 A common random effect induced bivariate gamma degradation process with application to remaining useful life predictionKai Song and Lirong Cui Reliability Engineering and System Safety, 2022, vol. 219, issue C Abstract: Due to the complex structures and the multi-functionality of modern products, there are usually two or more performance characteristics which can reflect a product’s degradation states. The degradation processes corresponding to these performance characteristics are dependent in general, which brings challenges to the degradation data analysis. In this paper, a gamma process based degradation model is developed for the bivariate dependent degradation data, where the dependency between the two degradation processes is captured by a common random effect naturally. The expectation maximization algorithm is employed to estimate the model parameters. Then, a real-time prediction method for a product’s remaining useful life is proposed using the Bayesian method. Finally, both the simulation study and the case study are provided for illustration, whose results demonstrate that the proposed model as well as the corresponding inference methods does work well. Keywords: Bivariate degradation data; Expectation maximization algorithm; Gamma process; Maximum likelihood estimation; Remaining useful life prediction (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021006797 DOI: 10.1016/j.ress.2021.108200 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.