Residual useful life estimation for products with two performance characteristics based on a bivariate Wiener process

Tianyu Liu, Zhengqiang Pan, Quan Sun, Jing Feng and Yanzhen Tang

Journal of Risk and Reliability, 2017, vol. 231, issue 1, 69-80

Abstract: Residual useful life estimation plays an important role in the field of prognostics and health management, and condition-based maintenance. This article concerns the issue of residual useful life estimation for degraded components with two performance characteristics. A bivariate Wiener process with random effects is used to model the evolution of two performance characteristics, which are dependent on each other. A bootstrap method is used to estimate the initial parameters with history of degradation data. Once the new degradation information for an individual component is available, the hyper-parameters of the random effects in the model are first updated by the Bayesian theorem. And then, we use a Monte Carlo simulation method to estimate the posterior distribution of residual useful life approximately. Via a simulation study and a case study on Lithium-ion batteries, the effectiveness and validity of the proposed approach are demonstrated.

Keywords: Residual useful life; performance characteristics; bivariate Winner process; Bayesian theorem; degradation (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X16683317 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:231:y:2017:i:1:p:69-80

DOI: 10.1177/1748006X16683317

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().