one of the great statistical minds of the 20th century,
wrote in 1976
All models are wrong, but some are usefull.
and keen popularizer of physics said in his
1964 lecture on the scientific method
It doesn't matter how beautiful your theory is, it doesn't matter how smart you are.
If it doesn't agree with experiment, it's wrong.
A process can be seen as the fundamental entity of natural science.
The pragmatic but rigorous nature of the scientific method
is based on experimental
not on proofs which are a key component of the mathematical language of science.
With this platform, we are trying to support the development and usage
as a key component of experimental and theoretical
scientific investigations. We are using
or as Albert Einstein said, we like to keep things as simple as possible, but not simpler
Our issues are to
- deploy process models as computational documents,
computation of an epidemic (in german).
- demonstrate the solution of real world problems, e.g. by our
sheet cooling section set value prediction.
- demonstrate the Model Predictive Control approach,
e.g. by our
EAF MPC demonstration.
- define clear definitions and barrier free software
interfaces for process models.
- define quality criteria and quality assurance for process models.
- provide tools for model identification and parameterization.
- provide tools for the design of experiments
- provide tools for the seamless deployment and integration of process models.
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Frequently Answered Questions (FAQ)
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