Understanding ageing - calculating service life.
Lifetime models describe the time until a failure criterion (end of life) occurs depending on one or more influencing variables. They are based on the physics of failure mechanisms (physics of failure), such as diffusion processes or material-related ageing processes.
Significance in product development
Knowledge of a product- or technology-specific life cycle model makes it possible to significantly reduce testing costs during development. This is because a robust model can be used to convert the results of accelerated life cycle tests to real field conditions.
Well-known model approaches include, for example:
- Arrhenius model
- Eyring model
- Inverse power law
- Coffin-Manson
- Paris-Erdogan
- Black's law
Structure and determination of service life models
A service life model is created in two steps:
- Identification of the main influencing variables such as absolute temperature, temperature strokes, mechanical stresses or chemical concentrations
- Parameterization of the model through statistically planned experiments in which the model parameters are determined
In this way, ageing mechanisms can be quantified and reliable predictions made about product service life.
Our services
- Identification of the appropriate model approach based on the damaging influencing variables
- Definition of the required model quality
- Planning and monitoring of tests to parameterize the model
- Determination of gathering factors on the basis of a service life model
In combination with other methods
Lifetime models are closely related to accelerated life testing and design of experiments (DoE). While DoE identifies the key influencing variables, accelerated tests provide the database for parameterizing the models. Together, they enable precise predictions and efficient validation in industries such as energy, automotive and electronics.
