A non-linear fuzzy degradation model for estimating reliability of a polymeric coating

• Reliability analysis is performed by nonlinear degradation model within uncertainty
• Calibration regression method is used to quantify the uncertainty.
• Knowledge about the process is considered to calculate an acceleration factor.
• Fuzzy numbers to include uncertainty without information loss are used.
• Industrial inspection frequency plan based on certain reliability is showed.

Oftentimes, material components follow non-linear degradation because the material loss trough time is non-linear; the components present different levels of resistance during a degradation process. Constructing predictions of the component life span and performing reliability analyses regarding degradation is possible by non-linear regression. Generally, this method ignores the prediction error in the extrapolated time and it does not account measurement error in the observed sample paths. In this paper, it is proposed new means for predicting time to failure of the components, using a calibration regression method for measuring the error prediction in the extrapolation process. In order to consider the uncertainty, we proposed to perform the estimated times by a trapezoidal fuzzy numbers, providing a more reliable prediction without loss of information. Since the times to failure are shaped by fuzzy numbers, it was adapted the fuzzy probability theory to the classical reliability analysis for estimating the fuzzy reliability of a component. An accelerated test of a polymeric coating process was performed and also an application for a preventive maintenance frequency was proposed.