結合 ABC 分析與模糊分類分析法於存貨管理之應用
－以醫院衛材為例
合理化的存貨管理 成本、資金、服務三方面滿足，然而對多數品項若施以爲
相同程度之控管，既不經濟且更為耗時，採重點管理 (management by importa
nce) 則是明智的方式，
至今存貨管理多以成本作 決策變數，以存貨管理規劃周期爲 ( 例如一年 ) 之總
使用金額 依據，並將存貨加以分類，爲 ABC 分析法 其典型代表者，在分類爲
後進而對各類存貨專案採取不同的存貨管理策略，然而非成本準則 ( 通常是
作業屬性：如前置時間、存貨的老化報廢、可用率、可替代性、關鍵性 ) 有
時也將扮演關鍵角色。模糊分類法即考量非成本因素，輔以 ABC 分析法之不
足。且於本研究中對相同衛材品項作模糊分類後，與僅使用 ABC 分析法之一
致性高達 73.6% 。
另研究結合傳統的 ABC 分析法與模糊分類法，推導出一個存貨重要性分類方
法並對分類後之比較實施前後最重要群品項與全院品項的存貨績效評估。結
果顯示，最重要群之品項數為 52 項，佔全部品項數之 13.9% ，佔年度領用成
本之 66.9% ，只要對最重要群之品項妥善管理，即可提升存貨管理之績效，
本研究於 93 年 3 月始對最重要群品項施以重點管理，實施前後其全院存貨週
轉率由 93 年 1 月的 99.4% 提升至 93 年 4 月的 111.0% ；盤點差異率由 93 年
1 月的 37.6% 降低至 93 年 4 月的 24.0% ；缺貨率由 93 年 1 月的 3.20% 降低
至 93 年 4 月的 1.12% 。由此可知，結合成本與非成本因素之存貨分類法，於
存貨管理上亦可有其效益
Combining Fuzzy Classification and ABC Analysis
in Hospital Inventory Management
The objective of inventory management is to rationalize cost, funds and service. Since there ar e too many items of inventory in hospitals, practically, it is difficult to pay equal attention to m anage each single item of inventory. Therefore, management by importance is an ideal method . Traditionally, inventory management often base on the cost attributes. ABC analysis is a typic al method of inventory management. In addition to cost, leading time, replaceable and other n on-cost attributes are also important factors in inventory control. One limitation of the ABC an alysis system is that non-cost attributes cannot be considered in this system.
In this research, we combined fuzzy classification and ABC analysis systems, which considere d both non-cost and cost attributes. This new inventory management system divides inventory items into three groups: important, ordinary, and unimportant groups.
This new inventory management system was implemented in one regional hospital in Taipei.
We compared inventory indicators, including inventory turnover rate, stocktaking error and sh ortage rate during January to April 2004.
The results showed that 52 items were identified as important group, which was 13.9% of all t
he hospital inventory items. By focusing on the important group management, results showed
that inventory turn over rate raised from 99.4 % to 111.0 %; stocktaking error reduced from 37
.6 % to 24.0 %; shortage rate reduced from 3.20 % to 1.12 % during January to April 2004. Th
erefore, we may conclude that combining Fuzzy Classification and ABC Analysis is a good to
ol in hospital inventory management
