臺灣博碩士論文加值系統

面板為目前最重要之電子產品之一，市場需求是日益漸增，提昇產能及滿足顧客需求以增加市場佔有率為國內各大面板廠之主要目標。本研究針對TFT-LCD之Cell製程各階段機台數量該如何配置，以達到產能及顧客滿意度最大化加以探討，兩者相對應之指標分別為訂單內所有工件總完工時間(Total completion time)及總延遲件數(Number of Tardy Jobs)為最小。研究將以國內某TFT-LCD製造廠為個案，過程中先搜集相關資料包括產品種類，各產品在各製程單機情況下之單位加工時間，每月訂單之各種類產品之批量數及批量中之產品數量，以及製程各階段之機台數。研究中探討三種機台配置方案：(1) 流線型生產系統(Flow shop, FS)；(2) 目前工廠之配置，為一個彈性流線型生產系統 (Flexible flow shop, FFS)；(3)依據現場經驗而提出之另一種FFS生產系統。三種方案比較先採用工件(單種產品批量)到達時間為靜態(static)情況做探討，靜態排程假設各工件之資訊已知且可在同一時間排程；之後再探討更符合實務之動態(Dynamic)情況，動態排程假設下個工件到達時間、產品種類及其批量大小、交期均未知，這些資訊直到工件到達時刻才知曉。研究結果在靜態情況，以混合式基因演算法做上述三種方案之探討，研究結論為流線型系統為最佳。動態情況運用不同派工法則(Dispatching rule) FIFO、SPT、LPT、EDD、FST等，同時納入設置時間(Setup times)，並考慮交期。考量Cmax及總延遲件數雙目標下，並配置不同權重，當同時考慮雙目標之下結論是以方案一流線型生產系統且使用LPT法則為最佳。

TFT-LCD is currently one of the most essential electronic products. Its demand is growing every month. To contend in such a competitive environment, TFT-LCD corporations must focus on productivity and customers’ satisfaction. This study aims to improve the TFT-LCD Cell manufacturing process for a corporation in Taiwan. The Cell process is a flexible flow shop. In this paper, we consider three feasible machine allocation alternatives, and recommend the best alternative based on two evaluation standards: minimizing the total completion time (makespan) and the number of tardy jobs. The analysis involves two cases: static scheduling and dynamic (online) scheduling with unknown release dates. The case study consists of four phases: (1) Data collection, including product types and their demands on each month of recent years, processing and setup time estimations, and the current machine configuration in each Cell stage; (2) Comparing three feasible alternatives, which are flow shop, one-job on one-machine, and current arrangement; (3) Generating test instances using the data collected in phase one for comparison purposes; (4) Evaluating performance based on static scheduling solved with GA, and dynamic scheduling with five dispatching rules: FIFO, SPT, LPT, EDD, and FST.
Our experimental results conclude the following: The flow shop arrangement is preferred in a static scheduling environment, whereas the one-job on one-machine excels the other alternatives in a dynamic scheduling environment with the two standards of equal weight.

中文摘要 ii
英文摘要 iii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
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 研究範圍與限制 2
1.4 研究架構與流程 3
第二章 文獻探討 6
2.1 TFT-LCD簡介與構造 6
2.1.1 TFT-LCD製程 7
2.1.2 TFT-LCD Cell製程及個案公司機台配置 8
2.2 排程問題與分類 13
2.2.1 彈性流線型工廠 15
2.2.2 個案公司工件處理時間資源使用量及其限制 16
2.3 排程問題求解方法 16
2.4 專案排程問題的求解方法 19
2.5 基因演算法 21
2.5.1 基因演算法優點 21
2.5.2 基因演算法的方法及運算流程 22
2.5.3 混合式基因演算法 25
2.5.4 基因演算法運用在排程上相關文獻 26
2.6 派工法則 27
2.6.1 派工法則相關文獻 29
2.7 績效衡量指標 30
第三章 問題描述 33
3.1 問題描述 33
3.2 問題假設 35
3.3 例題說明 36
第四章 研究方法 39
4.1 基因演算法模型 39
4.2 區域搜尋法 42
4.3 停止條件 45
4.4 動態排程模式建立 45
4.5 動態數據收集 48
4.6 Arena模擬模型 50
4.7 動態排程例題說明 51
4.8 動態排程模型設計 56
第五章 實驗結果與分析 60
5.1 方案說明 60
5.2 實驗方法 63
5.3 求解分析 63
5.3.1 小型測試題-50筆訂單 63
5.3.2 中型測試題-100筆訂單 66
5.3.3 大型測試題-200筆訂單 69
5.4 動態排程實驗結果 72
5.4.1 方案1實驗結果 72
5.4.2 方案2實驗結果 76
5.4.3 方案3實驗結果 78
5.4.4 最佳方案分析結果 80
第六章 結論與後續研究建議 83
6.1 研究結論 83
6.1.1 靜態排程結論 83
6.1.2 動態排程結論 83
6.2 後續研究建議 84
參考文獻 85
附錄 89
附錄1 各產品批量分配 89

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