Forecast-driven tactical planning models for manufacturing systems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2012
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| Online Access: | http://hdl.handle.net/1721.1/68700 |
| _version_ | 1826199174461259776 |
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| author | Chhaochhria, Pallav |
| author2 | Stephen C. Graves. |
| author_facet | Stephen C. Graves. Chhaochhria, Pallav |
| author_sort | Chhaochhria, Pallav |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011. |
| first_indexed | 2024-09-23T11:15:32Z |
| format | Thesis |
| id | mit-1721.1/68700 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:15:32Z |
| publishDate | 2012 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/687002019-04-12T15:20:52Z Forecast-driven tactical planning models for manufacturing systems Chhaochhria, Pallav Stephen C. Graves. Massachusetts Institute of Technology. Operations Research Center. Massachusetts Institute of Technology. Operations Research Center. Operations Research Center. Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student submitted PDF version of thesis. Includes bibliographical references (p. 243-247). Our work is motivated by real-world planning challenges faced by a manufacturer of industrial products. In the first part of the thesis, we study a multi-product serial-flow production line that operates in a low-volume, long lead-time environment. The objective is to minimize variable operating costs, in the face of forecast uncertainty, raw material arrival uncertainty and in-process failure. We develop a dynamic-programming-based tactical model to capture the key uncertainties and trade-offs, and to determine the minimum-cost operating tactics. The tactics include smoothing production to reduce production-related costs, and segmenting the serial-flow line with decoupling buffers to protect against variance propagation. For each segment, we specify a work release policy and a production control policy to manage the work-in-process inventory within the segment and to maintain the inventory targets in the downstream buffer. We also optimize the raw material ordering policy with fixed ordering times, long lead-times and staggered deliveries. In the second part of the thesis, we examine a multi-product assembly system that operates in a high-volume, short lead- time environment. The operating tactics used here include determining a fixed-length cyclic schedule to control production, in addition to smoothing production and segmenting the system with decoupling buffers. We develop another dynamic-programming-based tactical model that determines optimal policies for production planning and scheduling, inventory, and raw material ordering; these policies minimize the operating cost for the system in the face of forecast and raw material arrival uncertainty. We tested these models on both hypothetical and actual factory scenarios. The results confirmed our intuition and also helped develop new managerial insights on the application of these operating tactics. Moreover, the tactical model's factory performance predictions were found to be within 10% of simulation results for the testbed systems, thus validating the models. by Pallav Chhaochhria. Ph.D. 2012-01-30T15:22:16Z 2012-01-30T15:22:16Z 2011 2011 Thesis http://hdl.handle.net/1721.1/68700 773934118 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 247 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Operations Research Center. Chhaochhria, Pallav Forecast-driven tactical planning models for manufacturing systems |
| title | Forecast-driven tactical planning models for manufacturing systems |
| title_full | Forecast-driven tactical planning models for manufacturing systems |
| title_fullStr | Forecast-driven tactical planning models for manufacturing systems |
| title_full_unstemmed | Forecast-driven tactical planning models for manufacturing systems |
| title_short | Forecast-driven tactical planning models for manufacturing systems |
| title_sort | forecast driven tactical planning models for manufacturing systems |
| topic | Operations Research Center. |
| url | http://hdl.handle.net/1721.1/68700 |
| work_keys_str_mv | AT chhaochhriapallav forecastdriventacticalplanningmodelsformanufacturingsystems |