基于改进Apriori算法的动车组备件的库存管理研究

Based on the improved Apriori algorithm of the EMU spare parts inventory management research

车辆主机厂承担了列车的主要生产检修工作,科学地备品备件的库存管理是节约成本的关键问题,但是目前来看,还没有专门针对主机厂的备品备件方面管理的研究,因此,本文旨在研究如何更加高效地科学管理车辆主机厂的备品备件管理,提出通过Web页面并运用改进后的Apriori的多维数据关联规则算法挖掘列车的各类关键设备购买行为之间关联性规则,结合实际生产中的具体数据安排备件库存的增减,通过补货批量和补货时机的最优化来减小库存成本,科学地规划统筹备品备件的库存管理。

Vehicle makers take the main production of repair work of trains,so scientific inventory management of spare parts is the key to cost savings.But there is not specific research for makers of spare parts management until now.Therefore,the purpose of this paper is to study how to make the scientific management of vehicle makers about spare parts management more efficiently and we put forward using the improved Apriori algorithm multidimensional association rule data to find the correlation between all kinds of key equipment purchase behavior rules of the train in the web.Through the replenishment quantity and replenishment time optimization,we can reduce inventory costs and make the scientific inventory management.