A nonlinear mixed-effects model for degradation data obtained from in-service inspections

X.-X. Yuan and M.D. Pandey

Reliability Engineering and System Safety, 2009, vol. 94, issue 2, 509-519

Abstract: Monitoring of degradation and predicting its progression using periodic inspection data are important to ensure safety and reliability of engineering systems. Traditional regression models are inadequate in modeling the periodic inspection data, as it ignores units specific random effects and potential correlation among repeated measurements. This paper presents an advanced nonlinear mixed-effects (NLME) model, generally adopted in bio-statistical literature, for modeling and predicting degradation in nuclear piping system. The proposed model offers considerable improvement by reducing the variance associated with degradation of a specific unit, which leads to more realistic estimates of risk.

Keywords: Degradation; Inspection; Regression model; Mixed effects; Prediction; Reliability (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:94:y:2009:i:2:p:509-519

DOI: 10.1016/j.ress.2008.06.013

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