Introduction
With upcoming data science and neural network knowhow, a lot of
application fields are emerging in the process industry. In order to use
these new methods (e.g. for control algorithms), it is reasonable to
gain experiences with small scale apparatus, but comparable processes
already in the laboratory. The following brief overview shows that there
are good examples for procedures and interoperability when adopting ML
solutions. The main focus is set on an easy-to-follow procedure for the
integration of machine-learning ML solutions following the example of
Min et al. , which is described in the following in more detail.