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作者(中文):朱曉晴
論文名稱(中文):考慮需求不確定之隨機動態產能規劃─以TFT-LCD產業為例
論文名稱(外文):Stochastic Dynamic Capacity Planning under Demand Uncertainty for TFT-LCD Industry
指導教授(中文):林則孟
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學號:9634506
出版年(民國):98
畢業學年度:97
語文別:中文
論文頁數:120
中文關鍵詞:薄膜液晶顯示器產能規劃需求不確定性隨機動態規劃情境產生
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薄膜液晶顯示器(Thin Film Transistor-Liquid Crystal Display, TFT-LCD)產業面臨的市場需求具有劇烈的波動之下,考量在規劃期間內,各產品機種於各期有不同的需求分配,且前後期的需求是彼此相關的。因此在需求不確定的環境下,傳統上僅以需求預測的期望值來做規劃是無法滿足實際的需求,必須考量各期需求間的相依性,動態的決定各期所需的產能與產能的配置。本研究利用時間序列的ARIMA(p, d, q)模式建立需求預測模式,產生需求分配,並考慮前後期需求的相依性,建立隨機動態規劃數學模式,期望找出一穩健的(Robust)產能擴充決策,並依此產能擴充決策的結果,規劃各期最佳的生產產品組合,達到最佳的產能配置結果。
本研究將以一實際的案例,產生需求分配之樣本內需求情境,透過定義隨機性的衡量指標,驗證考慮需求不確定之二階隨機規劃與隨機動態規劃模式可得到較確定型模式佳的結果,而隨機動態規劃模式多考慮了需求不確定性,因此在相同的需求情境之下,可得到較二階隨機規劃多的利潤。接著,利用蒙地卡羅模擬法(Monte Carlo Simulation),隨機抽樣得到樣外的需求情境,透過比較所有需求情境下規劃求得的利潤平均數、標準差、風險測量值(Value at Risk; VaR),來驗證此隨機動態規劃模式的有效性與穩健性,透過觀察90%的VaR,可得到在90%的信心水準之下,隨機動態規劃模式在最差的情況之下所求得的利潤會比二階隨機規劃與確定型模式佳,表示在可容忍的信心水準之下,隨機動態規劃所求得的最小利潤會比二階隨機規劃與確定型模式所求得的最小利潤高,可降低更多的風險與增加更多的利潤。

關鍵字:薄膜液晶顯示器、產能規劃、需求不確定性、隨機動態規劃、情境產生
目錄
摘要 I
誌謝 II
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 3
1.3 研究範圍與限制 4
1.4 研究架構 4
第二章 文獻回顧 6
2.1 需求不確定性之相關文獻 6
2.1.1 需求不確定性的表達種類 6
2.1.2 需求情境的產生方式 9
2.2 產能規劃問題之相關文獻 15
2.2.1 產能規劃層級 15
2.2.2 單廠區與多廠區產能規劃問題與比較 19
2.2.3 需求確定性與需求不確定性之產能規劃問題與比較 26
2.3 產能規劃之方法 27
2.3.1 需求確定性之產能規劃方法 27
2.3.2 需求不確定性之產能規劃方法 29
2.4 需求不確定性之產能規劃研究模式 32
第三章 TFT-LCD產業產能規劃問題之特性分析 34
3.1 供給產能特性分析 34
3.1.1 生產鏈廠區結構特性 34
3.1.2 生產鏈廠區與產品機種關係特性 36
3.1.3 生產鏈廠區供給產能特性 37
3.2 需求預測特性分析 39
3.2.1 產品特性 39
3.2.2 產品需求特性 40
3.3 供給產能與需求預測之平衡狀況 42
3.4 TFT-LCD產業之產能規劃問題與分類 43
第四章 需求不確定之單階層多廠區隨機動態產能規劃 47
4.1 問題定義 47
4.2研究模式 50
4.2.1產生需求分配 51
4.2.2 產生需求情境值與需求移轉機率 54
4.2.3 需求不確定之單階層多廠區動態產能規劃模式 56
4.2.3.1 隨機動態規劃方法說明 56
4.2.3.2 建立隨機動態規劃模式 57
4.2.3.3 範例說明 59
4.3 案例驗證 69
4.3.1 情境說明 69
4.3.2 產生需求分配與需求情境 69
4.3.3 建立隨機動態規劃模式 73
4.3.4 隨機動態規劃結果 74
4.3.5 規劃結果分析 76
4.3.6 敏感度分析 79
第五章 模擬實驗與分析 90
5.1模擬實驗架構與結果 90
5.1.1 實驗目的 90
5.1.2 樣本內需求情境驗證隨機動態規劃之穩健性 90
5.1.3 樣本外需求情境驗證隨機動態規劃之穩健性 93
5.2 蒙地卡羅模擬實驗結果分析 95
第六章 結論與建議 99
6.1 結論 99
6.2 建議 99
參考文獻 101
附錄一 產業案例輸入資料 109
附錄二 確定型產能規劃數學模式 111
附錄三 二階隨機規劃數學模式 112
附錄四 DEMAND SAMPLE PATH 113
附錄五 SIMULATION RESULT 117
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