Reliability Modeling Method for Constant Stress Accelerated Degradation Based on the Generalized Wiener Process.

Area of Science:

• Engineering
• Reliability Engineering
• Materials Science

Background:

• Products often exhibit nonlinear degradation, complicating accurate reliability estimation.
• Traditional models may not fully capture the impact of accelerated stress on degradation parameters.
• Understanding product degradation is crucial for effective engineering maintenance and reliability management.

Purpose of the Study:

• To develop an advanced degradation model for nonlinear behavior under constant-stress accelerated degradation testing (CSADT).
• To enhance the accuracy of reliability estimates and failure time predictions.
• To account for the influence of accelerated stress on both drift and diffusion coefficients.

Main Methods:

• Proposed a novel degradation model based on a generalized Wiener process.
• Incorporated random effects to address individual product variability.
• Employed maximum likelihood estimation (MLE) and the expectation-maximization (EM) algorithm for parameter estimation.
• Derived the probability density function (PDF) of remaining useful life.

Main Results:

• The proposed model effectively fits nonlinear degradation processes.
• Demonstrated improved accuracy in failure time prediction compared to existing methods.
• Validated using simulated CSADT data and stress relaxation data.
• The model successfully accounts for stress effects on drift and diffusion parameters.

Conclusions:

• The generalized Wiener process model offers a robust approach for reliability analysis of products with nonlinear degradation.
• The method provides more accurate failure time predictions, aiding in engineering maintenance and reliability management.
• This work contributes to a better understanding of product degradation under accelerated testing conditions.