使用贝叶斯方法预测二维保修期内的故障

IF 0.9 Q3 STATISTICS & PROBABILITY
Valeriana Lukitosari, S. D. Surjanto, Sena Safarina, Komar Baihaqi, Sri Irna Solihatun Ummah
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引用次数: 0

摘要

传统上,保修成本被假定为基于损坏索赔产生的平均成本的维修成本。一些研究在估算故障分布参数时考虑了最小二乘法和最大似然估计法。然而,本研究采用贝叶斯方法,使用从先验分布和似然函数得到的后验分布。与其他方法相比,贝叶斯方法的艾凯克信息准则(AIC)值最小,因此更适合用于估计参数。接近自然的失效预期可用于分析存活率,以确定产品在失效前还能使用多长时间。本研究中的数字示例是发动机排量为 125 CC 的摩托车,采用 Weibull 分布,而 150 CC 和 160 CC 采用指数分布。本研究的新颖之处在于,二维自由修复法可以在考虑车龄和里程的情况下预测故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Predicted Failure on A Two-Dimensional Warranty Using the Bayesian Approach
Traditionally, the warranty cost is assumed to be the cost of repairs based on the average cost that arises from a damage claim. Several studies have considered the Least Square and Maximum Likelihood Estimation methods in estimating the parameters of the failure distribution. However, this study uses the Bayesian method using the posterior distribution obtained from the prior distribution and the likelihood function. The Bayesian approach is more optimal to use in estimating parameters because it has the smallest value of Aikaike’s Information Criterion (AIC) compared to other methods. Failure expectations that are close to natural can be used to analyze survival to determine how long a product will last before the failure. The numerical example in this study, is the type of motorcycle with an engine capacity of 125 CC with the Weibull distribution, while the 150 CC and 160 CC with Exponential distribution. The novelty in this study is that the free repair approach in two-dimensional can be anticipated with failure considering the dimensions of age and mileage.
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来源期刊
CiteScore
1.60
自引率
12.50%
发文量
24
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