結合分群法及ABC 分析於庫存管理之改善 -以IC設計為例

Integrating Clustering Methods and Activity Based Classification Analysis to Improve Inventory Management - A Case of IC Design House

陳香如(Hsiang-Ju Chen)

指導教授 ： 劉敦仁

國立交通大學/管理學院/管理學院資訊管理學程/碩士(2011年)

https://doi.org/10.6842/NCTU.2011.00921

摘要

在日新月異且不斷進步的科技產業中，越是賺錢的產品，越是希望能在越短時間內提供給客戶，然而，以IC設計產業來說，熱銷產品在旺季時，往往會因為供不應求而造成客戶滿意度下降；相反地，當市場供需過量時，又因為製造過剩而造成庫存成本大增，甚至演變成庫存呆滯而超過存放期限一年無法銷售的營運虧損狀態。以公司立場來說，希望能隨時滿足客戶訂單需求，也希望能在旺季時，能將營利提高，然而，庫存呆滯問題也造成管理者的隱憂，造成決策單位在準備安全庫存時的兩難。
因此，本研究將分析實際IC設計業之銷售資料建置，整合分群方法與庫存管理ABC分析法，以改善庫存管理，並比較庫存管理ABC分析方法，進而找出更符合公司的庫存管理方式，提供決策者準備安全庫存的依據。研究成果將可協助相關單位制定決策，以提升客戶滿意度並降低庫存成本。

關鍵字

資料探勘 ； 分群 ； EM ； ABC分析 ； 安全庫存

並列摘要

Companies usually want to satisfy customer’s requirements and also increase the profit at the same time. Nevertheless, the problems of slow-moving inventory became an underlying concern to managers and the dilemma for setting the quantity of safety stock.
This research integrates Clustering methods and Activity-based Classification (ABC) analysis to determine the stock amount. The actual sales data of an IC design house is analyzed by comparing with traditional ABC analysis to discover the most appropriate way for stock management. The research result can be a reference for decision makers to prepare safety stock and improve inventory management. Furthermore, the research findings can be helpful to increase customer satisfaction and decrease stock cost.

並列關鍵字

Data mining ； clustering ； EM ； ABC analysis ； safety stock

參考文獻

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