| Summary: | 碩士 === 國立高雄科技大學 === 資訊管理系 === 107 === The best way for the manufacturing factory to survive is to meet customer demands in order to maximize profits. The key point for being profitable is to balance quality and the cost of the product. The main purpose of the study is one heavy machinery company in Taiwan. The purpose of this study is data mining and analyzing the raw material inventory status and finds out the factors of the long-term inventory and the factors which affect the inventory time.
The subject is a case study based on the raw material inventory aging analysis table for 2018. The table also includes the order status and other information. After the ERP system data is reintegrated, cleaned, and converted, the stock time will be investigated by the Statistical method, Clustering, Apriori association rules, and Decision trees, etc.
The results show the company in the case study manages their stock well. Only 4.4% of the stock is not managed well. The 4.4% stock needs to be investigated as the amount increases to 11.5% for annual material requisition. For the data of "more than half a year in the stock", there are two highly related rules, including "medium order amount, with project manager, in-process materials", "user department is B22, not in the stock in the current year, in-process materials". The result also indicates that "whether the stock is safety stock", "customer order type", "products selection P/N", "purchasing type", "material category" are important factors for stock time via decision tree analyzing in the case of "more than half a year in the stock" and "less than seven days in the stock". Hope the result of this study can be helpful for relevant management departments for reference to reduce the costs of the stocks.
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