模具制造企业备件库存分类方法研究

摘要

Based on the spare parts management system of mold manufacturing enterprises, the spare parts of main features of the mold manufacturing enterprises were analyzed,combining the traditional ABC classification method and the basic principle o/BP neural network, and the spare parts'ABCD classification method which came from BP neural network algorithm were proposedThrough the repetitious network training on the sample data,an ideal classified model was establishedAt the same time,the accuracy of the model was tested with the test samples and confirmed that the reliability had reached to the prospective goals.%以模具制造企业中的备件管理系统为研究背景,重点分析模具制造企业备件的主要特征,结合传统ABC分类法和BP神经网络的基本原理,提出了基于BP神经网络算法的备件ABCD分类法,通过对样本数据进行多次网络训练,最终确定理想分类模型,同时对此分类模型进行精度检验,证实其精度达到预期目标.