臺灣博碩士論文加值系統

本研究透過FlexSim模擬工具對傳統自動化倉儲系統與AutoStore倉儲系統在進出貨效率方面進行了系統的比較。目的是量化和分析在相同條件下這兩種系統的效能差異，包括處理時間、錯誤率等指標。研究採用模擬實驗的方法，設計了一系列的操作場景，從而評估各系統在不同貨物流量和儲存策略下的表現。這些場景涵蓋了從低需求到高需求波動，以及不同的貨物種類和批量，提供了全面的性能評估。
結果表明，AutoStore倉儲系統在大多數場景下提供了較高的空間利用效率和運營靈活性。尤其是在高需求波動和多品種小批量的操作環境中，AutoStore系統顯示出其在快速響應市場變化方面的優勢。這些優勢主要來自於其高度模塊化和靈活的存儲結構，能夠快速適應和調整庫存布局。此外，AutoStore系統還展示了其在能源效率和維護成本方面的優勢，顯著降低了長期運營成本。
對於具有固定和大量單一商品流的應用，傳統自動化系統在初期投資和維護成本方面可能更具成本效益。這是因為傳統系統在面對單一、大批量商品時，其設置和運營成本較低，並且在這類場景下的運行效率仍然能夠滿足需求。
本研究不僅為物流和供應鏈管理領域的專業人士提供了決策支持，還為倉儲系統的未來研究和發展提供了新的見解和方向。未來的研究可以進一步探討在更複雜和多變的市場環境下，這兩種系統的性能表現，以及如何利用先進的技術（如人工智慧和物聯網）來進一步提升倉儲系統的效率和靈活性。通過這些深入的研究，將能夠為企業在選擇和優化倉儲系統時提供更加全面和實用的參考。

關鍵詞：倉儲自動化、AutoStore系統、傳統倉儲系統、進出貨效率、FlexSim模擬。

This study systematically compares the traditional automated warehousing system and the AutoStore warehousing system in terms of inbound and outbound efficiency using the FlexSim simulation tool. The objective is to quantify and analyze the performance differences between these two systems under identical conditions, including metrics such as processing time and error rate. The research employs simulation experiments, designing a series of operational scenarios to evaluate the performance of each system under different cargo flow and storage strategies. These scenarios cover everything from low demand to high demand fluctuations, as well as various types and batches of goods, providing a comprehensive performance evaluation.
The results indicate that the AutoStore warehousing system provides higher space utilization efficiency and operational flexibility in most scenarios. Especially in environments with high demand fluctuations and a wide variety of small batches, the AutoStore system shows its advantages in rapidly responding to market changes. These advantages mainly stem from its highly modular and flexible storage structure, which can quickly adapt and adjust the inventory layout. Additionally, the AutoStore system demonstrates advantages in energy efficiency and maintenance costs, significantly reducing long-term operating costs.
However, for applications with fixed and large single-item flows, the traditional automated system may be more cost-effective in terms of initial investment and maintenance costs. This is because traditional systems have lower setup and operating costs when dealing with single, large-batch goods, and their operational efficiency can still meet the demand in such scenarios.


This study not only provides decision support for professionals in the logistics and supply chain management field but also offers new insights and directions for the future research and development of warehousing systems. Future research can further explore the performance of these two systems in more complex and variable market environments, and how advanced technologies such as artificial intelligence and the Internet of Things can be utilized to further enhance the efficiency and flexibility of warehousing systems. Through these in-depth studies, more comprehensive and practical references can be provided for enterprises in selecting and optimizing warehousing systems.

Keywords: Warehouse Automation, AutoStore System, Traditional Warehousing Systems, Inbound and Outbound Efficiency, FlexSim Simulation.

目錄
摘要 I
Abstract II
目錄 IV
圖目錄 VII
表目錄 IX
第1章、 緒論 1
1.1、 研究背景與研究動機 1
1.1.1、 研究背景 1
1.1.2、 研究動機 2
1.2、 研究目的 3
1.3、 研究架構 5
第2章、 文獻探討 7
2.1、 自動化倉儲系統的演進 7
2.2、 Autostore系統的創新 8
2.3、 模擬倉庫的容積問題 9
2.4、 AGV行走路線問題 10
2.5、 不同倉儲模型下的選擇方法 11
2.6、 成本效益分析 12
2.7、 環境影響和可持續發展 13
2.8、 小結 14
第3章、 研究方法 16
3.1、 基礎模型情境 16
3.2、 AGV進出貨邏輯 17
3.3、 AGV 行駛最短路徑之方法 19
3.3.1、 數學模型 19
3.3.2、 AutoStore系統中適用的算法 21
3.4、 AGV 防碰撞邏輯 23
3.5、 AGV與AGV聯絡網路參數設定 25
3.6、 兩種倉儲模型之給貨邏輯 26
3.6.1、 AutoStore倉儲系統的給貨邏輯 27
3.6.2、 傳統自動化倉儲系統的給貨邏輯 28
第4章、 分析與討論 30
4.1、 傳統自動化倉儲系統與Autostore倉儲系統在相同倉儲容積下機器人移動距離之比較。 30
4.2、 傳統自動化倉儲系統與Autostore倉儲系統在相同倉儲容積下存貨量之比較。 35
4.2.1、 趨勢分析 36
4.2.2、 差異增長分析 38
4.2.3、 小結 39
4.3、 傳統自動化倉儲系統與Autostore倉儲系統在相同倉儲容積下撿貨效率之比較。 40
4.3.1、 趨勢分析 40
4.3.2、 差異分析 42
4.3.3、 小結 43
第5章、 結論與未來展望 44
5.1、 結論 44
5.2、 未來展望 45
參考文獻 47

圖目錄
圖 1-1電子商務成長率 2
圖 3-1 Auto store 智慧倉儲(左)與傳統智慧倉儲(右) 17
圖 3-2 Flexsim AGV 運行邏輯1 19
圖 3-3 Agv路徑規劃 22
圖 3-4 防碰撞控制區參數設置 24
圖 3-5 Agv網路屬性設置介面 26
圖 3-6 Autostore 給貨邏輯 27
圖 3-7 傳統智慧倉儲給貨邏輯 29
圖 4-1 兩倉儲系統之AGV 移動距離分析之程式碼與結果 31
圖 4-2 AGV移動距離擴展數據樣本量程式碼 32
圖 4-3 擴展後的數據 34
圖 4-4 線性回歸分析來比較兩種系統存貨量 37
圖 4-5 每個倉儲容積下兩個系統的存貨量差異 38
圖 4-6 增長差異連續圖 39
圖 4-7 撿貨效率趨勢分析折線圖 40
圖 4-8 迴歸分析結果 41
圖 4-9 python進行t檢定來比較傳統自動化倉儲系統與AutoStore系統在相同撿貨數量下的所需時間 42
圖 4-10 t檢定結果 42
圖 4-11 新增模擬數據後t檢定結果 43

表目錄
表 1-1 倉儲系統比較表格 3
表 4-1 倉儲系統擴展模型比較表格 30
表 4-2 兩種倉儲模型在各平方公尺下的存貨量表現 35

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