The advantages of statistical Design of Experiments (DoE)
Approach you problems efficiently using Statistical Design of Experiments (DoE)
Depending on the complexity of the problem setting, sequential design of experiments yields the appropriate information. If there are many potential influence factors, the main aspect is to separate the important from the negligible ones. Only after identifying the main contributors and their interactions, a detailed optimisation is performed. This is a very efficient approach. [More...]
- A limited (and small) number of experiments.
- The factor region of interest is covered optimally by the chosen experimental settings.
- Using statistical Design of Experiments (DoE) also allows for investigating factor interactions (in contrast to the often used "one-factor-at-a-time"-method).
- You do not have to perform the statistical evaluation of your experimental results yourself. DoE software tools (e.g. the expert system STAVEX) do this automatically for you. STAVEX subsumes the results in easy understandable, natural language. Therefore it is not necessary to have a deeper previous knowledge in statistics.
- Modern DoE software tools (e.g. the expert system STAVEX), make the application of statistical Design of Experiments easy, even in complex situations. In particular, they yield meaningful results also under real-life restrictions, such as insufficient factor independence, presence of mixture factors or alternative factors, or for failed experiments.
- The graphics produced by the DoE software tools allow for a structured and intuitive analysis of the results.
More reasons for statistical Design of Experiments (DoE)
- The best way to cope with experimental variation is a systematic investigation.
- Trial and Error can yield a result quickly, but it also may need some more time...
- Nobody stops you from breaking off a series of experiments if you are already content with the current result.
- The user-friendly concept of STAVEX guides the user through all stages of sequential Design of Experiments (DoE). On completion of a stage, it suggests how to proceed further. Eventually, the entire project is clearly documented within a single file.
Any questions about statistical Design of Experiments (DoE)?
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