汽車製造業在接連面臨2008年金融海嘯與大陸車低價競爭的優勢，未來ECFA通過汽車相關產業條例後可能面臨更大規模的開放大陸汽車來台販售，國內八大車廠在如此嚴峻的汽車市場中，各家業者唯有積極導入新車款與提升配備種類，提供客戶全方位的選擇才能在競爭激烈的市場中佔有一席之地，在此種競爭風氣的助長下汽車製造商在零件管理的品項相對也會提升，因此汽車製造業如何能夠有效率的管理庫存水準，使庫存能在對應生產需求的條件下達到最低的庫存金額，儼然成為每家汽車製造商必須面臨重要課題。 本研究旨在針對汽車零件庫存水準的原因進行分析，透過資料探勘的技術針對影響庫存的參數進行探討，過程中主要是利用統計軟體Clementine，對於汽車庫存履歷進行資料探勘，挖掘關鍵性因子提供庫存管理者正確之改善方向，減少試誤的次數及摸索的時間，同時可藉由利用軟體已建立的模型，針對新零件所設定參數值進行庫存水準的預測提前預知庫存水準，使企業除了能夠快速且有效降低庫存水準更能預估庫存資金的需求，減少企業在庫存的資金積壓，提升在同業中之競爭力。Automotive manufacturing industry has faced financial crisis of 2008 and the competitive advantage of China’s inexpensive car continuously. In automotive related industries may face the extensive trade deficits about the car market of China after signing ECFA Ordinance. The only thing that automotive corporations can do is to import new models actively and upgrade fixture types in tough auto market. To providing customers a full range of options then the automotive corporations may have more competition in the highly competitive market. In such a competitive atmosphere fueled to vehicle manufacturers the items of assembly parts will be increased. So the inventory management would be an important issue for car manufacturers on the premise of satisfying production requirements. The issue is how to make the management efficiently of inventory levels to achieve the lowest inventory amount of money. This research aims auto parts inventory levels and analysis of the causes, through the techniques of data mining to discuss the parameters influence about the stocks. In the process is to use the statistical software Clementine to explore the inventory about the stock in automotive corporation. According to the results of mining can provide the inventory key for management to improve inventory in the right direction and reduce the times of the methods about Try and Error. In the meanwhile we can take advantage of the established model to predict the inventory levels according to the parameters that we set up for the new parts. Though this mode we make business not only to reduce inventory quickly but also forecast the demand for stock funds. Reducing the backlog of business also enhances competitiveness in the same industry.
