Targeted test planning for maximum knowledge.
The Design of Experiments (DoE) describes efficient methods for identifying the key influencing variables and their effect on a specific target variable.
In industrial practice, so-called one-factor-at-a-time experiments are still frequently carried out. However, these do not make use of the possibility of varying several influencing variables at the same time – and thus give away the greatest statistical advantage of DoE.
Advantages of statistical design of experiments
- Efficient use of resources through combined test approaches
- Consideration and control of unknown trends in the design of experiments
- High statistical validation of the results
- Clear cost forecast and predictability
Various experimental designs
Design of Experiments offers different approaches for different objectives:
- Full factorial designs for identifying main effects and interactions of different influencing factors
- Response surface approaches for optimising a target variable while taking non-linear influences into account
- Composite experimental designs when a combination of different approaches is required
- Partial factorial designs for selecting the most important influencing factors from a large number of parameters
Our services
- Joint definition of the investigation objective in the area of product and process optimization
- Creation of test plans for various analysis objectives
- Joint implementation of initial pilot tests
- Ensuring a clear procedure for carrying out tests and recording data
- Statistical evaluation of the test results
- Implementation of the findings in product or process improvements
- Evaluation of real improvements compared to previous settings
In combination with other methods
DoE is a central method in test planning and plays an important role in the development of ageing models & physics of failure as well as in the validation of new technologies in the field of devices & systems. The combination with Accelerated Life Testing allows load influences to be analyzed even more specifically and development times to be further reduced.
