以多屬性法則探討TFT-LCD廠Array製程區的Stacker Crane之Cassette選取問題

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張惠筑(Hui-Chu Chang) 查詢紙本館藏

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以多屬性法則探討TFT-LCD廠Array製程區的Stacker Crane之Cassette選取問題

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摘要(中)

由於資訊科技的快速發展，薄膜電晶體液晶顯示器（TFT-LCD）為生活帶來更高的便利性和使用性，逐漸影響人們的數位化生活。為了提升台灣TFT-LCD產業在國際間的競爭力，除了導入自動化生產系統外，企業傾向興建更大尺寸的面板廠，尺寸越大能使單片基板可切割出的片數越多，增加產量之外也使單位生產成本降低，但隨著尺寸逐漸增大，進而衍生出更大尺寸面板的搬運需求，因此面對大尺寸玻璃基板的搬運需求，如何更有效率地搬運，使生產效率提升，是本研究探討之重點。
現今自動化物料搬運系統（AMHS）為TFT-LCD廠自動化生產的核心，而AMHS系統主要是由無人搬運車（AGV）、有軌式無人搬運車（RGV）和林坤濱（2008）所提出的內嵌式自動倉儲（In-Line Stocker）的有軌巷道堆高機（Stacker Crane）所組成，本研究將會在AMHS的系統環境下針對大尺寸玻璃基板搬運流動規劃進行深入的探討，模擬物料搬運控制策略與生產流程之間的關係，期望能證明車輛搬運控制策略對TFT-LCD生產效率有正面的影響。
本研究將研究探討重點放在第八代TFT-LCD廠Array製程中的製程區內搬運活動，探討Stacker Crane之Cassette選取問題對於整體系統的影響，提出多屬性派送控制法則，根據先前研究之單屬性法則分析結果來作為權重設定的參考依據，並針對先前模擬環境進行修正。最後透過仿真模擬軟體Arena 15.0建構新的環境，並利用SPSS 22.0分析觀察多屬性法則與單屬性法則之產出量、平均流程時間、平均延遲時間、平均提早時間和平均差異時間之比較，以此判斷多屬性派送法則是否有顯著提升整個系統派送控制之效率。

摘要(英)

Due to the rapid development of information technology, thin-film transistor liquid crystal display (TFT-LCD) brings higher convenience and usability to life, and gradually affects people′s digital life. In order to promote the international competitiveness of Taiwan′s TFT-LCD industry, in addition to the introduction of automated production systems, companies have increased the construction of large-scale panel factories. The size enables the number of single-piece substrates that can be cut out to increase output. The unit production cost is reduced, but the size must be gradually expanded, and the slenderness leads to the demand for handling large-sized panels. Therefore, in the face of the demand for handling large-size glass substrates, how to overcome the efficiency of handling and improve production efficiency is the focus of this study.
Nowadays automated material handling system (AMHS) is the core of TFT-LCD factory automation production, and the AMHS system is mainly built by the unmanned vehicle (AGV), railless unmanned vehicle (RGV) and Lin Kunbin (2008). In-Line Stocker (In-Line Stocker) is composed of a rail roadway stacker (Stacker Crane). This study will conduct an in-depth discussion of the large-scale glass substrate handling flow planning under the AMHS system environment, and simulate material handling control. The relationship between the strategy and the production process is expected to prove that the vehicle handling control strategy has a positive impact on the TFT-LCD production efficiency.
This study inherits the paper of Wang (2019) and research Intra-Bay handling and Inter-Bay handling in the Array process of the eighth generation TFT-LCD panel factory. Discuss a decision-making problems here : the selection problem of Stacker Crane’s Cassette, and propose a multi-attribute dispatch control rule. According to previous research At last, the simulation environment software Arena 15.0 is used to reconstruct the new environment, and SPSS 22.0 is used to analyze and compare the replacement amount of the multi-attribute rule and the single-attribute rule, the average process time, the average delay time, the average early time and the average difference time. Determine whether the multi-attribute dispatching law has significantly improved the efficiency of dispatch control for the entire system.

關鍵字(中)

★ TFT-LCD
★ AMHS
★ Intra-Bay搬運
★ Stacker Crane
★ 多屬性派送控制法則

關鍵字(英)

★ TFT-LCD
★ AMHS
★ Intra-Bay handling
★ Stacker Crane
★ Multiple Attribute dispatching control rule

論文目次

摘要 i
Abstract ii
目錄 iii
圖目錄 ix
表目錄 xii
第一章、緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究環境 4
1.4 論文架構 6
第二章、文獻探討 9
2.1 TFT-LCD之結構組成與製程 10
2.1.1 Array製程 11
2.1.2 Cell製程（面板） 12
2.1.3 Module製程（模組） 13
2.2 TFT-LCD廠自動化物料搬運系統 14
2.3 無人搬運車派送之相關研究 17
2.3.1 無人搬運車（Automatic Guided Vehicle，AGV）的派送問題 17
2.3.2 有軌式無人搬運車（Rail Guide Vehicle，RGV）的派送問題 22
2.3.3 具有儲存功能與搬運功能的S/R Machine相關的派送問題 24
2.4 TFT-LCD廠與半導體晶圓廠AMHS派送控制相關研究 26
2.5 多屬性自動化物料搬運系統派送控制相關研究 30
第三章、研究方法 33
3.1 研究環境說明 33
3.2 作業流程符號及變數定義 35
3.3 TFT-LCD系統中Array製程之工作站與無人搬運車作業流程 35
3.3.1 Cassette進入系統之左側工作站流程 35
3.3.2 Cassette進入系統之右側工作站流程 36
3.3.3 左側RGV之派送作業流程 37
3.3.3.1 左側無人搬運車 LRGV J的派送流程 40
3.3.3.1.1 LRGV J 執行左側RGV程序一 41
3.3.3.1.2 RRGV J 執行右側RGV程序二 42
3.3.3.1.3 RRGV J 執行右側RGV程序三 42
3.3.4 右側RGV之派送作業流程 43
3.3.4.1 右側無人搬運車 RRGV J 的派送流程 44
3.3.4.1.1 RRGV J 執行右側RGV程序一 45
3.3.4.1.2 RRGV J 執行右側RGV程序二 46
3.3.4.1.3 RRGV J 執行右側RGV程序三 47
3.3.5 In-Line Stocker之一般加工機台作業流程 48
3.3.6 In-Line Stocker之Stacker Crane作業流程 49
3.3.6.1 Inline Stocker I之Stacker Crane S（I）派送流程一 52
3.3.6.1.1 Stacker Crane S（I）執行程序一 54
3.3.6.1.2 Stacker Crane S（I）執行程序二 54
3.3.6.1.3 Stacker Crane S（I）執行程序三 55
3.3.6.1.4 Stacker Crane S（I）執行程序四 56
3.3.6.2 Inline Stocker I之Stacker Crane S（I）派送流程二 57
3.3.7 完成品集中工作站之作業流程 58
3.4 研究方法整理 59
3.4.1 Stacker Crane之Cassette多屬性選取法則 60
3.4.2 RGV之Cassette多屬性選取法則 63
3.4.3 Stacker Crane之Cassette單屬性選取法則 64
3.4.3.1 隨機選取法則 64
3.4.3.2 到期日最早的Cassette優先選取法則 64
3.4.3.3 剩餘加工時間最少的Cassette優先選取法則 65
3.4.3.4 剩餘加工時間最多的Cassette優先選取法則 65
3.4.3.5 寬鬆時間最少的Cassette優先選取法則 66
3.4.3.6 （寬鬆時間/剩餘加工時間）最少的Cassette優先選取法則 66
3.4.3.7 最早進入系統的Cassette優先選取法則 67
3.4.4 RGV之Cassette單屬性選取法則 67
第四章、實驗結果與分析 68
4.1 模擬實驗設計 68
4.1.1 模擬實驗環境設定 68
4.1.2 模擬系統設定 69
4.1.3 實驗因子組合 70
4.1.4 績效評估指標 73
4.2 統計分析 74
4.2.1 以產出量（Throughput）為績效評估值 74
4.2.1.1 RGV之Cassette選取問題搭配隨機選取法則（RgvRND） 74
4.2.1.1.1 搭配RgvRND之Stacker Crane之Cassette選取法則 (以Throughput為績效值) 75
4.2.1.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 76
4.2.1.2.1 搭配RgvSRPT之Stacker Crane之Cassette選取法則(以Throughput為績效值) 77
4.2.1.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 78
4.2.1.3.1 搭配RgvMultiple之Stacker Crane之Cassette選取法則（以Throughput為績效值） 79
4.2.2 以平均流程時間（Average Flow Time，AFT）為績效評估值 80
4.2.2.1 RGV之Cassette選取問題搭配隨機選取法則（RgvRND） 80
4.2.2.1.1 搭配RgvRND之Stacker Crane之Cassette選取法則（以AFT為績效值） 81
4.2.2.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 81
4.2.2.2.1 搭配RgvSRPT之Stacker Crane之Cassette 選取法則（以AFT為績效值） 81
4.2.2.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 82
4.2.2.3.1 搭配RgvMultiple之Stacker Crane之Cassette選取法則（以AFT為績效值） 83
4.2.3 以平均延遲時間（Average Tardiness Time，ATT）為績效評估值 83
4.2.3.1 RGV之Cassette選取問題搭配隨機選取法則（RgvRND） 83
4.2.3.1.1 搭配RgvRND之Stacker Crane之Cassette選取法則（以ATT為績效值） 84
4.2.3.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 84
4.2.3.2.1 搭配RgvSRPT之Stacker Crane之Cassette選取法則（以ATT為績效值） 84
4.2.3.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 85
4.2.3.3.1 搭配RgvMultiple之Stacker Crane之Cassette選取法則（以ATT為績效值） 86
4.2.4 以平均提早時間（Average Earliness Time，AET）為績效評估值 86
4.2.4.1 RGV之Cassette選取法則搭配隨機選取法則（RgvRND） 86
4.2.4.1.1 搭配RgvRND之Stacker Crane之Cassette選取法則（以AET為績效值） 87
4.2.4.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 88
4.2.4.2.1 搭配RgvSRPT之Stacker Crane之Cassette選取法則（以AET為績效值） 88
4.2.4.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 89
4.2.4.3.1 搭配RgvMultiple之Stacker Crane之Cassette選取法則（以AET為績效值） 90
4.2.5 以平均差異時間（Average Lateness Time，ALT）為績效評估值 91
4.2.5.1 RGV之Cassette選取法則搭配隨機選取法則（RgvRND） 91
4.2.5.1.1 搭配RgvRND之Stacker Crane之Cassette選取法則（以ALT為績效值） 92
4.2.5.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 92
4.2.5.2.1 搭配RgvSRPT之Stacker Crane之Cassette選取法則（以ALT為績效值） 92
4.2.5.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 93
4.2.5.3.1 搭配RgvMultiple之Stacker Crane之Cassette選取法則（以ALT為績效值） 94
4.3 實驗結論 94
4.3.1 RGV之Cassette選取問題搭配隨機選取法則之情況（RgvRND） 94
4.3.2 RGV之Cassette選取問題搭配剩餘加工時間最少選取法則（RgvSRPT） 95
4.3.3 RGV之Cassette選取問題搭配多屬性選取法則（RgvMultiple） 95
第五章、結論與後續建議 96
5.1 研究結論 96
5.2 未來研究建議 97
參考文獻 98
中文文獻 98
英文文獻 99
相關網站 105

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相關網站
1. 經濟日報，2020，“今年全球LCD電視面板出貨量將降一成”，Retrieved April 16, 2020，from https://money.udn.com/money/story/5612/4461314
2. Insight，2018，“ TFT LCD Manufacturing Process ”，Retrieved April 16, 2020，from https://insightsolutionsglobal.com/tft-lcd-manufacturing-process/
3. 友達光電，2020，“顯示器解決方案- TFT－LCD製程”，Retrieved April 16, 2020，from https://www.auo.com/zh-TW/TFT-LCD_Introduction/index/TFT_LCD_Process
4. 群創光電，2020，“TFT－LCD製程介紹”，Retrieved April 16, 2020，from http://www.innolux.com/Pages/TW/Technology/Production_Process_TW.html
5. 盟立自動化，2018，“OHT-節省廠內空間的好幫手”，Retrieved April 19, 2020，from https://reurl.cc/kdlGxn
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指導教授

何應欽(Ying-Chin Ho)

審核日期

2020-8-17

推文