類Kiva系統之Pod分配揀貨工作站挑選、Pod分配與品項分配之相關問題探討

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姓名

王新淳(Xin-Chun Wang) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

類Kiva系統之Pod分配揀貨工作站挑選、Pod分配與品項分配之相關問題探討

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摘要(中)

隨著網路技術的進步，大幅的改變了人們之消費習慣，顧客無論在何時何處都能夠在網路上選購商品，顛覆以往花費時間成本到實體店面購物。這種消費習慣的轉變也迫使物流中心做出改變，追求更有效率之運作模式。

工業4.0的到來使得物流中心智慧化，提升了物流中心競爭力。全球電子商務龍頭亞馬遜於2012年收購Kiva System，並以Kiva System為其第八代物流中心之核心。Kiva System最大之特色為Kiva機器人，以「物到人」的方式完成揀貨作業，降低了龐大的人力成本，此舉顛覆了以往以「人到物」的方法進行揀貨作業，也大幅提升了物流中心之效率。

本研究欲探討類Kiva系統中之「Pod分配之揀貨工作站挑選」、「Pod分配挑選」及「訂單分配之品項挑選」等派送問題，並且透過模擬軟體提出多種績效指標，用來評估及分析何種因子法則之組合能有最好的表現，期望能找出最佳之法則使類Kiva系統達到最佳效能，減少不必要的浪費。本研究將延續何東益（2019）之研究，觀察何東益（2019）所提出之單屬性法則並發展出一多屬性評估法則，期望多屬性評估法則能在類Kiva系統中有不錯的績效表現。

摘要(英)

With the advancement of network technology, people′s consumption habits have been greatly changed. Customers can buy goods on the Internet no matter when and where they are, subverting the time and cost of shopping in physical stores. This change in consumption habits also forced the logistics center to make changes in pursuit of a more efficient operation mode.
The arrival of Industry 4.0 makes the logistics center intelligent and enhances the competitiveness of the logistics center. Global e-commerce leader Amazon acquired Kiva System in 2012, and made Kiva System the core of its eighth-generation logistics center. The biggest feature of the Kiva System is the Kiva robot, which completes the picking operation in a "goods-to-human" way, which reduces the huge labor cost. This move subverts the previous "human-to-goods" method for picking operations, and also greatly improves The efficiency of the logistics center.
This paper intends to explore the delivery problems of " workstation selection", "Pod allocation" and "SKU allocation" in Kiva-like systems, and proposes various performance indicators through simulation software for evaluation and Analyze what combination of factor laws can have the best performance, and expect to find the best law to make the Kiva-like system achieve the best performance and reduce unnecessary waste. This research will continue the research of Ho (2019), observe the single-attribute rule proposed by Ho (2019) and develop a multi-attribute evaluation rule, hoping that the multi-attribute evaluation rule can perform well in Kiva-like systems .

關鍵字(中)

★ Kiva System
★ 物流
★ 多屬性評估方法

關鍵字(英)

★ Kiva System
★ Logistics
★ Multi-attribute evaluation

論文目次

目錄
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 研究目的 1
1.3 研究動機 2
1.4 研究環境 2
1.5 研究架構 4
第二章文獻探討 6
2.1 物流 6
2.1.1 物流之定義 6
2.1.2 物流中心之類型與作業 7
2.2 揀貨介紹 9
2.2.1 揀貨作業 9
2.2.2 揀貨路徑策略 13
2.3 Kiva系統 15
2.3.1 Kiva系統介紹 16
2.3.2 Kiva系統之相關研究 20
第三章研究方法 23
3.1 符號及變數定義 23
3.2 類Kiva系統作業流程 24
3.2.1 揀貨工作站作業流程 24
3.2.2 Pod分配流程 27
3.3 各研究議題之方法整理 30
3.4 Pod分配之揀貨工作站挑選法則 31
3.4.1 隨機挑選法則 31
3.4.2 「已分配Pod數最小」法則 31
3.4.3 「未滿足訂單品項總數最小」法則 32
3.4.4 「訂單總寬放時間最少」法則 33
3.4.5 「訂單平均寬放時間最少」法則 33
3.4.6 「最小總寬放時間與尚未滿足揀貨的訂單品項總數之比值」法則 34
3.4.7 揀貨工作站之多屬性評估法則 35
3.5 Pod分配挑選法則 37
3.5.1 隨機法則 37
3.5.2 「距離揀貨工作站最近的Pod優先」法則 37
3.5.3「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 38
3.5.4 Pod多屬性評估法則 40
3.6 品項分配法則 44
3.6.1 隨機法則 44
3.6.2 「對該品項種類IT*需求量愈大之訂單愈優先」法則 44
3.6.3 「對該品項種類IT*需求量愈小之訂單愈優先」法則 45
3.6.4 「未滿足品項種類數愈多之訂單愈優先」法則 46
3.6.5 「未滿足品項總數愈多之訂單愈優先」法則 48
3.6.6 訂單多屬性評估法則 49
第四章實驗結果與分析 53
4.1 模擬實驗設計 53
4.1.1 環境設定 53
4.1.2 訂單設定與其他設定 55
4.1.3 實驗假設 56
4.1.4 實驗因子組合 56
4.2 績效評估指標 58
4.3 統計分析 58
4.3.1 依「總系統執行時間」為績效指標 60
4.3.2 依「訂單流程時間」為績效指標 65
4.3.3 依「差異時間」為績效指標 70
4.3.4 依「延遲時間」為績效指標 75
4.3.5 依「總Pod行走時間」為績效指標 80
4.3.6 依「Pod在工作站平均等待時間」為績效指標 84
4.4 實驗結論 89
第五章結論與後續建議 93
5.1 研究結論 93
5.2 未來研究建議 94
參考文獻 95
中文文獻 95

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

2020-8-18

推文