Improved Gamma Process for Degradation Analysis under Non-linear Condition  
Author Zhaoyi Fan


Co-Author(s) Hua Ju; FengBin Sun


Abstract Abstract - Some life tests result in few or no failures. In such cases we can, and should, consider using degradation meas- urements to assess reliability. In real world, product degrada- tion is a stochastic process. Since such degradation is often- times seen as a monotonous process, literature widely uses Gamma Process to describe and quantify degradation. How- ever, in these publications, scale parameter is considered a constant over time and results under this assumption may have big deviation from the actual measurements under non-linear condition. The purpose of this paper is to improve Gamma Process method to fit a broader class of degradation models. Firstly we use MLE to estimate the parameters under the timely constant-scale- parameter assumption and analyze why the model does not fit data well. Then we propose an im- proved model to improve the method and use Monte Carlo simulation to verify the validity of the improved method.


Keywords Reliability, Degradation, Gamma Process, Non-linear
    Article #:  21267
Proceedings of the 21st ISSAT International Conference on Reliability and Quality in Design
August 6-8, 2015 - Philadelphia, Pennsylvia, U.S.A.