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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.
Highlights
Introduction and SummaryNowadays, many products are designed and manufactured to function for a long period before they fail
Determining product reliability is a great challenge to manufacturers of highly reliable products with only a relatively short period of time available for internal life testing
light emitting diode (LED) products have become widely used in a variety of fields with applications ranging from consumer electronics to optical fiber transmission systems
Summary
Many products are designed and manufactured to function for a long period before they fail. Due to the mentioned-above difficulties, the stochastic process formulation turned out to be an alternative approach to model the product’s degradation path Typical examples for this approach are Doksum and Hoyland (1992), Yu and Tseng (2002), Tseng, Tang and Ku (2003), and Lawless and Crowder (2004). Most literature in this area assume that the error term of degradation path follows a Wiener process (which is a time-dependent version of the iid N (0, 1)) or a Gamma process. Motivated from the residual analysis of a real LED data (see Section 6 and Figures 4-5 below), a stochastic diffusion process is more appropriate to model the error term of degradation path.
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