本論文是在兩個撿貨區的倉儲系統下提出一個檢貨時間的評估模式。揀貨人員根據訂單進行貨物揀取而各貨物的擺放是根據訂單體積指標(Cube-Per-Order Index; COI)為基礎，並利用最少的儲存空間達到最小化行走距離之目的，進而達到揀貨績效的提升。本論文先推導出行走時間的一、二階動差並考量允許訂單批量處理的情況下求得平均揀貨時間。此外，本論文也利用eM-Plant模擬軟體建構倉儲模式，並進行模擬測試，並探討最佳訂單批量及揀貨路徑中所運用的COI策略各項參數分析。

This thesis presents a throughput evaluation model in a low-level picker-to-part system, which is a 2-block warehouse. The order-picker retrieves items in the tour according orders and assumed that items are assigned to storage location on the basis of the cube-per-order index (COI) rule. Adopt return policy and obtain the first and second moments of the order-picker’s travel time. Then we consider order batching problem in the warehouse and assume that orders arrive according to a Poisson process. Apply these moments to estimate the average throughput time. The results generated by the model are compared and validated via simulation which modeled by software eM-Plant. Furthermore, the effects of batch size, storage strategy on the travel distance are discussed in the paper.

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