基于聚类算法的电力制造业ERP数据分类

鉴于传统制造业企业仓储分类方法分类边界不明确、难以适应现代企业信息化发展趋势的问题，提出了基于聚类算法的ABC库存分类算法，提升了传统库存分类模型的分类精度和效率。以某电力制造业企业的库存产品数据为研究对象，结合聚类算法与ABC分类法提出了适用于实际研究场景的评价函数，并给出了新的基于k-means 算法的ABC分类法。采用该分类模型对库存环网柜产品进行分类，并基于ERP系统中存储的产品数据将库存环网柜产品分为A、B、C三类，根据分类结果对不同类别的环网柜产品采取不同的库存控制策略。研究结果表明，将数据挖掘算法应用于库存管理实现了企业库存管理决策的科学化和智能化。

Research on ERP data classification of power manufacturing industry based on clustering algorithm

In view of the unclear classification boundary of the traditional manufacturing enterprise warehouse classification method and the difficulty of adapting to the development trend of modern enterprise informatization, the ABC inventory classification algorithm based on the clustering algorithm is proposed to improve the classification accuracy and efficiency of the traditional inventory classification model. Taking the inventory product data of an electric power manufacturing company as the research object, combining the clustering algorithm and the ABC classification method, an evaluation function suitable for actual research scenarios is proposed, and a new ABC classification method based on the k-means algorithm is given. This classification model is used to classify the inventory ring network cabinet products, and based on the product data stored in the ERP system, the inventory ring network cabinet products are divided into three categories: A, B, and C. According to the classification results, different categories of ring network cabinet products are taken Different inventory control strategies. The research results show that the application of data mining algorithms to inventory management has realized the scientific and intelligent decision-making of enterprise inventory management.