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Customized warranty policies for heterogeneous populations

机译:针对异类人群的定制保修政策

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Warranty policies are typically optimized under the assumption that customer populations are homogeneous-each customer's time to failure is calculated from the same probability distribution. A more realistic approach to the study of optimal warranty duration leads to the consideration of heterogeneous customer populations, where customers can be divided into groups, with each group following a separate failure distribution. This situation can be addressed in two ways. First, the individual failure distributions can be used to find optimal warranty durations for each customer group. Second, the distributions of the groups can be mixed to form a single distribution, used to optimize a warranty policy for the entire population. In this study, our objective is to analyze the economic impact of implementing a customized warranty policy. We begin by calculating failure distributions for each customer group that are dependent on the differentiating customer characteristic as well as one for the entire population. In addition, we develop a demand curve that is a function of the warranty duration and a profit function that utilizes demand, population, and failure properties to determine the total profit generated by each customer group. We can maximize this profit by changing the duration of the warranty to find an optimal warranty policy for each of these customer profiles. The same profit optimization is then used to develop a warranty policy for the overall distribution situation. We find that the implementation of customized warranty policies increases the profitability of the system when operating under the assumption that customization does not change the demand profile.
机译:保修政策通常是在假设客户群是同质的前提下进行优化的-每个客户的故障时间都是根据相同的概率分布计算得出的。研究最佳保修期限的更现实的方法导致需要考虑异构客户群,其中客户可以分为几组,每组遵循单独的故障分布。这种情况可以通过两种方式解决。首先,可以使用各个故障分布来找到每个客户组的最佳保修期。其次,可以将组的分布混合以形成单个分布,用于优化整个人群的保修政策。在本研究中,我们的目标是分析实施定制保修政策的经济影响。我们首先计算每个客户组的故障分布,这些故障分布取决于差异化的客户特征以及整个人群的故障分布。此外,我们开发了一个需求曲线,该曲线是保修期限的函数,并且是一个利用需求,数量和故障属性来确定每个客户组产生的总利润的利润函数。我们可以通过更改保修期限来为这些客户档案中的每一个找到最佳的保修政策,以最大限度地提高利润。然后,将相同的利润优化用于制定总体分销情况的保修政策。我们发现,在定制不会更改需求状况的假设下,实施定制保修政策可提高系统的盈利能力。

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