基于威布尔分布的车辆首次故障索赔预测
Warranty Claims Forecasting Based on Weibull Distribution for the First Failure
孙喜龙 1荣宝军 2姜燕3
作者信息
- 1. 大理大学工程学院,云南 大理 671003;一汽奥迪销售有限责任公司,浙江 杭州 310020
- 2. 吉林工程技术师范学院机械工程学院,吉林 长春 130052
- 3. 大理大学公共卫生学院,云南 大理 671003
- 折叠
摘要
基于车辆首次故障的索赔数据,以车辆服役月的索赔故障数n为随机变量,利用双参数威布尔分布对样本进行拟合,并利用极大似然估计方法对双参数威布尔分布的参数进行估计,建立车辆服役月的累积故障数预测模型.结果表明,利用过去12个月的索赔数据,预测未来1至3月故障数的平均相对误差为0.9％;4至6月的平均相对误差为3.8％;但预测超过6个月的故障数,相对误差较大.为了验证截断数据样本大小,对预测精度的影响,分别建立截断数据T=6、T=9的预测模型,预测未来3个月故障数的平均相对误差分别为16.1％、2.4％,结果表明增加样本数据量可以有效提高预测精度.使用T=12的索赔数据,预测未来连续3个月的索赔故障数,预测精度较高;如果仅预测未来1个月的索赔故障数,使用T=9的索赔数据,预测精度同样满足分析要求;但不建议使用低于6个月的索赔数据进行预测.
Abstract
Based on the warranty claim of the first failure,the failure number n in month-in-service(MIS)is taken as the random variable,and used the two-parameter Weibull distribution to fit the warranty claim data,and used the maximum likelihood mothed to estimate the parameters of Weibull distribution,and established the prediction model of the cumulative failure quantity.The results show that,using warranty data in the past 12 months,the mean relative error(MRE)of predicting for the future from 1 to 3 months is 0.9％,and MRE of predicting from 4 to 6 months is 3.8％,but MRE in predicting the number of failures beyond 6 months is very bigger.In order to validate the influence of the sample size of truncated data on the prediction accuracy,the prediction models with truncated data T=6 and T=9 are established,and MRE in predicting the number of faults in the next 3 months is 16.1％and 2.4％,respectively,which shows that increasing the sample data size can effectively improve the prediction accuracy.The warranty data of T=12 is used to predict the number of faults in the next 3 consecutive months,and the prediction accuracy is very good.If only the number of claim faults in the next one month is predicted,the warranty data of T=9 can be used,because the prediction accuracy can also reach the analysis requirements.However,it is not recommended to use warranty data less than 6 months for forecasting.
关键词
可靠性/保修数据分析/索赔预测/威布尔分布/极大似然估计Key words
reliability/warranty data analysis/warranty claim prediction/Weibull distribu-tion/maximum likelihood estimation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据