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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 吳政鴻(Cheng-Hung Wu) | |
dc.contributor.author | Chih-Chuan Chang | en |
dc.contributor.author | 張智荃 | zh_TW |
dc.date.accessioned | 2021-06-08T02:38:09Z | - |
dc.date.copyright | 2018-08-01 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-07-24 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19962 | - |
dc.description.abstract | 本研究考量在由非等效平行機台構成之串聯式生產系統中的派工問題。非等效平行機台代表機台間能進行相似的加工程序,但其加工速率並不相同,而在本研究中,該項差異來自於機台間健康狀態的不同。為最小化周期時間(Cycle time),本研究結合線性規劃與動態規劃以發展混合式淨空動態派工(HCSDD)。我們將系統中的各工作站拆解成單一工作站,並以線性規劃評估其最大平均產能,再根據工作站位置及最大平均產能決定在單站動態派工中使用的參數及決策方法。透過對整體系統的拆解,求解複雜度被有效降低,使HCSDD在提供良好的整體派工決策的同時,保持其計算可行性。 | zh_TW |
dc.description.abstract | This research studies scheduling problems in multi-stage production systems with unrelated parallel machines. Unrelated parallel machines are machines functioning similarly but with different processing rates, which are caused by machine deterioration. To minimize average cycle time, Hybrid Clearing System Dynamic Dispatching(HCSDD) was developed by combing linear programming decomposition with dynamic programming. The whole system is decomposed to single workstations and the capacity of each workstation is estimated by a linear programming model. For each workstation, the dispatching policy is obtained from single workstation dynamic dispatching model. The parameters used in the model and decision rules are determined based on the workstation location and capacity. The algorithm is computationally efficient and performs well in large systems. Comparing with other methods, cycle time is significantly improved in simulation analysis. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T02:38:09Z (GMT). No. of bitstreams: 1 ntu-107-R05546033-1.pdf: 9097362 bytes, checksum: e5bb0dcffba035f85f6b5a603931c116 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 誌謝 I
中文摘要 II Abstract III 目 錄 IV 圖目錄 VI 表目錄 VIII 第一章 緒論 1 1.1 研究背景 1 1.2 研究問題 2 1.3 研究目的 4 1.4 研究方法 4 1.5 研究流程 5 第二章 文獻回顧 6 2.1 非等效平行機台派工方法 6 2.2 序列式生產系統控管方法 7 2.3 複雜度解決方法 8 2.4 機台健康度辨識 9 第三章 單站與多站動態派工 10 3.1 研究問題假設 10 3.2 多在製品多機台單工作站動態派工模型(DD) 10 3.3 多在製品多機台多工作站動態派工模型 14 3.4 求解複雜度 17 第四章 混合式淨空動態派工與數值範例 19 4.1 上游工作站負載與下游工作站之在製品到達率 19 4.2 考量機台健康狀態之多序列工作站產能評估 21 4.3 混合式淨空動態派工(HCSDD) 23 4.3.1 符號定義 24 4.3.2 第一工作站之派工策略與決策 24 4.3.3 瓶頸工作站之派工策略與決策 25 4.3.4 其他工作站之派工策略與決策 25 4.3.5 混合式淨空動態派工策略與決策統整 26 4.4 數值範例 26 第五章 模型驗證 33 5.1 求解工具介紹 33 5.1.1 求解工具介紹-動態規劃 33 5.1.2 求解工具介紹-線性規劃 35 5.2 模擬方法架構 35 5.2.1 模擬程式驗證 35 5.2.2 比較的其他派工方法 36 5.3 實驗設計-三健康狀態、兩在製品、每站兩機台之生產系統 38 5.4 三工作站實驗設計 39 5.4.1 三工作站實驗結果與分析-指數分配製造時間 43 5.4.2 三工作站實驗結果與分析-均勻分配製造時間 51 5.4.3 三工作站實驗結果與分析-常數製造時間 59 5.5 四工作站實驗設計 67 5.5.1 四工作站實驗結果與分析-指數分配製造時間 73 5.5.2 四工作站實驗結果與分析-均勻分配製造時間 82 5.5.3 四工作站實驗結果與分析-常數製造時間 91 5.6 六工作站實驗 100 第六章 結論與未來研究方向 104 6.1 結論 104 6.2 未來研究方向 104 參考文獻 105 | |
dc.language.iso | zh-TW | |
dc.title | 考量機台損耗之連續工作站動態派工 | zh_TW |
dc.title | Dynamic Production Scheduling of Deteriorating Machines in Serial Production Lines | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳吉政(Jei-Zheng Wu),陳文智(Wen-Chih Chen),余承叡(Fish Yu),Jefferson Huang(Jefferson Huang) | |
dc.subject.keyword | 機台健康資訊,動態派工,多工作站序列式生產系統,啟發式演算法,動態規劃, | zh_TW |
dc.subject.keyword | Machine Health Information,Dynamic Dispatching,Multiple Tandem Systems,Heuristic Control,Dynamic Programming, | en |
dc.relation.page | 107 | |
dc.identifier.doi | 10.6342/NTU201801740 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2018-07-25 | |
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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