基于汽车故障统计分析的备件需求预测

运用SPSS软件对某型汽车故障的实际数据进行处理和统计分析,研究了汽车故障发生的规律以及与备件的关系,认为可用4种典型模型对汽车的故障分布进行描述。在确定故障分布类型及参数的基础上,结合整车保有量的历史数据,建立了备件需求预测模型。实例验证了这种方法的准确性高于传统方法,并且在计算机的辅助下可以方便操作。

Demand Forecasting for Spare Parts Based on Statistical Analysis of the Auto Failure Rules

The actual failure dates of a certain type automobile were statistical analyzed using SPSS software,the vehicle failure rules and the connection of spare parts were researched,the result shows that auto faults can be described by four typical distribution models.Based on make sure the distribution and parameters,c all the history dates of vehicle population,a demand forecasting model of auto spare parts was established.This method is proved to be more reasonable than the existing methods through an example,and can be used expediently with computer assist.