類 Kiva 系統的「Pod 分配之揀貨站挑選」、 「Pod 分配於揀貨站」與「品項分配至訂單」問題之探討

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宋狄軒(Ti-Hsuan Sung) 查詢紙本館藏

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論文名稱

類 Kiva 系統的「Pod 分配之揀貨站挑選」、「Pod 分配於揀貨站」與「品項分配至訂單」問題之探討

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摘要(中)

從現今工商業起飛，科技蓬勃發展的時代下，各種事情都講求效率，希望能愈快愈好，以產生更多利潤，從工業的角度來看，許多工廠從傳統的人力慢慢轉變成以機器去替代，再經過不斷的改革以及創新，現在以進入另一個階段，「大數據」的時代，此階段利用網路雲端、物聯網、電子商務系統等與機器做結合，使得工廠的效率提升到了另外一個檔次，不僅加快了運作速度也提高產品的品質，方能更迅速更穩定的提供現今社會的各種需求。
在物流業方面，每家物流公司都希望能利用最短的時間將產品送自顧客手中，以滿足顧客的需求。本研究以 Amazon 收購的 Kiva System 為研究目標，此系統最重要的改革就是從獲取訂單後，將訂單中的物品送往揀貨人員，如此，揀貨人員就不必親自前往揀貨區，降低了揀貨人員到揀貨區所花費的揀貨時間，從上述可看出，這系統的觀念大大顛覆了以往人們對傳統物流的作法，也對往後整個物流業有了更大更深的影響。
本研究欲探討在類 Kiva 系統的「Pod 分配之揀貨站挑選」、「Pod 分配於揀貨站」與「品項分配至訂單」等問題，利用不同的績效指標搭配不同的實驗因子，去比較哪種搭配最合適，並找出哪種情況下，對於 Kiva 系統將有顯著的影響，以期能達到最佳的效能，減少不必要的浪費。

摘要(英)

In the era with prosperous business and booming technology, efficiency has been the most important thing for doing all kinds of matters, hoping to have more profits as soon as possible. From an industrial point of view, many factories using machine to replace traditional manpower. After continuous reform and innovation, another stage, "big data" era, is coming. This stage is combine with the Clouds, IoT( Internet of Things) , E-commerce systems and other machines, so that efficiency gains. Not only accelerate the operating speed but also improve the quality of the product to meet the demand of the needs of today′s society more quickly and stable.
From the logistics point of view, each logistics company hopes to use the shortest time to send products to customers. This study is based on Amazon′s acquisition of Kiva system, the most important reform of this system is to get orders from the order after the items sent to the picking staff. In this way, picking staff do not need to go to the picking area in person, reducing the picking time from picking staff to the picking area. As can be seen from the above, the concept of this system change the way of traditional logistics, but also greatly affected the whole logistics industry.
This study wants to investigate the problem” The selection of picking station of Pod assign”, “Pod assign in picking station” and “ Items assign to the order” in the Similar Kiva system. Using different performance indicators with different experimental factors to compare with what the most appropriate combination, and find out what circumstances will have a significant impact for the Kiva system, so as to achieve the best performance and reduce unnecessary waste.

關鍵字(中)

★ 物流中心
★ Kiva系統
★ 無人搬運車派送
★ 訂單分配

關鍵字(英)

★ Distribution Center
★ Kiva System
★ AGV Dispatching
★ Assignment

論文目次

摘要 I
Abstract II
圖目錄 VI
表目錄 VIII
第一章緒論 1
1.1 研究背景 1
1.2 亞馬遜第八代物流中心 2
1.3 研究動機 3
1.4 研究目的 4
1.5 研究環境與假設 4
1.6 研究方法說明 7
1.7 論文架構 8
第二章文獻探討 10
2.1 物流 11
2.1.1 物流的定義 11
2.1.2 物流的領域 13
2.1.3 物流中心之介紹及其類別 14
2.1.4 物流中心之功能及其重要性 17
2.2 揀貨作業 20
2.2.1 揀貨作業的概念及方式 20
2.2.2 揀貨路徑策略 23
2.3 無人搬運車系統 28
2.3.1 無人搬運車系統之介紹 28
2.3.2 無人搬運車之派送問題 28
2.3.3 AGV的途程（routing）問題 32
2.4 Kiva系統 34
2.4.1 Kiva系統之介紹 35
2.4.2 Kiva之作業流程 40
2.4.3 Kiva 系統之效益 42
第三章研究方法 45
3.1 符號及變數定義 45
3.2 類 Kiva 系統中作業流程說明 46
3.2.1 類 Kiva 系統中揀貨工作站WS(w)之作業流程 46
3.2.2 類 Kiva 系統中 Pod(p) 之分配流程 49
3.3 各研究議題之方法整理 53
3.4 缺貨時間點計算 55
3.5 Pod 分配之揀貨工作站挑選法則 56
3.5.1 「隨機挑選」法則 56
3.5.2 有「已分配 Pod 數最小之工作站優先」法則 57
3.5.3 有「已分配 Pod 之總剩餘揀貨時間最小之工作站優先」法則
58
3.5.4 「未滿足訂單品項總數最大之工作站優先」法則 59
3.5.5 「未滿足訂單品項總數最小之工作站優先」法則 60
3.5.6 「訂單的總寬放時間最少之工作站優先」法則 61
3.5.7 「訂單的平均寬放時間最少之工作站優先」法則 63
3.5.8 最小（總寬放時間除以尚未完成揀貨的訂單品項數）比值之工作站優先法則 64
3.6 類 Kiva 系統中 Pod 分派法則 66
3.6.1 隨機法則 66
3.6.2 「可滿足最多（訂單）品項總數的 Pod 優先」法則 67
3.6.3 「可滿足最多品項種類數的 Pod 優先」法則 68
3.6.4 「距離揀貨工作站最近的 Pod 優先」法則 69
3.6.5 「有品項種類被 Pod 滿足之訂單的平均出貨時間最近優先」法則 70
3.7 類 Kiva 系統中品項分配法則 72
3.7.1 隨機排序 72
3.7.2 「出貨期最早之訂單愈優先」法則 73
3.7.3 「對該品項種類 IT* 需求量愈大之訂單愈優先」法則 75
3.7.4 「對該品項種類 IT* 需求量愈小之訂單愈優先」法則 76
3.7.5 「寬鬆時間愈小之訂單愈優先」法則 78
3.7.6 「未滿足品項種類數愈多之訂單愈優先」法則 80
3.7.7 「未滿足品項種類數愈少之訂單愈優先」法則 82
3.7.8 「未滿足（訂單）品項總數愈多之訂單愈優先」法則 84
3.7.9 「未滿足（訂單）品項總數愈少之訂單愈優先」法則 86
第四章實驗結果與分析 89
4.1 實驗設計 89
4.1.1 實驗環境 89
4.1.2 實驗訂單張數與其他設定 91
4.1.3 環境假設 91
4.1.4 模擬實驗因子 92
4.1.5 實驗績效評估指標 94
4.2 統計分析 95
4.2.1 依「總系統執行時間（Total System Time）」為績效評估指標 96
4.2.2 依「訂單流程時間（Flow Time）」為績效評估指標 107
4.2.3 依「訂單延遲時間（Tardiness Time）」為績效評估指標 118
4.2.4 依「總 Pod 行走時間（Total Pod Time）」為績效評估指標
129
4.3 實驗結論 140
第五章結論與後續建議 142
5.1 研究結論 142
5.2 未來研究建議 143
參考文獻 144
中文文獻 144
英文文獻 146

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指導教授

何應欽(Ying-Chin Ho)

審核日期

2017-7-26

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