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Stochastic Diffusion Modeling of Degradation Data

Sheng‐Tsaing Tseng, Chien‐Yu Peng

2021Journal of Data Science83 citationsDOIOpen Access PDF

Abstract

Accelerated degradation tests (ADTs) can provide timely relia bility information of product. Hence ADTs have been widely used to assess the lifetime distribution of highly reliable products. In order to properly predict the lifetime distribution, modeling the product’s degradation path plays a key role in a degradation analysis. In this paper, we use a stochastic diffusion process to describe the product’s degradation path and a recursive formula for the product’s lifetime distribution can be obtained by using the first passage time (FPT) of its degradation path. In addition, two approxi mate formulas for the product’s mean-time-to-failure (MTTF) and median life (B50) are given. Finally, we extend the proposed method to the case of ADT and a real LED data is used to illustrate the proposed procedure. The results demonstrate that the proposed method has a good performance for the LED lifetime prediction.

Topics & Concepts

Degradation (telecommunications)Product (mathematics)Computer sciencePath (computing)Mean time between failuresDiffusionReliability engineeringStochastic processAlgorithmStatisticsMathematicsEngineeringFailure rateProgramming languageGeometryThermodynamicsTelecommunicationsPhysicsReliability and Maintenance OptimizationStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering Design
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