What are the commonly used models for accelerated life testing? What issues should be noted?

2024-07-02 09:40:18

Acceleration models can be divided into three categories based on the methods they were proposed: physical acceleration models, empirical acceleration models, and statistical acceleration models.

The physical acceleration model is proposed based on the physical and chemical explanation of the product failure process. A typical physical acceleration model is the Arrhenius model, which describes the relationship between product life and temperature stress. Another typical physical acceleration model is the Eyring model, which is based on the theory of quantum mechanics. This model also describes the relationship between product life and temperature stress. Glassten et al. extended the Eileen model and provided a description of the relationship between product life and temperature stress, voltage stress.

The empirical acceleration model is proposed based on the long-term observation of product performance by engineers, and typical empirical acceleration models such as the inverse power-law model, Coffin Manson model, etc. The inverse power-law model describes the relationship between factors such as voltage or pressure stress and product life. The Coffin Manson model provides the relationship between temperature cyclic stress and product life. The statistical acceleration model is based on statistical analysis methods and is commonly used to analyze data that is difficult to interpret using physical and chemical methods.

Statistical acceleration models can be divided into parametric models and non parametric models. The number and characteristics of parameters in a parametric model are determined, while in a non parametric model, the number and characteristics of parameters are flexible and do not need to be predetermined. A parametric model requires a predetermined distribution of the product's lifespan, while a non parametric model is a model with no distribution assumption and is more favored by researchers.

The acceleration factor is an important parameter for accelerated life testing. It is the ratio of a certain life characteristic value of a product under accelerated stress to the life characteristic value under normal stress, also known as the acceleration coefficient, and is a dimensionless number. The acceleration factor reflects the acceleration effect of a certain acceleration stress level in the accelerated life test, which is a function of the acceleration stress. At present, there are roughly two types of research methods for acceleration factors: statistical inference based and prediction based. Although prediction based methods are simple, they cannot provide accurate values for acceleration factors, so they are not as valuable and promising in life assessment as statistical inference based methods.

The accelerated test model is derived from testing the key factors of a product under normal stress levels and one or more accelerated stress levels. Extreme attention must be paid when using an accelerated environment to identify and correctly confirm failures that will occur during normal use and those that do not typically occur. Because accelerated environments generally use stress levels much higher than expected during on-site use, accelerated stress can lead to erroneous failure mechanisms that are impossible to occur in actual use. For example, raising the temperature of the tested product beyond the temperature point of material performance change or the threshold temperature for dormancy activation can lead to failure that would not occur in normal use. In this case, solving this failure will only increase the cost of the product, without any improvement in reliability. Understanding the true failure mechanism to eliminate the root cause of failure is extremely important.