Reliability assessment model for multiple stress factors accelerated degradation test using a Wiener process with...

Area of Science:

• Reliability Engineering
• Materials Science
• Statistical Modeling

Background:

• Existing accelerated degradation tests primarily focus on single stress factors, limiting their applicability to real-world scenarios with simultaneous environmental and operating stresses.
• There is a critical need for reliability assessment models that can handle multiple stress factors concurrently to better predict product lifespan.

Purpose of the Study:

• To develop a novel Wiener process-based accelerated degradation test model that accounts for multiple simultaneous stress factors, random effects, and measurement errors.
• To derive the lifetime distribution and approximate mean lifetime under normal operating conditions using the proposed model.

Main Methods:

• Utilizing a Wiener process framework to model product degradation under multiple stresses.
• Employing the profile likelihood approach for maximum likelihood estimation of model parameters.
• Applying the bias-corrected and accelerated percentile bootstrap method for constructing confidence intervals.

Main Results:

• An explicit expression for the lifetime distribution and its approximate mean lifetime under normal operating conditions was derived.
• Maximum likelihood estimates for model parameters and key reliability metrics were obtained.
• Confidence intervals for parameters and reliability metrics were successfully constructed.

Conclusions:

• The proposed Wiener process-based model effectively addresses accelerated degradation under multiple stress factors, random effects, and measurement errors.
• The derived lifetime distribution and reliability metrics provide valuable insights for product reliability assessment.
• Simulation studies and a numerical example validate the performance and applicability of the developed method.