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研究生:柯閔翔
研究生(外文):KO,MIN-HSIANG
論文名稱:關聯法則應用於機器人輔助揀貨下移動式輕型料架儲位指派策略之模擬分析
論文名稱(外文):Simulation Analysis of Applying Association Rule to Storage Assignment Strategy of Shelving Unit by Robot-Assisted Picking
指導教授:卓裕仁卓裕仁引用關係
指導教授(外文):Cho, Yuh-Jen
口試委員:陳立峰張建彥卓裕仁
口試委員(外文):Chen, Li-FengChang, Chien-YenCho, Yuh-Jen
口試日期:2020-06-17
學位類別:碩士
校院名稱:中華大學
系所名稱:運輸科技與物流管理學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:56
中文關鍵詞:關聯法則儲位指派機器人輔助揀貨
外文關鍵詞:Association rulesStorage assignmentRobot-assisted picking
相關次數:
  • 被引用被引用:1
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  • 評分評分:
  • 下載下載:38
  • 收藏至我的研究室書目清單書目收藏:1
隨著時代的進步,現代的物流中心比起以往傳統的物流中心,漸漸地從人力作業變成使用機器人作業,也從傳統的以人至貨的揀貨作業變成以貨至人的揀貨作業模式,是近幾年來興起的一個新課題,如何提升訂單揀貨效率也漸漸地越來越受到重視,希望能夠降低揀貨成本以及提升揀貨效率為最終目標。
本研究利用Excel產生虛擬訂單進行確認,並且應用關聯法則進行模擬分析,探討有應用關聯法則和ABC分類法則儲位指派策略及單純只使用ABC分類法則的儲位指派策略,比較兩種揀貨策略的揀貨效率,並且確認使用關聯法則後進行儲位指派是否能相對明顯的提升揀貨效率,最後提出適合的儲位指派策略。
經過模擬分析確認後發現100張虛擬訂單在未使用關聯法則只考慮商品ABC分類進行儲位指派的策略下,其機器人的總移動距離為29726.35公尺,而在有使用關聯法則再進行儲位指派之策略下,機器人的總移動距離則減少至13017.50公尺,使用關聯法則再進行儲位指派策略比起單純考慮商品ABC分類進行儲位指派策略,兩種策略方法,前者比後者總共提升了56.21%的效率。由此可知,利用關聯法則進行儲位指派確實能夠很有效的提升揀貨效率。

With the progress of the times, modern logistics centers have gradually changed from human operations to using robots, and from traditional human-to-goods picking operations to cargo-to-human picking modes compared to traditional logistics centers. It is a new subject, which has arisen in recent years. How to improve the efficiency of order picking is gradually getting more and more attention. This research hopes to reduce the cost of picking and increase the efficiency of picking as the ultimate goal.
This study uses Excel to generate virtual orders for confirmation, and uses correlation rules for simulation analysis. It discusses storage assignment strategies that use correlation rules and ABC classification rules, and storage assignment strategies that use only ABC classification rules. Compare the picking efficiencies of the two picking strategies, and confirm whether the use of the correlation rule for storage assignment can relatively improve the picking efficiency. Finally, a suitable storage assignment strategy is proposed.
After simulation analysis and confirmation, the results show that 100 virtual orders without the use of the association rule only consider the commodity ABC classification for the storage assignment strategy, the total distance of the robot's movement is 29726.35 meters, and the storage assignment according to the association rule is used. Under this strategy, the total distance moved by the robot reduced to 13017.50 meters. Using the association rule to carry out the storage location assignment strategy compared to simply considering the commodity ABC classification for the storage assignment strategy, the two strategy methods, the former has improved the efficiency of 56.21% compared with the latter. Such a result showed that the usage of association rules to storage allocation could effectively improve the picking efficiency.
摘要 i
Abstract ii
致謝 iii
目錄 iv
表目錄 v
圖目錄 vi
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研究對象與範圍 3
1.4 研究流程與步驟 3
第二章 文獻回顧 5
2.1 儲位管理與指派 5
2.2 關聯法則 6
2.3 機器人輔助揀貨 8
2.4 小結 17
第三章 研究方法 18
3.1 關聯法則 18
3.2 模擬法 20
第四章 模擬實驗與分析 22
4.1 模擬訂單 22
4.2 ABC分類 26
4.3 關聯法則應用 27
4.4 儲位指派策略 32
第五章 結論與建議 37
5.1 結論 37
5.2 建議 37
參考文獻 39
附錄一 100種假設商品資料 43
附錄二 訂單產生結果 45
附錄三 關聯法則統計表 49
附錄四 關聯法則前216項計算結果 50

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