本研究主要目標為協助 IC 封裝廠或具有類似加工特性之生產系統，在評估導入無人搬運車前的預算規劃階段，藉由本研究介紹的FlexSim 系統模擬建立與真實環境相似的模型並使用實驗設計法 (DOE) 針對模擬結果進行績效評估，進而幫助決策者決定多少數量的無人搬運車將是最有效率之方案。
本實驗的控制因子包含(1)訂單中產品A與產品B的比例、(2)工廠的工作負荷、(3)派車法則及(4) AGV車隊規模。關鍵績效指標 (KPI) 為每週產出工件數、車輛利用率、生產前置時間。本研究總共探討了 84 種情境，並透過分析控制因子與關鍵績效指標之間的主效果和交互作用，觀察到派車法則和AGV數量對系統效能產生顯著影響。最後根據實驗結果，我們獲得了本研究參考之IC封裝廠最佳AGV數量。

This study is to evaluate the optimal automated guided vehicle (AGV) fleet sizing for IC packaging plants or other factories with similar processing characteristics before introducing the expensive AGV system. By using FlexSim simulation model and Design of Experiment (DOE) in this study, the optimal AGV fleet size was determined considering some critical performance indicators.
The control factors include (1) the ratio of product A and B in the order, (2) the work loading of the plant, (3) dispatching rule, and (4) AGV fleet size. Key performance indicators (KPI) are weekly throughput, vehicle utilization rate, and production lead time. Eighty-four scenarios were investigated in this research. By analyzing the main effect and the interaction among control factors and KPI, dispatching rules and the number of AGV were observed resulting in a significant impact on system performance. According to the experiment results, the optimal fleet sizing was obtained for the reference IC packaging plant.

摘要 I
Abstract II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VII
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論文架構 3
第二章 文獻回顧與相關技術 5
2.1 IC封裝廠特性與零工式生產 5
2.2無人搬運車系統 6
2.2.1 定義 6
2.2.2 AGV車數決定與最佳化相關文獻 7
2.2.3 AGV載運法則 10
2.3 FlexSim 模擬軟體 10
第三章 研究方法 12
3.1系統描述 12
3.2 AGV系統模型之假設與限制 14
3.3 FlexSim模擬 15
3.3.1 FlexSim模組介紹與運用 15
3.3.2 FlexSim 模型建立方式 16
第四章 模擬輸出分析 21
4.1 實驗設計 21
4.2 投入與產出項相關係數分析 26
4.2.1 主效果 (Main Effect) 29
4.2.2 交互作用 (Interaction) 34
第五章 結論與未來建議 37
5.1研究貢獻及研究限制 37
5.2未來研究方向 38
參考文獻 39

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