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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳政鴻(Cheng-Hung Wu) | |
| dc.contributor.author | Chiao-Ju Sun | en |
| dc.contributor.author | 孫巧儒 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:03:47Z | - |
| dc.date.copyright | 2018-08-07 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-01 | |
| dc.identifier.citation | [1] Baras, J., Ma, D.-J., & Makowski, A. (1985). K competing queues with geometric service requirements and linear costs: The μc-rule is always optimal. Systems & control letters, 6(3), 173-180.
[2] Belouadah, H., & Potts, C. N. (1994). Scheduling identical parallel machines to minimize total weighted completion time. Discrete Applied Mathematics, 48(3), 201-218. [3] Bernier, V., & Frein, Y. (2004). Local scheduling problems submitted to global FIFO processing constraints. International Journal of Production Research, 42(8), 1483-1503. [4] Biskup, D., Herrmann, J., & Gupta, J. N. (2008). Scheduling identical parallel machines to minimize total tardiness. International Journal of Production Economics, 115(1), 134-142. [5] Grigoriu, L., & Briskorn, D. (2017). Scheduling jobs and maintenance activities subject to job-dependent machine deteriorations. Journal of Scheduling, 20(2), 183-197. [6] Gyulai, D., Kádár, B., Kovács, A., & Monostori, L. (2014). Capacity management for assembly systems with dedicated and reconfigurable resources. CIRP Annals-Manufacturing Technology, 63(1), 457-460. [7] Kim, B., & Kim, S. (2001). Extended model for a hybrid production planning approach. International Journal of Production Economics, 73(2), 165-173. [8] Kurz, J. (2016). Capacity planning for a maintenance service provider with advanced information. European Journal of Operational Research, 251(2), 466-477. [9] Lin, C.-H., & Liao, C.-J. (2008). Makespan minimization for multiple uniform machines. Computers & Industrial Engineering, 54(4), 983-992. [10] Lu, S., Liu, X., Pei, J., Thai, M. T., & Pardalos, P. M. (2018). A hybrid ABC-TS algorithm for the unrelated parallel-batching machines scheduling problem with deteriorating jobs and maintenance activity. Applied Soft Computing, 66, 168-182. [11] Min, L., & Cheng, W. (1999). A genetic algorithm for minimizing the makespan in the case of scheduling identical parallel machines. Artificial Intelligence in Engineering, 13(4), 399-403. [12] Nobil, A. H., Sedigh, A. H. A., & Cárdenas-Barrón, L. E. (2016). A multi-machine multi-product EPQ problem for an imperfect manufacturing system considering utilization and allocation decisions. Expert Systems with Applications, 56, 310-319. [13] Puterman, M. (1994). Markov decision processes. 1994. Jhon Wiley & Sons, New Jersey. [14] Sakhaii, M., Tavakkoli-Moghaddam, R., Bagheri, M., & Vatani, B. (2016). A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines. Applied Mathematical Modelling, 40(1), 169-191. [15] Sun, K., & Li, H. (2010). Scheduling problems with multiple maintenance activities and non-preemptive jobs on two identical parallel machines. International Journal of Production Economics, 124(1), 151-158. [16] Wang, J.-J., Wang, J.-B., & Liu, F. (2011). Parallel machines scheduling with a deteriorating maintenance activity. Journal of the Operational Research Society, 62(10), 1898-1902. [17] Wein, L. M. (1988). Scheduling semiconductor wafer fabrication. IEEE Transactions on semiconductor manufacturing, 1(3), 115-130. [18] Xia, T., Jin, X., Xi, L., & Ni, J. (2015). Production-driven opportunistic maintenance for batch production based on MAM–APB scheduling. European Journal of Operational Research, 240(3), 781-790. [19] Yang, S.-J. (2011). Parallel machines scheduling with simultaneous considerations of position-dependent deterioration effects and maintenance activities. Journal of the Chinese Institute of Industrial Engineers, 28(4), 270-280. [20] Zandieh, M., Sajadi, S. M., & Behnoud, R. (2017). Integrated production scheduling and maintenance planning in a hybrid flow shop system: a multi-objective approach. International Journal of System Assurance Engineering and Management, 8(2), 1630-1642. [21] 姚怡均. (2017). 考量機台損耗之非等效動態生產系統派工與保養. 臺灣大學工業工程學研究所學位論文, 1-106. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22124 | - |
| dc.description.abstract | 本研究利用線性規劃進行產能配置，降低動態派工與預防保養策略時的複雜度(Decomposition)，應用於大型的多產品多機台的生產系統中。其中機台的健康狀態與產品的派工以及機台預防保養策略相關，在此生產環境下，若無考量妥善的派工與保養決策將造成產品週期增加，進而系統生產成本上升，因此凸顯適當的派工與保養策略之重要性。
然而利用動態規劃(Dynamic programming)建立多產品多機台的動態派工與預防保養策略模型(Dynamic Dispatching with Preventive Maintenance Model, DDPM)時，考慮所有健康狀態下的機台數量導致當系統機台數目增加，維度越大以致於無法在合理時間內得到適當的動態派工與保養之決策，故本研究提出LPD (Linear Programming Decomposition)方法將考量的健康狀態化簡為單一機台，目標為最小化等候時間，模擬在同質機台系統下以兩產品三機台與兩產品四機台生產系統為例，以及異質機台系統下以兩產品兩異質機台系統進行模擬分析，並與DDPM以及其他派工方法比較。結果顯示LPD方法的表現接近於DDPM，且優於其他方法能夠有效提升生產效率且降低產品等候成本，顯示LPD能夠在合理時間內獲得妥善的動態派工與預防保養策略。 | zh_TW |
| dc.description.abstract | This research decomposes the dynamic dispatching and preventive maintenance strategy for large-scale production system by capacity allocation with linear programming model. The health condition of machines is dispatching and maintenance dependent. Therefore, an improper dispatching and maintenance rules will lead to an increase in the cycle time of product, and thus stress the importance of appropriate dynamic dispatching and preventive maintenance policy.
However, when the dynamic programming is used to develop the Dynamic Dispatching with Preventive Maintenance (DDPM) model, the consideration of the number of machines in all health conditions will result in the fact that an appropriate policy cannot be obtained within a reasonable time as the scale of production system becomes larger. Hence, we propose Linear Programming Decomposition (LPD) as a method to divide multiple machines system into several single machine problems so as to consider only one machine’s health condition. The simulation results show that the performance of LPD is close to DDPM and superior to other dispatching rules under both homogeneous machine system and heterogeneous machine system, which verifies that an approximately optimal dispatching with preventive maintenance can be obtained by LPD within a reasonable time. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:03:47Z (GMT). No. of bitstreams: 1 ntu-107-R05546021-1.pdf: 4863045 bytes, checksum: bd29d26f26f54c05596b080eecfb5221 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 第1章 緒論 1
1.1 研究背景與動機 1 1.2 研究目的 3 1.3 研究方法 4 1.4 研究流程 5 第2章 文獻回顧 6 2.1 多機台系統產能配置 6 2.2 平行機台之生產系統管理 7 2.2.1 同質機台系統 7 2.2.2 異質機台系統 8 第3章 同質機台系統研究方法與數值驗證分析 10 3.1 問題描述與假設 10 3.1.1 問題描述 10 3.1.2 研究問題假設 11 3.2 多產品多同質機台動態派工與保養模型 13 3.2.1 參數與變數符號定義 13 3.2.2 多產品多同質機台動態派工與保養模型 13 3.2.3 求解複雜度解釋 16 3.3 同質機台Linear Programming Decomposition模型 18 3.3.1 參數與變數符號定義 18 3.3.2 同質機台線性規劃模型 19 3.3.3 結合單機台DDPM模型 20 3.3.4 求解複雜度解釋 21 3.4 數值範例 22 3.5 模擬結果與數值分析 26 3.5.1 求解程式演算邏輯 26 3.5.2 實驗設計 28 3.5.3 實驗結果與分析—兩產品三同質機台 33 3.5.4 實驗結果與分析—兩產品四同質機台 61 第4章 異質機台系統研究方法與數值驗證分析 88 4.1 問題描述與假設 88 4.1.1 問題描述 88 4.1.2 研究問題假設 89 4.2 多產品多異質機台動態派工與保養模型 90 4.2.1 參數與變數符號定義 90 4.2.2 多產品多異質機台動態派工與保養模型 91 4.2.3 求解複雜度解釋 93 4.3 異質機台Linear Programming Decomposition模型 94 4.3.1 參數與變數符號定義 94 4.3.2 異質機台線性規劃模型 95 4.3.3 結合單機台DDPM模型 95 4.3.4 求解複雜度解釋 96 4.4 數值範例 97 4.5 模擬結果與數值分析 102 4.5.1 求解程式演算邏輯 102 4.5.2 實驗設計 104 4.5.3 實驗結果與分析—兩產品兩異質機台 108 第5章 結論與未來研究方向 142 5.1 結論 142 5.2 未來研究方向 143 參考文獻 144 | |
| dc.language.iso | zh-TW | |
| dc.subject | 產能配置 | zh_TW |
| dc.subject | 機台健康狀態 | zh_TW |
| dc.subject | 降低複雜度 | zh_TW |
| dc.subject | 動態派工 | zh_TW |
| dc.subject | 預防保養 | zh_TW |
| dc.subject | Machin Health Condition | en |
| dc.subject | Capacity Allocation | en |
| dc.subject | Preventive Maintenance | en |
| dc.subject | Dynamic Dispatching | en |
| dc.subject | Decomposition of Complexity | en |
| dc.title | 具擴充性之多機台動態派工與預防保養方法 | zh_TW |
| dc.title | A Scalable Linear Programming Decomposition Method for Dynamic Dispatching and Preventive Maintenance of Deteriorating Machines | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 余承叡,陳文智,Jefferson Huang | |
| dc.subject.keyword | 機台健康狀態,降低複雜度,動態派工,預防保養,產能配置, | zh_TW |
| dc.subject.keyword | Machin Health Condition,Decomposition of Complexity,Dynamic Dispatching,Preventive Maintenance,Capacity Allocation, | en |
| dc.relation.page | 145 | |
| dc.identifier.doi | 10.6342/NTU201802359 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2018-08-02 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
| 顯示於系所單位： | 工業工程學研究所 | |
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