類Kiva系統之Kiva派送與Pod暫存區停放位置分配等問題之探討

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梁苹(Ping Liang) 查詢紙本館藏

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工業管理研究所

論文名稱

類Kiva系統之Kiva派送與Pod暫存區停放位置分配等問題之探討

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摘要(中)

近年來，網路科技的日新月異帶動了電子商務的發展，大多數的消費者皆透過網路來購買所需之商品，因此為了蒐集大量數據，以了解消費者喜好及滿足消費者少量多樣之需求，工業4.0及物聯網技術紛紛被引入。然而許多公司為了能盡量在最短的時間內滿足顧客的需求，將物流中心中複雜的硬體與軟體做整合，逐漸朝自動化與智慧化發展。
亞馬遜物流中心於2012年3月，併購了主要生產自動化機器人的Kiva System，為第一個將AGV用於物流中心的公司。於此系統中，會利用Kiva機器人來載取Pod(貨架)至揀貨工作站，從傳統人至物的揀貨方式，變成物至人的作業方式，此舉不僅提高了物流中心之靈活性，也可使揀貨人員能更快速且更準確地完成訂單。
本研究主要延伸探討黃靖華（2017）中模擬亞馬遜物流中心之類Kiva系統中車輛之派送、Pod暫存區位置分配及補貨條件等三個問題進行探討。利用所提出之新的單屬性法則及單屬性組合法則做比較，並利用Arena模擬程式模擬出類似亞馬遜物流中心之環境，再利用三項不同的績效指標來評估在當前之環境下，各種不同的因子組合中，哪些因子組合為最佳，以期望能有效減少Kiva機器人之總揀貨行走距離，藉此提高揀貨人員的工作效率，並最大化系統資源。

摘要(英)

In recent years, the fast development of Internet technology has promoted the development of E-commerce. Most consumers purchase the required goods via online. Therefore, in order to collect a large amount of data to understand consumer preferences and satisfied with consumers’ a small and diverse demand, Many enterprises have been introduced Industry 4.0 and Internet of Things technologies. However, in order to meet customers′ demand in the shortest possible time, many companies have integrated the complex hardware and software in the logistics center and gradually developed towards automation and intelligence.
In March 2012, Amazon Logistics Center acquired Kiva System, which mainly produces automated robots, as the first company to use AGVs in logistics centers. In this system, Kiva robots can pick-up and delivery Pods to the picking stations, From the tradition way picker-to-good to good-to-picker , it’s not only improves the flexibility of the logistics center, but also enables the pickers to complete orders faster and more accurately.
In this paper, we continue Huang (2017) research. simulate the problem of Kiva Robot allocation, Pod storage allocation combine and replenishment condition three problems in an environment resembles Kiva System. Propose new single-attribute rules and single-attribute combination rules. The simulation software is used analyze the results and find out the performance of rules proposed by this study in different factors. We expect that the flexibility of the Kiva system and the advantage of receiving instant message will effectively reduce the path of the Kiva robot, improving picker’s efficiency and achieve the best performance for the entire system.

關鍵字(中)

★ 工業4.0
★ 物聯網
★ 亞馬遜物流中心
★ Kiva System

關鍵字(英)

★ Industry 4.0
★ IoT
★ Amazon Logistics Center
★ Kiva System

論文目次

摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 vii
第一章、緒論 1
1.1 研究背景 1
1.2 研究動機 1
1.3 研究目的 2
1.4 研究環境 2
1.5 論文架構 5
第二章、文獻探討 7
2.1 物流 7
2.1.1 物流的定義 8
2.1.2 物流的介紹與作業流程 9
2.2 揀貨作業 11
2.2.1 揀貨方式 11
2.2.2 揀貨路徑 13
2.3 Kiva系統 15
2.3.1 Kiva系統的介紹 15
2.3.2 Kiva系統的流程 18
2.3.3 Kiva系統之相關研究 20
第三章、研究方法 22
3.1 符號與變數定義 22
3.2 類Kiva系統中揀貨工作站WS(w)之作業流程 23
3.3 類Kiva系統中Pod(p)之作業流程 25
3.4 研究之方法整理 28
3.5 Kiva機器人分配於Pod之相關法則 29
3.5.1 隨機分配法則 29
3.5.2 「與Pod距離最近之Kiva優先分配」法則 29
3.5.3 「閒置最久之Kiva優先分配」法則 30
3.5.4 「使用率最低之Kiva優先分配」法則 31
3.5.5 「剩餘電力最多之Kiva優先分配」法則 32
3.5.6 「與Pod距離最近之Kiva優先分配」法則搭配「剩餘電力最少之Kiva優先分配」法則 33
3.5.7 「與Pod距離最近之Kiva優先分配」法則搭配「剩餘電力最多之Kiva優先分配」法則 34
3.6 Pod暫存區位置指派法則 35
3.6.1 隨機指派位置法則 36
3.6.2 「固定位置停放」法則 36
3.6.3 「與Pod目前位置距離最近的位置優先分配」法則 36
3.6.4 「與Pod原所在之揀貨工作站距離最近的位置優先分配」法則 37
3.6.5 「與揀貨工作站中心點距離最近的位置優先分配」法則 38
3.6.6 「與揀貨工作站（需求）重心點距離最近的位置優先分配」法則 38
3.6.7 「與補貨區中心點距離最近的位置優先分配」法則 39
3.6.8 「與充電區之中心點距離最近的位置優先分配」法則 41
3.6.9 「與整個倉庫中心點距離最近的位置優先分配」法則 42
3.6.10 「與任一揀貨工作站距離最近的位置優先分配」法則 44
3.7 補貨條件 45
3.7.1 「固定缺貨比例」法則 45
3.7.2 「動態缺貨比率」法則 46
第四章、實驗結果與分析 47
4.1 模擬實驗 47
4.1.1 實驗環境設定 47
4.1.2 實驗環境中訂單設定 49
4.1.3 環境假設 49
4.1.4 實驗因子組合 50
4.2 績效評估準則 52
4.3 實驗分析 53
4.3.1 依「總系統執行時間（TST）」為績效指標 54
4.3.2 依「訂單流程時間（OFT）」為績效指標 59
4.3.3 依「Kiva總執行揀貨任務時間（TPT）」為績效指標 64
4.4 實驗結果 69
第五章、結論與後續研究建議 71
5.1 研究結論 71
5.2 後續研究建議 72
參考文獻 73
中文文獻 73
英文文獻 74

參考文獻

中文文獻
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指導教授

何應欽(Ying-Chin Ho)

審核日期

2020-8-17

推文