https://scholars.lib.ntu.edu.tw/handle/123456789/81985
DC Field | Value | Language |
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dc.contributor | 周雍強 | en |
dc.contributor | 臺灣大學:工業工程學研究所 | zh_TW |
dc.contributor.author | 李慧婷 | zh |
dc.contributor.author | Lee, Hui-Ting | en |
dc.creator | 李慧婷 | zh |
dc.creator | Lee, Hui-Ting | en |
dc.date | 2006 | en |
dc.date.accessioned | 2007-11-26T01:11:54Z | - |
dc.date.accessioned | 2018-06-29T00:34:05Z | - |
dc.date.available | 2007-11-26T01:11:54Z | - |
dc.date.available | 2018-06-29T00:34:05Z | - |
dc.date.issued | 2006 | - |
dc.identifier | zh-TW | en |
dc.identifier.uri | http://ntur.lib.ntu.edu.tw//handle/246246/51249 | - |
dc.description.abstract | 供應鏈在產品需求或是製造流程面臨著許多不確定性,節點工廠為了減緩變異所帶來的衝擊,大都會採用不同控制策略來因應,如調整產能或投料等,但若供應鏈的節點仍是各自為營,即使每個節點的利益都達到最佳化還是無法提高整體供應鏈的效益,因此節點工廠應該要透過協同合作以降低營運成本。不同於文獻中需求鏈的資訊分享,本研究主要目的為探討生產供應鏈中的節點,應用生產狀態資訊之分享方法,包括在製品存貨資訊和節點投料資訊等,藉以降低整體供應鏈的存貨成本。 本研究首先使用流體模型來建構單一節點的生產行為模式,即以微分方程式表示在製品在供應鏈之中流動速率與生產決策的關係,並且考慮流程的時間遞延以及重製事件對生產製造的影響,進而提出節點於滿載時發生重製事件的線性產能調整策略,其次,根據此動態模型,建立兩節點的供應鏈,分析兩節點對彼此狀態資訊的最佳應用方法,並提出評估資訊價值的代理指標,由此指標可以得知狀態資訊對節點和供應鏈的價值,最後,以非線性規劃法探討供應鏈使用狀態資訊的最佳協同合作之策略。本文所建構的流體模型可提供工廠控管動態事件的設計工具,而所描述的生產資訊分享之價值可作為製造供應鏈之廠商於協同合作時的基礎應用。 | zh_TW |
dc.description.abstract | Supply chains are full of dynamic events arising from demand uncertainty and process problems. To mitigate the impact of dynamic events, various control methods are usually used by production units, such as active flexible capacity or adjusting release rate. However, performance optimization of individual units does not guarantee the best outcome for the supply chains. Supply chain performance can be improved by collaboration. The focus of this research work is on how manufacturing chains can utilize the state information of production to enhance the performance of supply chains. This thesis is composed of three parts. First, continuous fluid models are used to model production behavior of individual nodes. Flow time delays and rework events are taken into account in the dynamic model. A linear control method for capacity adjustment is developed to stabilize the system when a node encounters rework events during a full-load situation. Second, a framework is presented for analyzing the use of the state information in supply chain collaboration and a surrogate measure is proposed for valuing the state information. Finally, a nonlinear programming model is described for optimizing production decisions in supply chain collaboration. | en |
dc.description.tableofcontents | 摘要 I Abstract II 目錄 III 圖目錄 V 表目錄 VI 第一章 緒論 1 1.1 研究背景與動機 2 1.2 問題描述 3 1.3 研究目的 6 1.4 研究方法與範疇 8 1.5 論文組織與結構 10 第二章 文獻探討 11 2.1 流體模型的簡介 11 2.2 時間延遲模式 17 2.3 動態事件的控制方法 19 2.4 資訊分享於供應鏈的應用方式 19 2.5 不同控制節點對存貨控制影響 21 第三章 單一節點的生產控制模型 24 3.1 供應鏈的生產流動情形 24 3.2 需求變異之穩態的生產控制 25 3.2.1 Linear retarded delay differential systems 27 3.2.2 需求動態模型之穩定性的驗證 29 3.2.3 需求動態模型的數值範例 30 3.3 產品重製之動態的生產控制 32 3.3.1 製程動態模型之穩定性的驗證 36 3.3.2 製程動態模型的數值範例 37 3.4 有效產能降低之生產控制 38 第四章 供應鏈協同合作之資訊價值分析 43 4.1 資訊分享下節點的生產情形 43 4.1.1 資訊分享的來源 45 4.1.2 資訊的應用方式 48 4.1.3 決策等候時間對資訊價值影響 51 4.2 生產資訊的價值曲線 53 4.2.1 存貨資訊之價值曲線 57 4.2.2 總成本的最小化 58 第五章 結論 63 5.1 研究貢獻 63 5.2 未來展望 64 參考文獻 65 | zh_TW |
dc.format.extent | 797486 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language | zh-TW | en |
dc.language.iso | en_US | - |
dc.subject | 動態系統 | en |
dc.subject | 流體模型 | en |
dc.subject | 資訊價值 | zh_TW |
dc.subject | system dynamics | en |
dc.subject | fluid models of supply chains | en |
dc.subject | information value | en |
dc.title | 供應鏈動態事件協同控制之資訊價值分析 | zh_TW |
dc.title | Analysis of state information in collaborative control of dynamic events in manufacturing chains | en |
dc.type | thesis | en |
dc.identifier.uri.fulltext | http://ntur.lib.ntu.edu.tw/bitstream/246246/51249/1/ntu-95-R93546027-1.pdf | - |
dc.relation.reference | [1] Armbruster, D., D. Marthaler, and C. Ringhofer, “Kinetic and Fluid Model hierarchies for Supply Chains,” Multiscale Modeling and Simulation, p. 43-61, 2004. [2] Arunsawatwong, Suchin, “Stability of retarded delay differential systems,” International Journal of Control, p. 347-364, 1996. [3] Balduzzi, Fabio and Giuseppe Menga, “A State Variable Model for the Fluid Approximation of Flexible Manufacturing Systems,” Proceedings of the 38th Conference on Decision & Control, p. 1172-1178, 1999. [4] Billings, Ron and John J. Hasenbein, “A Survey of Applications of Fluid Models to Semiconductor Fab Operations,” Proceedings of the International Conference on Modeling and Analysis of Semiconductor Manufacturing, 2000. [5] Bolot, Jean- Chrysostome and A. Udaya Shankar, “Analysis of a fluid approximation to flow control dynamics,” Proc. INFOCOM ’92, p. 11A.4.1-11A.4.10, 1992. [6] Connors, Dan, Gerry Feigin, and David Yao, “Scheduling Semiconductor Lines-Using a Fluid Network Model,” IEEE Transactions on robotics and automation, p. 88-92, 1994. [7] Fowler, John W., Gary L. Hogg, and Scott J. Mason, “Workload control in the semiconductor industry,” Production Planning & Control, p. 568-578, 2002. [8] Gavirneni, Srinagesh, Roman Kapuscinski, and Sridhar Tayur, “Value of Information in Capacitated Supply Chains,” Management Science, p. 16-24, 1999. [9] Gong, L. and H. Matsuo, “Control Policy for a Manufacturing System with Random Yield and Rework,” Journal of Optimization Theory and Applications, p. 149-174, 1997. [10] Lee, Ching Chyi and Wai Hung Julius Chu, “Who should control inventory in a supply chain?” European Journal of Operational Research, p. 158-172, 2005. [11] Lee, Hau L., Kut C. So, and Christopher S. Tang, “The Value of Information Sharing in a Two-Level Supply Chain,” Management Science, p. 626-643, 2000. [12] Lefeber, E., R. A. van den Berg, and J. E. Rooda, “Modeling, validation and control of manufacturing system,” Proceeding of the 2004 American Control Conference, p. 4583-4588, 2004 [13] Ma, D., “THE SEMICONDUCTOR MANUFACTURING STRATEGIES,” IEEE, p. 51-55, 2002. [14] Mourani, Iyad, Sophie Hennequin, and Xiaolan Xie, “Continuous Petri Nets with Delays for Performance Evaluation of Transfer lines,” Proceedings of the 2005 IEEE International Conference on Robotics and Automation, p. 3721-3726, 2005. [15] Mori, T. and H. Kokame, “Stability of ,” IEEE Transactions on Automatic Control, p. 460-462, 1989. [16] Riddalls, C. E. and S. Bennett, “The stability of supply chains,” International Journal of Production Research, p. 459-475, 2002. [17] Rose, Oliver, “WIP Evolution of a Semiconductor Factory after a Bottleneck Workcenter Breakdown,” Proceedings of the 1998 Winter Simulation Conference, p. 997-1003, 1998. [18] Takashi, Nagatani and Dirk Helbing, “Stability analysis and stabilization strategies for linear supply chains,” Physica A, p. 644-660, 2004. [19] Tu, Ying-Mei, Yu-Hsiu Chao, Sheng-Hung Chang, and Huan-Chung You, “Model to determine the backup capacity of a wafer foundry,” International Journal of Production Research, p. 339-359, 2005. [20] Van Ryzin, Garrett J., Sheldon. X. C. Lou, and Stanley. B. Gershwin, “Scheduling job shops with delays,” International Journal of Production Research, p. 1407-1422, 1991. [21] Wardi, Yorai and Benjamin Melamed, “Continuous Flow Models: Modeling, Simulation and Continuity Properties,” Proceedings of the 1998 IEEE International Conference on Robotics & Automation, p. 34-39, 1998. [22] Weiss, Gideon, “Scheduling and Control of Manufacturing Systems-a Fluid Approach,” Proceedings of the 37 Allerton Conference, p. 577-586, 1999. [23] Yu, Zhenxin, Hong Yan, and T.C. Edwin Cheng, “Benefits of information sharing with supply chain partnerships,” Industrial Management and Data Systems, p. 114-119, 2001. | en |
item.languageiso639-1 | en_US | - |
item.cerifentitytype | Publications | - |
item.fulltext | with fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
item.openairetype | thesis | - |
item.grantfulltext | open | - |
Appears in Collections: | 工業工程學研究所 |
File | Description | Size | Format | |
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ntu-95-R93546027-1.pdf | 23.53 kB | Adobe PDF | View/Open |
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