Improving lead time setting and on-time delivery commitments under uncertain supply conditions
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2018
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| Online Access: | http://hdl.handle.net/1721.1/119330 |
| _version_ | 1811081715090718720 |
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| author | Balent, Zachariah (Zachariah Francis) |
| author2 | David Simchi-Levi and Stephen Graves. |
| author_facet | David Simchi-Levi and Stephen Graves. Balent, Zachariah (Zachariah Francis) |
| author_sort | Balent, Zachariah (Zachariah Francis) |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. |
| first_indexed | 2024-09-23T11:51:19Z |
| format | Thesis |
| id | mit-1721.1/119330 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:51:19Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1193302022-01-28T15:31:16Z Improving lead time setting and on-time delivery commitments under uncertain supply conditions Balent, Zachariah (Zachariah Francis) David Simchi-Levi and Stephen Graves. Leaders for Global Operations Program. Leaders for Global Operations Program at MIT Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Sloan School of Management Civil and Environmental Engineering. Sloan School of Management. Leaders for Global Operations Program. Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (page 55). As Dell seeks to continually improve customer experience, the company is identifying new and innovative ways to improve on-time delivery. Inventory shortages that occur prior to production account for approximately 35% of missed delivery dates. When these part shortages occur, demand planners must apply "extended" lead times to these parts to ensure that Dell's customers have the correct expectation for when their order will be delivered. This project focuses on part shortage problems and how to generate accurate lead times for customers commitments. Previous research on the topic on lead time setting has focused predominately on buffering and measuring uncertainty in supply chains, which detail the benefits of having appropriate levels of safety stock and flexibility. However, prior research does not adequately describe methods for adjusting product lead times under uncertain supply conditions. The project develops a deterministic model for identifying when parts in Dell's supply chain require lead time adjustments due to supply shortages and then for setting the new lead times. Additionally, this project includes a statistical analysis of previous extended lead time events. After a five-week testing period, the deterministic model was quite accurate in identifying what parts require extended lead times. This offers a 3% improvement in identifying when extended lead times are needed as it decreases human error in missed and late lead time extensions. Predominant sources of error resulted from backlog management issues, part deviations in production, and miscellaneous data errors. The statistical analysis yields two insights into part recovery in Dell's supply chain: (1) larger volume shortages take shorter time to recover than small volume shortages, and (2) approximately 80% of all part shortages recover within 10 days. This research offers valuable insight into the problems associated with lead times in Dell's supply chain and recommends ways to best mitigate these errors. As Dell develops more robust and comprehensive databases on its inventory, future research can identify methods to accurately and automatically update lead times in real-time. by Zachariah Balent. S.M. M.B.A. 2018-11-28T15:43:30Z 2018-11-28T15:43:30Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119330 1065522779 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 55 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Sloan School of Management. Leaders for Global Operations Program. Balent, Zachariah (Zachariah Francis) Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title | Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title_full | Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title_fullStr | Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title_full_unstemmed | Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title_short | Improving lead time setting and on-time delivery commitments under uncertain supply conditions |
| title_sort | improving lead time setting and on time delivery commitments under uncertain supply conditions |
| topic | Civil and Environmental Engineering. Sloan School of Management. Leaders for Global Operations Program. |
| url | http://hdl.handle.net/1721.1/119330 |
| work_keys_str_mv | AT balentzachariahzachariahfrancis improvingleadtimesettingandontimedeliverycommitmentsunderuncertainsupplyconditions |