Observed and unobserved heterogeneity in failure data analysis

Rezgar Zaki, Abbas Barabadi, Javad Barabady and Ali Nouri Qarahasanlou

Journal of Risk and Reliability, 2022, vol. 236, issue 1, 194-207

Abstract: In reality, failure data are often collected under diffract operational conditions (covariates), leading to heterogeneity among the data. Heterogeneity can be classified as observed and unobserved heterogeneity. Un-observed heterogeneity is the effect of unknown, unrecorded, or missing covariates. In most reliability studies, the effect of unobserved covariates is neglected. This may lead to inaccurate reliability modeling, and consequently, wrong operation and maintenance decisions. There is a lack of a systematic approach to model the unobserved covariate in reliability analysis. This paper aims to present a framework for reliability analysis in the presence of unobserved and observed covariates. Here, the unobserved covariates will be analyzed using frailty models. A case study will illustrate the application of the framework.

Keywords: Reliability; observed covariate; unobserved covariate; gamma function; frailty models (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:236:y:2022:i:1:p:194-207

DOI: 10.1177/1748006X211022538

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