quantity Optimization |
| title_sort | raw material minimum order quantity optimization |
| topic | Optimization Sourcing Demand Planning Inventory |
| url | https://hdl.handle.net/1721.1/121302 |
| work_keys_str_mv | AT shenoyshilpa rawmaterialminimumorderquantityoptimization AT zhaoai rawmaterialminimumorderquantityoptimization |