A non-homogeneous Poisson process predictive model for automobile warranty claims
A non-homogeneous Poisson process predictive model for automobile warranty claims
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DOI：
10.1016/j.ress.2005.12.004
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发表时间：
2007-02
期刊：
影响因子：
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通讯作者：
K. Majeske
中科院分区：
文献类型：
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作者：
K. Majeske
汽车的保修期和使用寿命是以时间和里程的二维空间为特征的。本文提出了一个非齐次泊松过程（NHPP）预测模型的汽车保修索赔由两个组成部分：一个人口规模函数和故障或保修索赔率。人口规模函数在时域中跟踪人口，并通过在车辆超出保修里程限制时从人口中删除车辆来计算里程。该模型使用的强度函数的NHPP的瞬时故障概率模型保修索赔的发生。开发该方法是为了支持汽车制造商使用在车辆寿命的早期部分（前7个月）观察到的索赔来预测剩余保险期（通常为3至5年）的索赔的过程。本文使用制造商提供的保修数据，从豪华轿车证明NHPP模型预测索赔的三个车辆子系统。然后将保修预测与实际观察值和标准预测技术的预测进行比较。
Automobile warranties and thus lifetimes are characterized in the two-dimensional space of time and mileage. This paper presents a non-homogenous Poisson process (NHPP) predictive model for automobile warranty claims consisting of two components: a population size function and a failure or warranty claim rate. The population size function tracks the population in the time domain and accounts for mileage by removing vehicles from the population when they exceed the warranty mileage limitation. The model uses the intensity function of a NHPP—the instantaneous probability of failure—to model the occurrence of warranty claims. The approach was developed to support automobile manufacturers’ process of using claims observed during the early portion (first 7 months) of vehicle life to predict claims for the remainder of coverage, typically between 3 and 5 years. This paper uses manufacturer provided warranty data from a luxury car to demonstrate the NHPP model by predicting claims for three vehicle subsystems. Warranty predictions are then compared with the actual observed values and predictions made with a standard forecasting technique.