{"title":"Exponential Dispersion accelerated degradation modelling and reliability assessment considering initial value and processes heterogeneity","authors":"Runcao Tian, Fan Zhang, Hongguang Du, Peng Wang","doi":"10.17531/ein/191432","DOIUrl":null,"url":null,"abstract":"In the production and operation, inherent variability and uncertainty necessitate addressing unit-to-unit heterogeneity in initial performance values and degradation processes. This article presents a bi-stochastic exponential dispersion process (BS-ED) designed to account for heterogeneity in both initial performance values and degradation processes. First, based on the ED process, the time and acceleration covariates are introduced to form a nonlinear accelerated ED process, and a random effect coefficient associated with the accelerated stress is incorporated to consider the heterogeneity of the process. Meanwhile, through the modelling of degradation time-shift, a degradation model considering the stochastic initial value of the product performance is developed. To effectively conduct the statistic inference of the BS-ED process, an improved stochastic EM algorithm is proposed, and the information matrix and Ito calculus are combined to estimate the confidence intervals. Finally, the stability of the method is verified by simulation and analyzed by two real cases.","PeriodicalId":508934,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"31 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eksploatacja i Niezawodność – Maintenance and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17531/ein/191432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the production and operation, inherent variability and uncertainty necessitate addressing unit-to-unit heterogeneity in initial performance values and degradation processes. This article presents a bi-stochastic exponential dispersion process (BS-ED) designed to account for heterogeneity in both initial performance values and degradation processes. First, based on the ED process, the time and acceleration covariates are introduced to form a nonlinear accelerated ED process, and a random effect coefficient associated with the accelerated stress is incorporated to consider the heterogeneity of the process. Meanwhile, through the modelling of degradation time-shift, a degradation model considering the stochastic initial value of the product performance is developed. To effectively conduct the statistic inference of the BS-ED process, an improved stochastic EM algorithm is proposed, and the information matrix and Ito calculus are combined to estimate the confidence intervals. Finally, the stability of the method is verified by simulation and analyzed by two real cases.
在生产和运行过程中,由于固有的可变性和不确定性,有必要解决初始性能值和降解过程中单位与单位之间的异质性问题。本文提出了一种双随机指数离散过程(BS-ED),旨在考虑初始性能值和退化过程的异质性。首先,在 ED 过程的基础上,引入时间和加速度协变量,形成非线性加速 ED 过程,并加入与加速应力相关的随机效应系数,以考虑过程的异质性。同时,通过降解时移建模,建立了考虑产品性能随机初始值的降解模型。为了有效地进行 BS-ED 过程的统计推断,提出了一种改进的随机 EM 算法,并结合信息矩阵和伊藤微积分来估计置信区间。最后,该方法的稳定性得到了模拟验证,并通过两个实际案例进行了分析。