Accelerated Aging Testing: Extrapolating Service Life With Confidence
We rely on accelerated aging tests to estimate the useful life of products in their end-use environment.
Getting it right is particularly important when failure to perform can have severe consequences, as is in healthcare, for instance.
Getting it right can be tricky though, as the test conditions must reproduce the failure modes observed in natural aging over years while compressing the test time to weeks.
This is where having an intimate understanding of how material properties relate to product performance is crucial. A successful program to estimate the service life of a product relies on defining the following key parameters:
Key performance metrics that products have to meet to perform in their intended application
The relationship between the performance metrics and the material properties of the product
The environmental stressors (i.e. temperature, humidity, radiation, chemicals, mechanical stress, etc.) the product is likely to be exposed to and their intensity
How the critical material properties are affected by that exposure
The test conditions that increase the intensity of the environmental stressors and the rate of performance loss while maintaining the same degradation pathway as in natural aging
The acceleration rate caused by the stressors, to extrapolate a service life from the accelerated aging test results
ASTM F1980 is an excellent standard when it comes to testing medical devices under accelerated conditions. It provides a framework to determine an accelerated aging factor (AAF) based on the kinetics of chemical degradation.
This standard exemplifies the often-used idea that increasing the temperature by 10 °C doubles the rate of reaction (Q10 = 2). It is an estimate based on conservative assumptions; the effective lifetime can be longer than predicted.
In addition, the actual acceleration factor will vary for products of different composition, making it challenging to draw conclusions from comparative aging studies involving products made of dissimilar materials (e.g. vinyl vs. silicone). More accurate AAFs can be rigorously measured using the procedure outlined in standard ASTM D7160, based on the Arrhenius equation for the kinetics of chemical reactions.
As an example, let’s take products A and B, made of different materials.
Both products are tested at 60 °C and fail in 2 months. Are they equivalent? Only if their AAFs are equivalent. If, for instance, Q10 for Product A is 2 and for Product B is 4, the expected service life of Product A at 20 °C is 3 years, while it is 51 years for Product B.
Or what if Product A undergoes a thermal transition (e.g. Tg) at 50 °C? The results obtained at 60 °C cannot be used to estimate real-time aging at 20 °C, and we cannot compare products A and B.
This simple example illustrates how confidently extrapolating service life relies on material science and careful consideration of the key parameters listed above.
The same recommendations are valid and even more crucial for more complex cases involving multiple stressor factors (e.g. temperature and humidity, or temperature and radiation) or when physio-chemical phenomena other than kinetics control the accelerated aging factor (e.g. diffusion).
Getting service life estimation right is achievable, with the proper upfront work. It is essential, though, to also carry out real-time aging experiments in parallel. How will we know we got it right otherwise?
The answers from real-time aging studies may be slow, but they will help refine an accelerated aging study protocol… or catch issues before they impact customers if the accelerated aging test missed its mark.