類似Kiva系統之訂單分配於揀貨工作站的相關問題探討

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题名:	類似Kiva系統之訂單分配於揀貨工作站的相關問題探討
作者:	黃獎緯;Huang,Jiang-Wei
贡献者:	工業管理研究所
关键词:	Kiva作業系統;訂單分配法則;訂單分配之揀貨工作站挑選法則;訂單分配之空儲存格挑選法則;Kiva Operation System;Order Assigning Problem;Order of Picking Workstation Selecting Problem;Order of Cell Selecting Problem
日期:	2016-07-26
上传时间:	2016-10-13 12:13:40 (UTC+8)
出版者:	國立中央大學
摘要:	近年來受到全球化的影響且網路科技迅速發展，使市場競爭日趨激烈，因此物流產業為了因應這種變化，必須找出更有效率的作業模式，以符合消費市場的需求，並提供顧客更高的服務水準與品質。因此若是能使用恰當的作業策略來降低從進貨到出貨的作業時間與成本，這對提升物流中心的運作效率將有非常顯著之影響。 Kiva作業為目前物流作業中最新的一種策略，是指在Kiva作業上不用像以往傳統物流那樣以「人到貨」的方式，而是顛覆了傳統物流上的做法，改變為「貨到人」的方式來搬運商品，以致於能夠大幅降低在整個作業流程上人力與時間的成本。如此便可使品項從進貨到出貨的時間最小化，因此Kiva作業適合需要快速處理的緊急訂單，且能夠將訂單從訂單池選取進行揀取和包裝後，再出貨。本研究針對使用Kiva作業系統（Kiva Operation System）之物流中心所延伸出的三種決策問題進行探討，並分別提出相對應的訂單分配、訂單分配之工作站挑選，與訂單分配之空儲存格挑選問題，再利用模擬實驗所得到的數據，比較在此環境下的總系統執行時間（Total System Time）、總延後時間（Total Tardiness），以判斷哪種因子組合對訂單分配之揀貨工作站與訂單分配之空儲存格的挑選法則作業效率有較顯著的提升。 ;Because our country has impacted by globalization, and the network is growing fast, the market competition is becoming more and more fierce. For those reasons, the logistics industry has to find an operation mode which was more effective to conform to the demands of consumer market, and provide a higher level and quality to customers. Thus, reducing the operation time and costs from receiving to shipping by using appropriate operation strategy will significantly impact the effectiveness of logistic center. Kiva operation is a latest strategy of logistics operations, which means that Kiva operation changed to handle goods in "goods to person" method instead of in "person to goods" method, which subverted the measures in traditional logistics, resulting in big reduction in the cost and time of the whole operation process. Therefore, the time from purchase to shipment can be minimized. For those characteristics, Kiva operation is particularly suitable for urgent orders and it can pick orders from order pool to pick and pack, and then ship. This research aims to three issues of Kiva Operation System, which were order assigning problem rule, order of workstation selecting problem rule, and order of cell selecting problem rule. Finally, in this environment, comparing the data by Total System Time, Total Tardiness, which were obtained by simulation experiments, to know which combination of the rules will performs better.
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