查詢結果分析
來源資料
頁籤選單縮合
題名 | 裝配業自動倉儲之儲位規劃 |
---|---|
作者 | 鄭漢濱; 蘇純繒; 陳建文; | 書刊名 | 中原學報 |
卷期 | 21 1992.12[民81.12] |
頁次 | 頁178-190 |
分類號 | 448.946 |
關鍵詞 | 自動倉儲; 規劃; 裝配業; 儲位; 自動倉儲系統; 完全隨機儲存; 固定儲存; 分極儲存; ABC分類; 獨立需求; 相依需求; 群組技術; 模糊理論; AS/RS; Random storage; Dedicated storage; Class-based storage; ABC classification; Independent demand; Dependent demand; Group technology; Fuzzy theory; |
語文 | 中文(Chinese) |
中文摘要 | 自動化已成為當今工業界的必然趨勢,而自動倉儲系統(AS/RS)則在工廠自動化中扮演著不可或缺的角色。在自動倉儲系統中,內部儲位的規劃為一極為重要的研究課題,在早期以完全隨機儲存(Random Storage)與固定儲存(Dedicated Storage)二種方式應用在儲位規劃的政策上,由於此二種方式各有優缺點,因此在近年來發展了結合此二種方式優點的分級儲存(Class-base Storage)方法來做為儲位規劃的另一種方式。 在研究分級儲存的眾多文獻中,對於物料分級的做法大部份只是以週轉率為基礎來做ABC分類,但此種做法較適用於原物料零件及成品等有獨立需求(Independent Demand)性的物料,但對裝配用零件等有相依需求(Dependent Demand)性的物料則較不適用。因此本篇研究特針對裝配業的需求特性來發展另一啟發式(Heuristic)的物料分級11法。本篇研究首先將群組技術(GT)的分類觀念配合模糊理論(Fuzzy Theory)的聚類分析方法並考慮物料相依需求的特性與週轉率來對所需儲存的物料做一分級處理;再將已分級的物料用分級儲存的觀念以週轉率低高為基礎,依序儲存在離系統出入口不同遠近的區域,並考慮整個系統各種不同的外形尺寸,而推導出各級區在系統上的分段點模式,然後推導出整個系統的期望週期時間模式;最後以一範例來說明此方法並與完全隨機儲存方式做比較,由結果得知,本研究所發展出的方法較完全隨機儲存為優。 |
英文摘要 | The automated storage and retrieval systems (AS/RS) is widely used for reducing inventory and material handling cost in modern industry. In the early literatures, random storage and dedicated storage were two major methods to solve storage assignment problem of automated warehouse. However, by overcoming the disadvantages of these methods, the class-based storage has become a popular method in recent years. Most literatures of class-based storage assignment, use turnover rate as basis to do ABC classification. This approach is more suitable for the inventories with independent demand than inventories with dependent demand. Since the inventories of assembly industry have the characteristics of dependent demand, it is the objective of this research to deve1op a methodology to soIve the problem of storage assignment of automated warehouse in assembly industry. The paper first integrates the idea of group technology and fuzzy theory to develop a method for inventory classification. The mathematical models are then developed to decide the classification out points of storage location and expected travel time. Finally, the paper provides an example to display the storage assignment procedure developed in this research. In addition, the resu1ts of comparing this method with random storage assignment also shows better performances. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。