應用資料探勘於供應商交期管理

採購交期管理係指採購人員在下單給供應商後，針對採購品項的交貨期進行跟催及管理。若供應商交期延誤頻率高，則可能會造成公司競爭力下降、產品交貨延遲及客戶滿意度下降的問題。本研究使用採購相關資料做為原始資料集，並與採購人員進行供應商交期延誤的定義討論，再對資料集做前處理及特徵擴充。透過資料探勘分類演算法，本研究使用單純貝氏分類（Naïve Bayes）、隨機森林（Random Forests）、XGBoost（eXtreme Gradient Boosting）、K-近鄰演算法（K Nearest Neighbor Classfication）、Light GBM（Light Gradient Boosting Machine）進行供應商交貨延遲預測模型建立及分析比較，找出較佳的分類預測方法。造成供應商交期延誤的原因，可能在於人員、料件、供應商本身，或是數種特徵的結合體，本研究使用關聯規則（Association Rule）進行供應商交期延誤的關鍵因子探討，並將結果提供給採購人員進行改善的依據。

關鍵字

交期管理；關聯規則；資料探勘

並列摘要

Supplier Delivery Management refers to the procurement and management of the procurement items after placing orders with the supplier. If the supplier's delivery delay is high, it may cause the company's competitiveness to decline, delayed product delivery and decreased customer satisfaction. This study uses procurement-related data as the original dataset, and discusses the definition of supplier delivery delay with the purchasing staff, and then pre-processes and expands the features of the dataset. Through the data mining classification algorithm, this study uses Naïve Bayes, Random Forests, XGBoost, KNN, LGBM to establish and analyze the model to predict the supplier's delivery delay. The reasons for supplier delivery delays may be due to personnel, materials, suppliers themselves, or a combination of several characteristics. This study also uses the Association Rule to explore key factors for supplier delivery delays, and provides the results to the purchasing staff as a basis for improvement

並列關鍵字

Supplier Delivery Management ； Association Rule ； Data mining

參考文獻

[1] R. Agrawal, T. Imieliński, and A. Swami, Mining association rules between sets of items in large databases. ACM SIGMOD Record, 1993. 22(2): pp. 207-216.

Google Scholar

[2] R. Agrawal and R. Srikant, Fast Algorithms for Mining Association Rules in Large Databases, in Proceedings of the 20th International Conference on Very Large Data Bases. 1994, Morgan Kaufmann Publishers Inc. pp. 487-499.