| Summary: | 碩士 === 華梵大學 === 工業工程與經營資訊學系碩士班 === 94 === In many business management policies, the inventory management have been the very important of the business administration. The objective of invcntory management is to rationalize cost, funds and service. Since there are too many items of inventory in factory, practically, it is difficult to pay equal attention to manage each single item of inventory. Therefore, management by importance is an ideal method.
Traditionally, inventory management often based on the cost attributes. ABC analysis is a typical method of inventory management. In addition to cost, leading time, replaceable and other non-cost attributes are also important factors in inventory control.One limitation of the ABC analysis system is that non-cost attributes cannot be considered in this system.
In this research, we combined grey clustering analysis classification and ABC analysis systems, which considered 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 factory in forcecon. We conpared inventory indicators, including inventory turnover rate, stocktaking error and shortage rate during January to April 2006. The results showed that 52 items were identified as important group, which was l4.0% of all the factory inventory items. By focusing on the important group. The results also revealed that inventory tum over rate raised from 99.5% to 112.5%; stocktaking error reduced from 37.4% to 24.1%; shortage rate reduced from 3.54% to l.10% during January to April 2006. Therefore, we may conclude that combining grey clustering classification and ABC analysis is a good tool for factory inventory management﹒
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