{"title":"Mechanism equivalence analysis for accelerated degradation tests based on tweedie exponential dispersion process","authors":"Han Wang, Xiaobing Ma, Rui Bao, K. Zhou","doi":"10.1080/16843703.2022.2071536","DOIUrl":null,"url":null,"abstract":"ABSTRACT Mechanism equivalence analysis, focusing on the underlying quantitative relationship between degradation model parameters under different stress levels when the accelerated failure mechanism remains unchanged, has been developed and adopted widely in accelerated degradation tests (ADTs) over recent years. For a specific degradation process, the mechanism equivalence conditions can be derived based on the acceleration factor invariant principle and further utilized to test whether the accelerated failure mechanism remains unchanged or not under different stress levels. In this paper, a unified form of the mechanism equivalence conditions for commonly-used stochastic process models is derived based on Tweedie exponential dispersion process. The unified form can cover the conditions of Wiener, Gamma and inverse Gaussian processes, etc. Based on this, a complete procedure for mechanism equivalence test of ADT is proposed through the joint application of normality test and parameter hypothesis tests. In this way, the availability of the ADT data can be distinguished before using them for lifetime prediction of products. In addition, the effects caused by degradation model mis-specification and ADT data misuse are further analyzed from the perspective of relative error. A simulation example and two real-world case studies are used to demonstrate the effectiveness of the proposed methods.","PeriodicalId":49133,"journal":{"name":"Quality Technology and Quantitative Management","volume":"19 1","pages":"722 - 748"},"PeriodicalIF":2.3000,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Technology and Quantitative Management","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/16843703.2022.2071536","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT Mechanism equivalence analysis, focusing on the underlying quantitative relationship between degradation model parameters under different stress levels when the accelerated failure mechanism remains unchanged, has been developed and adopted widely in accelerated degradation tests (ADTs) over recent years. For a specific degradation process, the mechanism equivalence conditions can be derived based on the acceleration factor invariant principle and further utilized to test whether the accelerated failure mechanism remains unchanged or not under different stress levels. In this paper, a unified form of the mechanism equivalence conditions for commonly-used stochastic process models is derived based on Tweedie exponential dispersion process. The unified form can cover the conditions of Wiener, Gamma and inverse Gaussian processes, etc. Based on this, a complete procedure for mechanism equivalence test of ADT is proposed through the joint application of normality test and parameter hypothesis tests. In this way, the availability of the ADT data can be distinguished before using them for lifetime prediction of products. In addition, the effects caused by degradation model mis-specification and ADT data misuse are further analyzed from the perspective of relative error. A simulation example and two real-world case studies are used to demonstrate the effectiveness of the proposed methods.
期刊介绍:
Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.